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Fresno State Transportation Institute

Projects  

Year 1 (2018)

PI's Background: Dr. Nancy Van Leuven
Project's Start date: 1 July, 2018
Project's End date: 31 December, 2018

Executive Summary: As outlined by the Fresno County Transportation Institute (FSTI), this research project focuses on Objective 7 of SB 1: "To inform and improve decision-making on transportation-related issues through timely, relevant, and nonpartisan public opinion polling of Californians"; specifically, the Fresno County area. In addition to researching best practices about public opinion polling, this project will strengthen regional partnerships by involving local leaders in discussions about needed information and audiences. The aim is to create, pilot and evaluate a polling and survey tool to use in a deliberative decision-making process appropriate for issues associated with transportation-related topics. This will be accomplished by:
● Identifying existing tools and previous scholarship
● Analyzing major constructs or focal points of existing tools to identify major issues
● Identifying key informants or stakeholders who represent a broad sub-sample of the population in the FSTI region
● Soliciting participation in the structured interview
● Prioritizing issues identified by key stakeholders, including: Advanced multimodal and transit solutions and optimization of existing systems; facilitating mobility, improving air quality and reducing traffi congestion and energy demand; and other topics discovered in this research project
● Creating the focus group/interview script
● Administering the tool after capturing a full representation of publics from multiple cultures
● Analyzing data results compiled by researchers with student assistants
● Review of draft results with key informants or stakeholders
● Finalizing results and recommendations for submission to FSTI
● Disseminating report to desired audiences as requested by FSTI
● Identifying future funding and research possibilities

California's Central Valley area -- especially the FSTI area of focus among the 15 cities within Fresno County -- faces many challenges related to transportation, energy development, and air quality. As recognized in Senate Bill 1, this area is increasingly recognized as a congested corridor needing policies to address these challenges. Such policies require technical and scientific expertise, as well as support from multiple stakeholders, including the public. The inherent tension between policies that have a scientific basis yet require consensus among diverse stakeholders can lead to gridlock and inaction (Anderson, 2015).

Decision-making processes for transportation management have evolved over time and become more complex with increased pressure from exploding populations and subsequent development, as well as advances in transportation technologies. The risks and uncertainties of such processes (in both the near and long term) are heightened by controversial activities as well as opposing viewpoints such as rural vs. urbanized areas. This project aims to explore a decision-making approach based on informed deliberation between experts, stakeholders, decision-makers, and the public that could avoid the potential for gridlock.

Final Report: Please click here.

PI's Background: Dr. Maryam Nazari

Project's Start date: 16 June, 2018

Project's End date: 31 December, 2018

Executive Summary: This project aims to investigate the application of Tire-Derived Aggregates (TDA) in precast ‎concrete slabs in road pavements and bridge decks serving non-auto traffic, such as bicycle ‎routes. Application of TDA as a green, durable, and economically-efficient material, enhances the ‎sustainability of transportation infrastructure. The project addresses the following objectives, which ‎are aligned with the goals of the SB-1 and the FSTI Consortium:‎
• ‎"Long-term road and bridge maintenance and pavement/concrete rehabilitation needs" (SB-1 ‎Objective 3) of the bicycle routes, through the application of durable rubberized aggregate ‎concrete in the design and construction of precast concrete panels for pavement and bridge ‎decks; and
• ‎"Facilitating road and bridge rehabilitation/maintenance decision-making" (SB-1 Objective ‎‎2), through performing life-cycle cost analysis incorporating application of TDA in the ‎construction of durable precast pavement slabs and bridge decks.‎
The use of precast concrete elements in pavement applications has been successfully applied for ‎over 40 years in the USA (AASHTO). Precast concrete has also proven to be a durable, high-performance solution for bridges. To design and construct non-auto transportation routes in this ‎project, precast concrete panels will be used for pavement and bridge deck applications. To ‎address their long-term maintenance and rehabilitation needs, tire-derived aggregate concrete ‎‎(TDAC) will be used in the construction of precast elements. The TDA, recycled from waste ‎rubber materials in tires, replaces coarse aggregates in concrete. As reported in CalRecycle ‎‎(2016), TDA has been used for a number of applications in the state of California. Examples are ‎embankment fill material, retaining wall backfill material, vibration-damping material, and asphalt ‎pavements. Tires are made of very durable engineered materials in order to provide reliable, safe, ‎and predictable behavior while on the wheels of vehicles. Using these durable materials in ‎infrastructural construction will lessen their maintenance and rehabilitation needs. Further, this ‎application will divert waste tires from landfills. Higher energy dissipation and lower strength of ‎the rubberized concrete compared to the conventional concrete were reported in different ‎research studies (Tupco and Avcular 1997; Al-Tayeb et al. 2012; Miller and Tehrani 2017). Some ‎researchers (Atahan and Sevim 2008) also utilized this material in traffic barriers. As shown in ‎these studies, energy absorption enhancement is a unique feature of TDA concrete, which could ‎be efficiently used in bicycle routes and infrastructure. The application of rubberized precast ‎concrete panels cushions effectively the impact with the ground in case of falls and therefore ‎ensures a safe non-auto transportation system (Dondi et al. 2011). In this research, the possibility ‎of application of TDA concrete in precast pavement slabs and bridge decks will be investigated ‎by understanding their mechanical properties and presenting the optimal percentage of aggregate ‎replacement to achieve the best performance for precast applications. Moreover, a life-cycle cost ‎analysis will be developed to investigate the long-term benefits of constructing green and durable ‎infrastructure on transportation investments. ‎

Final Report: Please click here

PI's Background: Dr. Yushin Ahn

Project's Start date: 16 June, 2018

Project's End date: 31 December, 2018

Executive Summary: It has been of importance to monitor the actual status of existing structures such as bridges ‎regarding maintenance and assessment of the structure. Remote sensing technique has been one ‎of the efficient, economic and non-intrusive method for this task for years. ‎
Recent technological advancement in digital cameras brings consumer grade digital camera to the ‎game with high resolution and high frame rates. Digital photogrammetry, science of making ‎reliable measurement of photographs is well-suited and well-established for the monitoring tasks. ‎
‎ It is also a typical curriculum in civil engineering to test the reliability and stability of specimen ‎in the lab as in Figure and recent studies show encouraging results and claim the potential of ‎photogrammetric approach of these tasks. ‎
Figure Examples of photogrammetric monitoring in laboratory. (a) Beam deformation test (b) ‎concrete failure test (c) shake-table test (d) shake table displacement changes
Here, we take fullest advantage of Civil Engineering Lab tests at California State University at ‎Fresno. Shake-table test, one of stability test of structure or pile of soil when pressure is given ‎‎(See Figure (c)) is our primary test using digital camera and all necessary knowledge and practice ‎will be sought to perform Bridge Deformation Inspection Monitoring later. ‎
Through this project, we apply digital photogrammetry to investigate 1) the limitation and ‎potential of recent camera system in deformation test, 2) high frame rates, in other word, slow ‎motion capability on fatigue or vibration monitoring and 3) applicability in bridge deflection and ‎vibration in time.‎
We design this project to combine research and education together. In structural/geotechnical lab, ‎this method will be introduced to give students another view in solving problems and critical ‎thinking. This is also beneficial to geomatics students as well, for this topic is relevant for ‎photogrammetry, industrial tooling and deformation monitoring survey. ‎
Two students, one undergraduate and graduate will participate this project and help data ‎acquisition and make tutorials so that material will be utilized in real lab.‎
The core of proposed study have a good potential and flexibility in applying similar works such ‎as change detection, feature tracking and time-series analysis of images. The module that we will ‎be developing and results of this study will attract grants in Caltrans, NSF and will put us in ‎better position in industrial collaboration.‎

Final Report: Please click here

 

PI's Background: Dr. Chih-Hao Wang 

Project's Stardate: March 1st 2019

Project's End date: December 31st 2019

Executive Summary:

Fresno has been regarded as a city with a high concentration of poverty. There-fore, it is extremely important to examine whether transportation inequality exists in Fresno because transportation shapes residents’ economic opportunities, physical activities and social interactions. This study is to address this issue by looking at whether a resident of Fresno would have an equal opportunity to ac-cess to a variety of urban opportunities, such as jobs, physical activities and din-ing, social interactions, and public facilities. Two non-auto (green) transportation modes (i.e. public transit and cycling) are considered in this study since not eve-ryone can afford for a private vehicle. We fist use the GIS (Geographic Infor-mation System) to illustrate the service area by using these two green transporta-tion modes, respectively, for each block group in the city. With the recently com-pleted “open street” data, we then use the service area to count the number of various urban opportunities (jobs, restaurants, parks, multi-use paths, schools, libraries, and schools) that a block group can reach within a 10-, 20-, 30-, 45-, and 60- minute-long travel time by transit or cycling. This is based on the will-known cumulative opportunity approach to measure the accessibility of a com-munity to various opportunities in a city. To examine whether there exist differ-ence in accessibility between a community and one another, we compare an ar-ray of computed accessibilities between better-off communities and worse-off ones. Several economic and social-demographical factors are considered to di-vide the communities into two groups, including income, property value, school enrollment, vehicle ownerships, race, and age. This would allow for a more com-prehensive way to compare the accessibility for many socioeconomic aspects. Another innovation in this study is to create a platform to flexibly group communi-ties into two for the accessibility comparison. This would reveal whether the re-sults are sensitive to the threshold used for grouping. The comparison results suggest that the current green transportation network do help with the accessibil-ity in terms of economic opportunities for economically disadvantaged neighbor-hoods. However, the city might need to focus on improving the efficiency of the bus system to provide a wider service area for more urban opportunities. Stu-dents might be a good target for further study to better understand their needs because there is no consistent patterns found from the results. Finally, the find-ings point out that more efforts on providing multi-use paths need to be done to improve the accessibility by cycling for non-white and adolescent groups. 

Final Report: Please click here

PI's Background: Dr. Christian Wandeler

Project's Start date: March 1st, 2019

Project's End date: October 31st, 2019 

Executive Summary:

The complexity of a globalized world, accelerating technological advances, and rapid change challenge educational systems. Around the world the call is to develop 21st century skills with a focus on career readiness, ability for lifelong learning, and collaboration skills. The development of the foundational elements of civic engagement (civic knowledge, skills, and dispositions) of children and youth is also a dominant concern for educators and policymakers. Unfortunately, not all youth have the same opportunities to develop civic self-efficacy. However, the civic empowerment engagement gap can be closed by providing underserved students with interactive and authentic civic experiences.

We strove to create such an authentic civic experience and piloted the Fresno State Transportation Challenge (FSTI) at an elementary school in the Washington Unified School district, Fresno County, California. The research question for this innovation grant was: Can we leverage the expertise and resources of the Fresno State Transportation Institute to bring high quality educational experience to underserved students and help them improve their communities?

Final Report: Please click here.

 

Year 2 (2019)

 PI's Background: Dr. Chih-Hao Wang

Project's Stardate: May 1st 2019

Project's End dateDec 31st 2019

Executive Summary:

This study aims to develop a multi-objective optimization modeling framework to maximize the total accessibility to multi-use paths while minimizing the gap between low- and high- accessibility neighborhoods by an optimal allocation of active transportation investments for Fresno, California.

Accessibility to multi-use paths is calculated for Fresno, California that measures the total length of multi-use paths (walkway and bikeway) a resident could reach to from the own block group with a 30 minute cycling ride.
A geographically weighted regression (GWR) model is used to capture the local relationships between accessibility to multi-use paths and previous transportation investments (walkway, bikeway, and primary and secondary roads), while controlling for other socioeconomic factors.
The marginal-effect analysis for the GWR results indicates economically efficient, inefficient, and indifferent locations for further investments.
The GWR results are embedded into a multi objective optimization modeling framework to improve accessibility to multi-use paths over the city and simultaneously address inequality in active transportation accessibility.
The methodology of this multi-objective optimization modeling provides decision makers a new insight into the problem of making of an economicallyefficient and socially-equal active transportation plan to foster public health.

Final Report: Please click here.

PI's Background: Dr. Christian Wandeler 

Project's Stardate: May 1st 2019

Project's End dateDec 31st 2019

Executive Summary:

Project Objective

With the “Fresno State Transportation Challenge” we want to create an authentic civic service learning experience, where K-12 students, K-12 teachers, university students and community members work together on transportation related projects. The goal is to bring an innovative pedagogical approach to the Central Valley, particularly to underserved students.

 As the Fresno State Youth Transportation Challenge we want to engage K-12 students, K-12 teachers, university students and community members in transportation related projects, so that…

 K-12 STUDENTS

a)   develop their knowledge and sensitivity in regards to transportation related issues,

b)   develop awareness of transportation related careers (e.g. law, policy, engineering, advocacy…),

c)   practice their academic skills (e.g. literacy, STEM),

d)   develop their 21st century skills: critical thinking, communication, collaboration, and creativity,

e)   develop their leadership and citizenship skills,

f)    develop an agile, growth mindset,

g)   increase their overall sense of hope and self-efficacy to create a healthier and more prosperous future for themselves, their community, and their planet.

 

K-12 TEACHERS

a)   develop their knowledge and sensitivity in regards to transportation related issues,

b)   develop awareness of transportation related careers (e.g. law, policy, engineering, advocacy…),

c)   learn state of the art pedagogy to support the development of 21st century skills: critical thinking, communication, collaboration, and creativity

d)   teachers passion for project-based learning and service learning

e)   develop an agile, growth mindset

f)    develop teachers’ mindset as change agents and interrupters of negative cycles.

 UNIVERSITY STUDENTS

a)   develop their knowledge and sensitivity in regards to transportation related issues, transportation related careers (e.g. law, policy, engineering, advocacy…),

b)   learn to work with youth

c)   potentially increase their own interest for teaching profession

d)   give back to community

e)   increase engineering paths, recruitment

 COMMUNITY

a)   develop their knowledge and sensitivity in regards to transportation related issues,

b)   develop awareness of transportation related careers (e.g. law, policy, engineering, advocacy…),

engage with youth, share their knowledge and perspectives, support projects.

Background

The complexity of a globalized world, accelerating technological advances, and rapid change challenge educational systems. Around the world the call is to develop 21st century skills with a focus on career readiness, ability for lifelong learning, and collaboration skills (Ananiadou & Claro, 2009). The development of the foundational elements of civic engagement (civic knowledge, skills, and dispositions) of children and youth is also a dominant concern for educators and policymakers. Unfortunately, not all youth have the same opportunities to develop civic self-efficacy. However, the civic empowerment engagement gap can be closed by providing underserved students with interactive and authentic civic experiences (CIRCLE, 2013; Levinson, 2012; Rubin & Hayes, 2010).

We want to examine the create such an authentic civic experience the “Fresno State Transportation Challenge” and examine what the impact is on the various participants (i.e. K-12 students, K-12 teachers, university students and community members). 

Motivation

The topic of transportation lends itself very well for project-based service learning and action civics. We want to leverage the expertise and resources of the Fresno State Transportation Institute to bring high quality educational experience to underserved students and help them improve their communities.

 

Final Report: Please click here.  

This project proposed centers on developing a suite of standards-aligned, rigorous lesson plans for secondary school teachers centered on transportation issues. Each grade level will receive 3-4 lesson plans to cover a complete 2-week unit of study. Each grade level will address a specific major topic within the field of transportation. Examples of such topics will include the societal impact of autonomous vehicles, transportation safety, and traffic flow. The designers of this project believe that education on transportation issues from an early age can elevate awareness of these issues and boost interest in transportation careers. Each lesson plan will span at least one full classroom period; some will span multiple periods. Each lesson plan will be guided by a culminating activity and will include (a) the background knowledge that expected of students, (b) strategies for scaffolding students who do not possess this background knowledge, (c) the facts, skills, concepts, and metacognition address in the lesson plan, and (d) teaching methods likely to prove effective for delivering the lesson plan in the classroom.

Final Report: Please click here

PI's Background: Dr. Samer Sarofim

Project's Stardate: April 1st, 2019

Project's End date: December 31st, 2019 

Executive Summary:

The motivation for this research proposal stemmed from multiple recent meetings (during February 2019) with a variety of transportation stakeholders including Fresno Council of Government, The California Department of Transportation (Caltrans) District 6, and City of Fresno – Public Works Department. Discussions about the role of effective messaging in changing consumer attitudes and behaviors to increase traffic safety indicated the lack of cohesive messaging strategy. Current messages, and their framing, seem to be conducted on an ad-hoc basis, lacking effectiveness, and forgoing the benefit of building on the vast academic research on message strategy and framing. This research is aimed at identifying the most effective messaging strategy and framing that shall induce attitudinal and behavioral changes rated to traffic safety.

Fresno, due to its high rate of pedestrian and bicyclist fatalities, is selected as a Focus City. The Federal Highway Administration included Fresno to the list of cities with the highest bicycle and pedestrian fatalities, since 2015. The Focus Cities Program in California, a joint program between UC Berkeley Safe TREC and California Walks is aimed at supporting community efforts geared towards the development of safe walking and biking communities and programs.

Message framing has been increasingly attracting both scholars’ and practitioners’ attention as it influences various behaviors (Gerend & Cullen, 2008; Rothman, Bartels, Wlaschin, & Salovey, 2006). For instance, message framing has been found to affect consumer’s decision making when buying, using, or recommending health care products (Chang 2007) and that positive and negative framing massages are more effective for prevention and detection products, respectively (Chang 2007). In a related vein, Wu et al. (2012) illustrated the differential effect of message framing on the effectiveness of dietary supplement advertisement.

This research investigates the effectiveness of different massaging strategies and frames that are aimed at inducing safer behaviors among pedestrians, cyclists, and motorists. The framework will be investigated empirically and includes time horizon (expansive vs. limited), regulatory focus (prevention vs. promotion), and locus of control (internal vs. external) framing. This research theoretically and experimentally studies the differential effects of time horizon, regulatory focus, and locus of control message framing on advancing traffic safety, an endeavor that shall benefit the public, transportation authorities, city administrators, and policymakers.

This research is aligned with SB1, Objective 4 as it will provide evidence-based and theory- driven strategies that contribute to creating safer communities and greater opportunities for use of active transportation modes (i.e., biking and walking) through inducing positive behavioral changes to enhance traffic safety via effective messaging. Also, the proposed research is aligned with SB1, Objective 7 as it will inform and improve decision-making on transportation-related issues, namely traffic safety. Decision makers will be able to use the results of the proposed research to effectively allocate the communication effort and spending to induce attitudinal and behavioral change that shall impact the safety of active transportation modes.

Final Report: Please click here.  

PI's Background: Dr. Mazen Eldeeb 

Project's Stardate: 3/ 1/19 

Project's End date: 12/31/19  

Executive Summary:

Project Objectives

 •    The development of chemical kinetic models to be used for the investigation of combustion and emission characteristics of the most promising second-generation bio-derived transportation fuels, such as 2,5-dimethylfuran (2,5-DMF), 2-methylfuran (2-MF), and 2-methyltetrahydrofuran (2-MTHF) compared with those of conventional fuel surrogates such as iso-octane and n-decane at different equivalence ratio conditions.

•    The  development  and  utilization  of  simple,  easy-to-use,  and  time-efficient  model  reduction approaches that are capable of producing reduced models of second-generation biofuels, such as furans, with reasonable predictive accuracy relative to their detailed versions.

 Project Background and Motivation

 Second-generation biofuels, such as furans, are an environmentally friendly alternative to fossil fuels which can substitute them without major engine modifications. Moreover, they have significantly lower greenhouse gas emissions than fossil fuels, because of CO2 recycling through agricultural activities [1]. In addition, they have superior energy densities, engine knock resistance, and Research Octane Numbers (RON) to first-generation biofuels, such as bio-alcohols [2], making them promising as spark ignition (SI) engine fuels. Also, second-generation biofuels have a great potential for production from sugars and biomass [3-6], unlike alcohols that are mostly manufactured from edible sources such as corn. These properties promote second-generation biofuels as alternative fuels, especially in the transportation sector, which accounts for 21% of the global energy consumption [7]. Therefore, the fundamental combustion properties of biofuels need to be explored with the purpose of developing and validating detailed and reduced chemical kinetic models. 

 The development of detailed and reduced chemical kinetic models has become a main area of combustion research; necessitated by the fact that these models more accurately describe the chemical kinetics of the combustion processes than global reaction models [1]. Developing chemical kinetic models has attracted increased research activity in measuring key combustion properties, such as ignition delay times and laminar burning velocity, mechanistic exploration of new reaction pathways, and evaluation of the propensity of biofuels to emit pollutants such as CO, NOx, SOx, soot, and particulate matter. Modeling efforts are further prompted by the need for combustion models of emerging fuels such as biofuels [1]. 

 Fuel-flexible combustion technology is advanced through validated kinetic models, which can be used for computer-aided development of novel combustion engines, ultimately aimed at the development of clean and efficient transportation systems. Numerical modeling is one of the most powerful tools used for that purpose, as it provides flexibility and low cost, compared to experimental characterization. The synergy between chemical kinetics mechanisms and three-dimensional computational fluid dynamics (3D-CFD) flow simulations is necessary for the simulation of combustion and emissions behavior of second-generation biofuels as well as their blends with conventional  fuels  in  existing  compression  ignition  (CI),  spark  ignition  (SI),  dual-fuel  and homogeneous charge compression ignition (HCCI) engines.

 However, the use of chemical kinetic models for combustion and emission simulations requires efforts to reduce the computational cost, as the use of the resulting chemical kinetic models in computational combustion analysis is limited by their large sizes. Chemical kinetic models often contain tens of thousands of reactions among hundreds or thousands of species. Coupling these to the turbulent flows characteristic of combustion is therefore challenging. One approach to decrease the  computational  cost  of  detailed  models  is  to  reduce  them  to  smaller  sizes  while  retaining prediction  capabilities  of  practical  interest  [8-11].  The  motivation  behind  sustained  search  for

methods of mechanism reduction is to enable researchers in the combustion field to conveniently obtain reduced models efficiently without necessarily acquiring skills in chemical kinetic modeling. While most existing methods do not require detailed chemical kinetic insight, the methods tend to require substantial programming, judging from the few research groups using the proposed methods.

Therefore, the planned research is aimed at developing reduced chemical kinetic models to be used for the investigation of combustion and emission characteristics of the most promising furans in CI, SI, dual-fuel and HCCI engines at different equivalence ratio conditions. To that end, the research is also aimed at providing simple, easy-to-use, and time-efficient model reduction approaches that are capable of producing reduced models of second-generation biofuels with reasonable predictive accuracy relative to their detailed versions.

 The proper chemical kinetic modeling of the combustion and emission behavior of second- generation biofuels would identify potentially favorable characteristics of such fuels relative to conventional fossil fuels used in the transportation sector, both qualitatively and quantitatively. This in turn would be a helpful effort towards reducing the impact of the transportation sector on the environment and climate change, which is one of the main objectives of California’s cap-and-trade program (SB-1 Objective 5). The findings of such modeling effort would provide invaluable information that can support and improve the decision-making process of transportation-related issues. For instance, the results of this project can provide valuable information to the governmental agencies in California, such as the California Air Resourses Board, with regards to the estimated emission levels of furans combustion. Additionally, the results of this project can promote the mass- production of furans from biomass, which can be helpful to the farming businesses in the Central Valley and beyond, as agricultural waste is a main feedstock for cellulose, necessary for the production of furans. Finally, the results of the proposed project are necessary for submission of future research grant proposals to American Chemical Society’s Petroleum Research Fund (ACS- PRF), United States Department of Agriculture (USDA) Agriculture and Food Research Initiative (AFRI) Sustainable Bioenergy and Bioproducts (SBEBP) Challenge Area, USDA Biomass Research and Development Initiative (BRDI), USDA HSI Educational Grants Program (HSI), and National Science Foundation (NSF) Energy for Sustainability funding programs. 

Final Report: Please click here

PI's Background: Dr Hovannes Kulhandjian

Project's Stardate: 03 June, 2019

Project's End date: 27 December, 2019

Executive Summary:

In this work, we plan to develop a visible light communication framework that can be used for intelligent transportation system. Intelligent Transportation Systems (ITS) has been motivated by the need for reducing traffic congestion and offering better user experience in navigation and location-specific services. Recently, visible light communication (VLC) has drawn a lot of attention. ITS is one of its most important applications. Traffic lights have been used to control traffic flow and located at a particular place and rarely moved are competent to indicate and to supply the information about the surrounding.

In this project, our aim is to develop a framework that can support vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) and vehicle-to-cyclist (V2C) communication using VLC.

 Specifically, traffic lights will be used to not only to orderly provide traffic flow, but also to share some important information to the cars. The traffic light can provide information about the traffic conditions several blocks down the road and in case of accidents this information would be useful for the passenger to detour their original driving route to help reduce congestion and save time.

The infrastructure of the ITS is composed of a central station that controls the traffic flow and when new information is provided to the traffic lights they are routed to the central station to do analysis and smarter traffic control.

Our focus will be on the development of VLC protocols to establish communications back and forth with the traffic light and vehicle for better traffic management. In addition to that our framework will provide smoother traffic flow by collecting data at the traffic light on the number of cars heading towards the next few blocks of traffic lights and controlling those traffic lights such that the flow of traffic is more efficiently controlled by allowing those cars to pass through several green lights before meeting the next red light.

In this work, two undergraduate and one graduate students will be involved. After developing the VLC framework for intelligent transportation systems and obtaining some promising results we plan to write a paper and submit this work to a conference. This project will then be expanded and we will seek for funding from NSF or from US Department of Transportation. 

Final Report: Please click here

PI's Background: Dr. Hongwei Dong 

Project's Stardate: May, 01, 2019

Project's End date: December 31, 2019 

Executive Summary:

Research on the relationship between urbanicity and physical activity yielded mixed results despite many studies consistently showed that residents tended to undertake more transportation-related physical activity in a more urban environment. The purpose of this study is to examine the geographic disparities in transportation-related physical activity at finer geographic scales in the entire nation, with and without controlling for the built and social environment at the neighbor-hood level.

This study takes advantage of a few new questions that were added to the 2017 National Household Travel Survey (NHTS) regarding people’s physical activity and their walk and bike trips that were strictly for exercise. Unlike previous studies that adopted a dichotomous urban-rural variable, this analysis categorizes residents into eight geographic locations: four in large metropolitan areas (downtown, inner-ring suburb, mid-ring suburb, and outer-ring suburb), two in small metropolitan areas (urban and rural), and two in the non-metropolitan area (urban and rural). We conducted both descriptive and modeling analyses to evaluate the intra- and inter-metropolitan patterns of physical activity and active travel in the United States. We differentiated walk and bike trips that were strictly for exercise from walk and bike trips for other purposes.

This study shows that the relationship between urban city and physical activity demonstrates a flat U-shape. Residents were more physically active when they lived in the areas from the two ends of the urbanization spectrum: inner cities and inner-suburbs of large metropolitan areas and the rural parts of non-metropolitan areas. Suburbanites, particularly mid-ring and outer-ring suburbanites walked the least. The geographic pattern holds regardless of the inclusion of neighborhood characteristics in the models. There is a very slight geographic variation of the weekly rates of walk and bike trips that are strictly for exercise. There is a lot more variation of the weekly rates of walk and bike trips that are for non-exercise purposes.

Walkers and cyclists in the eight different geographic locations reported different infrastructure and safety barriers that kept them from the walk and biking more. For cyclists in the central cities of large metropolitan areas and cyclists in non-metropolitan areas, a lack of nearby paths or trail was the prominent infrastructure barrier to biking more. For suburbanites, a lack of nearby parks seemed to be a more prominent barrier to biking more. No matter which geographic location they lived in, walkers consistently reported no sidewalks or sidewalks in poor conditions as the most prominent barriers to walking more. The sidewalk issue was more serious for walkers in suburbs and the urban parts of small metropolitan areas than walkers in other locations. Not enough lighting at night was consistently reported as the most prominent safety barrier to walking more in different geographic locations.

The findings from this study contribute to evidence-based planning of active transportation and public health interventions. Suburban areas in large metropolitan areas seem to be the least physically active places and have the largest potential for improvement. Even incremental improvements in suburbs will generate huge public health benefits given that more than half of Americans live in suburbs. Specifically, addition or improvement of the quality of sidewalks in suburban neighborhoods seems to be a promising strategy given that suburban walkers reported no sidewalks or sidewalks in poor conditions as the most prominent barriers that keep them from walking more. Improving street lighting seems to be a promising strategy to encourage more walking in urban, suburban, and rural areas. Traffic calming and good lighting at night are two potentially effective tools to encourage more biking in urban and rural areas respectively. Rural residents take more walks outside than mid-ring and outer-ring suburbanites. Most extant studies of active travel focused on urban and suburban residents. There is a need for more research to understand how rural residents travel in non-motorized modes and how they manage to take more walk trips than mid-ring and outer-ring suburbanites.

Final Report: Please click here

Executive Summary:

With the proliferation of support for autonomous and connected vehicles in private and public sectors, many Cyber-Physical Systems (CPS) of different types, sizes, and sensitivity levels exist. The framework developed herein would be applicable to new and existing CPS, resulting in a more secure physical and virtual network of autonomous and connected vehicles. Autonomous and connected vehicles are increasingly gaining momentum across different disciplines, but the lack of standards and models for their design and implementation are major barriers ahead of such research and development, particularly from a security perspective. The project’s proposed framework would act as a baseline to facilitate security testing and assessment of a given vehicular network which paves the way for the development of advanced security analytics tools, leading to new knowledge discoveries in this area. The security of such networks is a fertile field and establishing a framework to make such networks secure would certainly trigger many interdisciplinary scholarly activities. The proposed research is an original and systematic investigation of security and is potentially transformative in nature as it challenges conventional wisdom in the field.

Smart objects and smart embedded sensors are currently secured based on the same best practices as traditional networks without considering the limitations imposed by the proliferation of smart nodes in terms of processing power and memory. This is mainly due to limited research in this field. Encapsulation of protocol stack layers is done on a single hardware processor, leaving the lower layers unprotected. With so many new forms of data, new forms of threats would come into existence. The main reasons for CPS security breaches are: i) Conventional network security wisdom is not applicable to the IoT realm. IoT is an ecosystem driven by business gaps, rather than just a myriad of devices; ii) IoT vendors compromise security to gain functionality and openness for a broader target market. IoT manufacturers follow Agile manifesto for their development process which opens many security gaps; iii) There are inherent vulnerabilities in individual IoT nodes: a) For many types of IoT devices, physical access cannot be restricted, and thus devices that expose critical information on internal nodes can be compromised; b) Although chip manufacturing innovations have led to the emergence of embedded chips with hardware-based security (e.g. ARM TrustZone) and hardware with cryptography support (e.g. ARMv8), the inclusion of such chips in every device is cost prohibitive. Thus, it makes sense to look for network security solutions that do not require modification of existing and emerging IoT devices; and c) IoT nodes generally don’t support advanced networking capabilities and security protocols.

 Final Report: Please click here.

PI's Background: Mr. Malshana Wadugurunnehalage

Advisor's Background: Dr. Ajith Weerasinghe

Project's Stardate: March 4th, 2019

Project's End date: December 31st, 2019 

Executive Summary: 

This project has three main objectives. The first objective is standardizing battery. There are various types of batteries used in the Automotive Industry. When this comes to Electric Vehicles (EV), battery manufacturers are hiding different recipes that they use for manufacturing batteries. This creates numerous limitations, especially in recycling processes and growth of EV demand. In this project, the importance of standardizing on EV battery technologies are discussed. The second objective is exploring battery switching stations. Battery Switching is identified as a promising technique for secure charging and a better way of maintaining the entire EV battery system in a region. In this project, it's identified the importance of having switching stations instead of fast charging. Fast charging leads to battery degradation and its effects on the grid if the power supply is not properly maintained. Considering tremendous benefits, implementing switching stations are widely encouraged throughout this project. The third objective is exploring IoT(Internet of Things) for efficient green energy transportation. Currently, the Internet plays a vital role in the business world. Through the IoT concept, it creates the connection between Electric Vehicles, Switching Stations, and other private and government organizations which interested to access the relevant data. In this way, it’s expected to energize the total battery switching system, bringing more productive and effective by establishing a robust IoT system. In addition to that, ultimately it's expected to make possible pathways to enhance performances of Electric Vehicles in public transportation.

This project aims to demonstrate the possible pathways to implement battery switching approaches for Battery Electric Vehicles (BEV) through the Electric Vehicle (EV) battery standardizing. During the past decade, there was significant interest in EVs and their technologies. Due to the number of studies and experiments which carried out for enhancing total performances of EVs, demand a different type of EVs are grown faster. The growth of different battery technologies has led to improving the primary aspects of Electric Vehicles. As a result of relentless research and developments regarding different battery technologies, the distance travel per single charge was growing day by day. Battery design and manufacturing techniques becoming complex, and battery manufacturers tend to hide their battery chemistry intend to increase the performance of their product stay strong in the competition.

EV batteries carry a different kind of chemical which can be harmful to the environment. Properly managed recycling approaches are essential to establish and maintain robust operation due to the increasing usage of EV batteries. Hiding their recipes of battery manufacturing, create complexity on the recycling process and through the enforcement of established rules and regulations for EV battery standardizing, battery manufacturers will be more open with their manufacturing techniques. Through this project, environmental impact due to increasing usage of EV batteries and possible pathways to create new businesses through recycling will be discussed. EV battery standardizing becoming an important concept, and scientists and engineers are found possible pathways to implement other approaches to establish a different type of business model through the EV battery standardizing. Battery switching stations are one of the promising business models, been introduced and, through this project, the values of such a business model will be discussed. 

Throughout the project, battery switching stations are identified as the most important aspect of harvesting benefits from all around. To make this battery switching process more effective and efficient, Introducing of the Internet of Things (IoT) is one of the major aspects of this project. The suggested network is something that goes beyond the traditional data acquisition and performance monitoring system. Through this system, the vehicle driver, the staff of battery switching station and data center for performance monitoring and system development, will be aware of each and every switched battery. This system will be demonstrated throughout the project and advances will be highlighted. In this way, there are numerous benefits that will be demonstrated and discussed throughout the project. Though it will be a time-constrained project, in the beginning, the further developments will be discussed at the end of the project. Depending on the availability of time and funds, this project will be continued for developing further, meeting its’ all aspects.

 Final Report: Will be available soon. 

  

Year 3 (2020)

 PI's Background: Dr. Chih-Hao Wang

Project's Stardate: March 1st 2020

Project's End dateDec 31st 2020

Executive Summary:

Objectives:

  • Explore the explicit local relationships between cycling activities (utilitarian and/or recreational) and the accessibility to multi-use paths through cycling computed from the previous CSUCT SB1 project for Fresno in California, using a geographically weighted (GWR) regression model;
  • Provide planning information for active transportation strategies for Fresno, California;
  • Present the analysis results in a planning conference, such as the Association of Collegiate Schools of Planning (ACSP) annual meeting.

 Motivation:

This research proposal is an extension of the two previous SB1 projects that (1) one calculated the accessibility to multi-use paths through cycling using the network analysis in the ArcGIS, and (2) the other found an optimal allocation of transportation investments that would maximize the total accessibility to multi-use paths through cycling while minimizing the gap between high- and low-accessibility neighborhoods. Along this line, it is interesting to explore whether the accessibility to multi-use paths would affect residents’ cycling activities, especially for those from socioeconomic disadvantaged neighborhoods. Therefore, this proposed project is designed to serve this purpose using a GWR model to examine the local relationships between the intensity/frequency of cycling activities and the effects of accessibility to multi-use paths through cycling while controlling for other built environment and social demographical factors. The results will point out where the accessibility does not work and therefore some other policy interventions might be needed to promote cycling activities. In other words, this study aims at revealing whether the residents who do not cycle is because of the lack of accessibility or their cycling perception or behavior. The findings will provide a new insight into the planning problem of promoting active transportation for Fresno, California.

 Final Report: Will be available in 2021.

PI's Background: Dr. Christian Wandeler 

Project's Stardate: Feb 1st 2020

Project's End dateDec 31st 2020

Executive Summary:

The goal of the Fresno State Transportation Challenge is to create an authentic civic service-learning experience, in which K-12 students and teachers; university students and professors; and community members work together on projects addressing transportation concerns and related issues in the region. During 2019 we piloted the Transportation Challenge process with 9 teachers. In 2020 the goal is to expand, refine, and create structures to sustain the implementation of the Transportation Challenge across subsequent years.

The objectives to meet this goal are as follows: 1) Conduct research on the implementation and expansion of the Transportation Challenge program to identify content and procedural supports and challenges; 2) Develop a pipeline for recruitment and continuous participation of K-8 teachers across the Central Valley; 3) Convene participating teachers and FSTI members to analyze instructional procedures and materials to develop a Transportation Challenge curriculum; and 4) Develop structures for increasing the connections between local educators and FSTI members and resources.

 Final Report: Will be available in 2021.

PI's Background: Dr. Jaymin Kwon

Project's Stardate: March 1st 2020

Project's End dateDec 31st 2020

Executive Summary:

Objectives: To promote active transportation modes (such as bike ride and walking), and to create safer communities for easier access to transit, it is essential to provide to the public that the consolidated data-driven transportation information to the stakeholders and the public. The relevant and timely information from data facilitates the opportunity for improving decision-making processes for the establishment of public policy and urban planning for sustainable growth and promoting public health in the region. The goal of our project aligns with the SB-1 objectives 4 and 7.

Transportation Emitted Air Pollutant Data: The vehicle transportation-related air pollution was measured at 150 neighborhood walking routes within 22 zip codes including 58 census tracts in Fresno/Clovis area for over four years from the previous NIEHS/USEPA funded research, Children’s Health to Air Pollution Study – San Joaquin Valley (CHAPS-SJV) with PIs of UC Berkeley, Stanford University and Fresno State. To characterize the spatial variation of transportation-emitted air pollution in the Fresno/Clovis neighborhood, various species of particulate matters emitted from traffic sources were measured using real-time monitors and GPS loggers. The pollutants include particulate matters (PM10, PM2.5, PM1), black carbon (BC), ultrafine particles, and polycyclic aromatic hydrocarbons (PAHs).

Spatial Analyses of Geocoded Data: Vehicle transportation, especially diesel trucks, is known as a major emission source of fine particulate matters (PM2.5). Black carbon and polycyclic aromatic hydrocarbons (PAHs) are the toxic components of the fine particulate matter and the trace of the diesel emission. The real-time concentrations of particulate species varying in different transportation sources will provide a remarkable insight to analyze the dynamic temporal impact on transportation-related pollution patterns. For aligning various pollutant concentrations synchronously over the accurately geocoded neighborhood locations from the walking routes, quality assurance and quality control (QA/QC) from the pollution and positional data are necessary. 

Final Report: Will be available in 2021.

PI's Background: Dr. Samer Sarofim

Project's Stardate: March 1st, 2020

Project's End date: December 31st, 2020 

Executive Summary:

The motivation for this research proposal stemmed from multiple interactions (during 2019) with a variety of transportation stakeholders including Fresno Council of Government, The California Department of Transportation (Caltrans) District 6, and City of Fresno – Public Works Department. Discussions about the role of effective messaging in changing consumer attitudes and behaviors to increase traffic safety indicated the lack of cohesive communication strategy and targeted mobile media platforms. Current media vehicles used to target vulnerable road users (pedestrians, cyclists, and motorists) seem to be lacking effectiveness, and forgoing the benefit of building on the vast academic research on media platforms design and content effects on altering motivations and behaviors. This research is aimed at identifying the most effective mobile application design and content that shall induce attitudinal and behavioral changes rated to traffic safety among vulnerable road users. Also, the mobile application will aim at enhancing the use active transportation modes. Fresno, due to its high rate of pedestrian and bicyclist fatalities, is selected as a Focus City. The Federal Highway Administration included Fresno to the list of cities with the highest bicycle and pedestrian fatalities, since 2015. The Focus Cities Program in California, a joint program between UC Berkeley Safe TREC and California Walks is aimed at supporting community efforts geared towards the development of safe walking and biking communities and programs.

Final Report: Please click here.  

PI's Background: Dr. John Green

Project's Stardate: May 1st, 2020

Project's End date: December 31st, 2020

Executive Summary:

 Objective: The objective of this research is to determine if the railroad operations management strategy of Precision Scheduled Railroading (PSR), which has had a significantly positive impact on the profitability of major freight railroads has had either a positive or negative, or negligible effect on intercity passenger and high speed rail operations.   

 Background: Hunter Harrison was a railroad visionary, that as Chief Executive Officer for three different Class One (major) North American freight railroads revolutionized their entire basic strategy for business.  The results of this business strategy have been praised for the railroads using it from stock markets and investors, but railroaders as a group have had a less enthusiastic response.  I wish to investigate what effects PSR has had on passenger operations, especially since high speed passenger operations often operate on tracks that they share with freight railroads. 

 Motivation:  I am interested in high speed rail passenger operations, and I recently was talking with an Amtrak employee about the troubles Amtrak has with its Acela trains and trying to operate in shared corridors wit freight trains.   Then I saw AREMA’s list of hot topics for the 2020 Annual Conference, and it included Precision Scheduled Railroading as one of the topics, and I wondered if it could bring improvements to the routes where Amtrak shared tracks with freight railroads. 

 

Final Report: Will be available in 2021.

PI's Background: Dr Hovannes Kulhandjian

Project's Stardate: 03 June, 20120

Project's End date: December 31st, 2020

Executive Summary:

Objective: The objective of this research is to determine if the railroad operations management strategy of Precision Scheduled Railroading (PSR), which has had a significantly positive impact on the profitability of major freight railroads has had either a positive or negative, or negligible effect on intercity passenger and high speed rail operations.   

Background: Hunter Harrison was a railroad visionary, that as Chief Executive Officer for three different Class One (major) North American freight railroads revolutionized their entire basic strategy for business.  The results of this business strategy have been praised for the railroads using it from stock markets and investors, but railroaders as a group have had a less enthusiastic response.  I wish to investigate what effects PSR has had on passenger operations, especially since high speed passenger operations often operate on tracks that they share with freight railroads. 

Motivation:  I am interested in high speed rail passenger operations, and I recently was talking with an Amtrak employee about the troubles Amtrak has with its Acela trains and trying to operate in shared corridors wit freight trains.   Then I saw AREMA’s list of hot topics for the 2020 Annual Conference, and it included Precision Scheduled Railroading as one of the topics, and I wondered if it could bring improvements to the routes where Amtrak shared tracks with freight railroads. 

Final Report: Will be available in 2021.

PI's Background: Dr. Hongwei Dong 

Project's Stardate: April 1st, 2020

Project's End date:December 31st, 2020

Executive Summary:

Project objective
The objective of this project is to evaluate whether Californian residents save money on transportation costs by living in neighborhoods that are served by high-quality rail transit.
This study is aligned with SB-1 Objective 4: “Create safer communities, increased access to transit, and greater opportunities for use of active transportation modes (i.e., biking and walking) through complete streets and innovative land use planning so that people of all abilities and socioeconomic levels enjoy the same opportunities for learning, living, labor, and leisure.”

Motivation
The motivation of this study is to contribute to the recent debate on the affordability impact of TODs. In 2012, the U.S. Department of Housing and Urban Development released the Housing and Transportation Index (H+T index). The H+T index provides an estimate of affordability that includes both the cost of housing and the cost of transportation at the neighborhood level. In general, the H+T index suggests that though residents may have to pay higher rent or home prices to live in TODs, they save money on transportation costs because TODs provide better transit services and reduce car use (both ownership and travel). Recent research at the individual level, however, found little evidence that living in TODs reduces transportation expenditures. The purpose of this study is to quantify and compare transportation-cost savings for residents in TODs in eight Californian metropolitan areas. To address the potential self-selection bias, I estimate propensity score to match residents in TODs (the treatment group) with similar residents outside of TODs (the control group). The findings from this study will inform transportation planning and practice that aim to promote equitable TODs.

Final Report: Will be available in 2021.

PI's Background: Dr. Shahab Tayeb

Project's Stardate: March 1st, 2020

Project's End date: December 31st, 2020

Executive Summary:

Project Objective: The main objective of this proposal are threefold: (1) to study the impact of data poisoning in sensed vehicular data and neural network training architectures; (2) to design a reconfigurable accelerator based on an adaptive framework for secure design, implementation, and evaluation of the Internet of Vehicles (IoV); and (3) to drive the reconfigurability of (2) using findings of (1). This project aims to make revolutionary progress to close the gap between the existing security mechanisms (e.g. multi-factor authentication), current decentralized vehicular security solutions (e.g. defense in depth), and the security needs of the IoV data. The project’s closely intertwined research activities include: (1) designing a modular framework for secure implementation of emerging autonomous and connected vehicles, covering deterrent, preventive, detective, corrective, and recovery controls; (2) developing and tuning Deep Learning architectures to classify malicious behaviors and target agents using sensed data as the input; and (3) designing the accelerator hardware to translate the security findings into actionable criteria. The Research Questions are: a) What are the security vulnerabilities and challenges presented by the poisoning the sensed data during the training process? b) Can neural networks be as successful in security of connected vehicles as they have been in computer vision and speech recognition? c) How different are the security gaps for connected vehicles from those of traditional networks? and d) Can security by design in hardware outperform the existing security patches and protocols?

Motivation: With the proliferation of support for autonomous and connected vehicles in private and public sectors, many IoV of different types, sizes, and sensitivity levels exist. Autonomous and connected vehicles are increasingly gaining momentum across different disciplines but lack of standards and models for their secure design and implementation are major barriers ahead of such research and development. The project’s proposed framework will act as a baseline to facilitate security testing and assessment of a given vehicular network which paves the path for development of advanced security analytics tools, leading to new knowledge discoveries in this area. The security of such networks is a fertile field and establishing a framework to make such networks secure will certainly trigger many interdisciplinary scholarly activities.

 Final Report: Will be available in 2021.

PI's Background: Dr. Aly Tawfik

Project's Start date: December, 2020

Project's End date: June, 2022

Executive Summary and Objective: In May 2020, a research team led by Fresno State Transportation Institute partnered with Fresno County Rural Transit Agency and Clovis Transit in Fresno County to perform a time and budget constrained pilot study on the possible risks of infection by the novel coronavirus that causes COVID-19 disease as well as the methods to mitigate those risks on transit buses. The research team included members from California State University, Fresno; the University of California, Merced; Fresno Metro Ministry, a community advocacy organization in Fresno; and a private heating, ventilation, and air conditioning (HVAC) engineering firm, Air2O Cooling. 
The research team had two objectives: 
1) To understand and model air circulation in the passenger and driver spaces of public transit buses under different operation conditions, with a focus on how that circulation impacts potential viral spread, and 
2) To evaluate the effectiveness of different technologies in mitigating the risks of infection of passengers and drivers from viruses released into the interior spaces of the bus via virus aerial circulation or settling on surfaces. 
For the first objective, the team studied the airflow within the respective agency buses using actual airflow measurements from the bus HVAC systems. Moreover, non-toxic colored smoke and steam were released inside the buses to visually observe and record the airflow movement. Testing was done with colored smoke and steam under various operational conditions such as vehicles in motion at highway speeds or sitting still, windows open and closed, vehicle door(s) open and shut, HVAC system on and off, HVAC fresh air on and off, emergency hatch open and shut, and with the source of spread at different locations on the vehicle. The times it took to fill the buses with smoke and then clear the space were recorded. Additionally, computational fluid dynamic models (CFD) were developed for the different vehicles investigated. 
The results of the airflow study show that the existing HVAC systems in transit buses are very effective in moving air-conditioned air quickly within the passenger and driver areas, and in maintaining that air in vehicles for long periods of time, as they are designed to do. However, this fast and effective movement of air creates a high level of risk of infection from an airborne viral agent released inside a transit bus such as the novel coronavirus. Particularly concerning was the much slower speed of air clearance from the vehicle cabin. The study points to the need for viral mitigation technologies to be retrofitted into the existing bus HVAC systems and potentially new systems to be developed and incorporated into buses in the future. 
For the second objective, the team investigated the efficiency of different methods and technologies in mitigating the virus from the air and surfaces. The team utilized three live bacteriophage viruses with different resemblance characteristics to the novel coronavirus: Phi6, MS2 and T7. The team examined the efficiency of the tested technologies both in the lab as well as on buses in the field. The tested technologies included: cooling, heating, carbon filter, HEPA filters, UVC lights, photocatalytic oxidation, ionization, positive pressure, and antiviral materials and fabrics. 
Findings of the virus mitigation study demonstrated comforting levels of consistency between the results of both the lab and field experiments. Photocatalytic oxidation inserts and UVC lights were found to be the most effective in mitigating the different virus types from the air. On the other hand, the creation of a positive pressure environment (0.5-inch water column) mitigated all viruses on surfaces. Also, copper foil tape and fabrics with a high percentage of copper mitigated the Phi6 virus; however, the results were inconclusive with the other two viruses. 
Following the completion of this project, the team received concerns about the possible release of toxic by-products into the vehicle cabins when using the photocatalytic oxidation inserts and UVC lights technologies. Accordingly, the team conducted limited exploratory experiments to measure the levels of formaldehydes, ozone, and volatile organic compounds inside the cabins of the vehicles with these technologies absent and installed within the bus HVAC system. The team conducted a few experiments while the buses were static and in motion. The experiments did not detect any increase in the levels of formaldehyde, ozone, or volatile organic compounds inside the bus cabin. 
It is worth noting that retrofitting these technologies into the bus HVAC systems would mitigate air-borne viruses distributed by the HVAC system. These technologies would not, however, mitigate the airborne viruses while traveling from the viral source to the intake of the HVAC system. Accordingly, these technologies do not eliminate the value of using personal protective equipment (e.g. facial masks) by both passengers and drivers. 
Proper implementation of these findings in transit buses (and potentially other similarly confined spaces with HVAC systems) could be significantly valuable and directly lead to improved protection of passengers and drivers on public transportation modes—possibly against all forms of air-borne viruses.

Motivation: In mid-May 2020, when this study was first begun, infection rates from the novel coronavirus that causes COVID-19 disease continued to climb in the United States and around the world, leading many health and government officials to conclude that there would be no “return to normal” unless an effective vaccine was developed and administered broadly across the global population. While the early focus on virus transmission centered on contaminated surfaces and making sure hands were washed properly, research emerged showing increasing evidence that the virus was airborne and could be transmitted through aerosol particles that linger in stagnant air. 
At that time, with an effective vaccine months away from being approved for use—and much time needed for it to be produced in a volume large enough to vaccinate billions of people—wearing a protective mask became the standard piece of apparel for everyone in nearly every aspect of life involving human interaction, especially in confined spaces. Analysis of the efficiency of the SARSCoV-2 coronavirus in infecting humans led researchers around the world to the conclusion that the virus would not be going away any time soon, making research into how to protect people from infection as they go about their daily lives a question of critical importance. 
As evidence of airborne transmission risk increased, shared transportation and transit vehicles gained more attention as potential places for infection due to the confined spaces of passenger seating, a relatively enclosed environment, and heating and air conditioning systems that recirculate the interior air. Without definitive evidence that public transit and shared mobility services could be made safe for riders and drivers from COVID-19 infection, the public would of course be reluctant to return to using these services. Moreover, the services themselves were at risk due to the expected loss of revenue from ridership. 
Accordingly, this study aimed to assess the risk of COVID-19 infection for drivers and passengers in transit buses and to identify effective and cost-efficient solutions to mitigate such risk. 

Final Report

PI's Background: Dr. Christian Wandeler

Project's date: December, 2020

Abstract: The Fresno State Transportation Challenge uses an action civics approach to support K-12 students in developing transportation-related projects that have a positive impact on the community. In 2020 the goal was to expand, refine, and create structures to sustain the implementation of the Transportation Challenge across subsequent years. As a result of the COVID pandemic, the process and goals of the project were adapted. The project was extended into April 2021 and was entirely conducted through remote participation. The focus was on two high schools. The expansion into the high school age bracket was successful and the experience with these two projects will allow for easier expansion in additional high schools in the future. One high school focused on the topic of active mobility, specifically biking, and addressed the challenge of how to get more students to bike to school. The other high school combined the transportation challenge with an economic vitalization project. The students were asked to also develop a modern transportation concept. Both projects exposed high school students to the topic of transportation and expanded awareness of transportation careers. Students also developed important competencies in the domains of problem solving, collaboration, communication, and leadership.

PI's Background: Dr. Samer Sarofim

Project's published date: June, 2020

Executive Summary and Motivation: The motivation for this research stemmed from multiple recent meetings with a variety of transportation stakeholders including Fresno Council of Government, California Department of Transportation (Caltrans) District 6, and City of Fresno Public Works Department. Discussions about the role of effective messaging in changing public attitudes and behaviors to increase traffic safety indicated the lack of a cohesive messaging strategy. Current messages, and their framing, seem to be conducted on an ad-hoc basis and forego the benefit of building on the vast academic research on message strategy and framing. This research is aimed at identifying effective messaging strategies and framing that shall induce attitudinal and behavioral changes rated to traffic safety. 
Fresno, due to its high rate of pedestrian and bicyclist fatalities, is selected as a focus city. The Federal Highway Administration has included Fresno in the list of cities with the highest bicycle and pedestrian fatalities since 2015. The Focus Cities Program in California, a joint program between UC Berkeley SafeTREC and California Walks, aims at supporting community efforts geared towards the development of safe walking and biking communities and programs. Message framing has increasingly attracted both scholars’ and practitioners’ attention, as it influences various behaviors. For instance, message framing has been found to affect consumers’ decision making when buying, using, or recommending health care products, and it has been found that positive and negative framing messages are more effective for prevention and detection products, respectively. Similarly, Wu et al. illustrated the differential effect of message framing on the effectiveness of dietary supplement advertisements.
This research investigates the effectiveness of different messaging strategies and frames that are aimed at inducing safer behaviors among pedestrians, cyclists, and motorists. The framework empirically investigates time horizon (expansive vs. limited) and regulatory focus (prevention vs. promotion) framing. The author experimentally studies the differential effects of time horizon and regulatory focus message framing on advancing traffic safety, an endeavor that shall benefit the public, transportation authorities, city administrators, and policy makers. 
Findings suggest that the utilization of expansive horizon time framing and promotion focused messaging could lead to higher perceptions of message credibility and greater intentions to act safely on the roads. Also, the individual difference of perceived personal control was significantly correlated with various safety behavioral intentions, suggesting that future research would benefit from message framing that heightens the sense of personal control. 
Decision makers will be able to use the results of this research to effectively allocate communication efforts and spending to induce attitudinal and behavioral change that shall enhance the safety of active transportation modes.

Final Report

PI's Background: Dr. Aly Tawfik

Project's Start date: December, 2020

Project's End date: July, 2022

Abstract: Electric vehicles (EVs) are a valuable tool in addressing the climate and energy challenges placed on our transportation systems. However, while national and international market shares of EVs have been rising with exponential rates, access to EVs of low-income populations has been significantly slower. This research developed a business model for expanding the EV market to low-income Californians. The team developed the model from qualitative data from various stakeholders, including Electric and Solar Companies, Professional and Community-Based Organizations, State Agencies, research institutions, and more, which enabled insights regarding various barriers that hinder the adoption of EVs. The team also used a state-wide survey to understand the barriers from the point of view of lower income Californians. The business model created from this data can be used by state administrators, policy makers, and social emprises to mitigate the barriers faced by low-income Californians within the EV market.

Final Report

PI's Background: Dr. Aly Tawfik

Project's date: December, 2022

Abstract: HSR is one of the largest projects in the nation currently under construction 24stations, 800 miles of rail from Sacramento to San Diego. HSR will impact travel accessibility between cities and areas across the state. Its objective is to Quantify and visualize the impact of HSR on travel time. Compare HSR to other travel modes (roads, bus, air and train) Provide more information to the public on whether investment is valuable. Completed with use of ArcGIS and advanced ArcGIS extensions including Network Analyst and Model Builder to produce: OD Matrices Isochrone Maps.

PI's Background: Dr. Aly Tawfik

Project's date: December, 2021

Abstract: Many believe that telecommuting could be a solution for some of the significant adverse impacts of our transportation systems, e.g., traffic congestion, greenhouse gas and air pollution emissions, and energy consumption. Observations may have further strengthened this belief during the first year of the COVID-19 Pandemic when streets were deserted and clean air and wildlife returned to urban areas. Accordingly, this study investigates the legitimacy of this belief. Telecommuting is the Substitution for work regularly performed at the workplace with work at home or a location close to home. It can be performed multiple days per week, for full or partial days. A telecommute framework was adapted to analyze the 2017 National Household Travel Survey dataset. To study the impact of telecommuting, in its various forms, on daily trip counts and daily miles traveled; for urban and rural workers. The derived relationships would indicate if increased telecommuting, expected after the COVID-19 Pandemic, would result in fewer or greater trip counts and miles traveled in urban and rural contexts.

 

Year 4 (2021)

PI's Background: Dr. Jaymin Kwon

Project's date: December, 2021

Abstract: Promoting alternative forms of transportation is a major focus area in Transportation Planning. Information on pedestrians' and cyclists' exposure to traffic-related air pollutants during commute and utilization of parks and recreational areas is very limited in our Fresno/Clovis area. This proposed research will provide valuable insights and findings that could be used to plan transportation facilities better and promote more active transportation. The purpose of our proposal is to continue and expand the StarTraq 2020 project that is currently funded by the Fresno State Transportation Institute (FSTI) to meet the identified needs of the Fresno/Clovis area, promoting alternative forms of transportation by examining air pollution data collected near roadways and on trails as related to the active transportation modes of walking and bicycling. Through this research, we attempt to broaden the scope of the roadside, on-road, and in-vehicle air quality data from particle pollutants.

Objective: This research attempts to broaden the scope of the roadside, on-road, and in-vehicle air quality data from particle pollutants. The results will provide the baseline exposure levels for public health concerns of different transportation modes. In addition, the information on pedestrians' and cyclists' exposure to traffic-related air pollutants during commute and utilization of parks and recreational areas will be precious to promote the active transportation mode while developing strategies for reducing the risks associated with the mode of transportation via urban planning and policy development.

PI's Background: Dr. Chihhao Wang

Project's date: December, 2021

Abstract: One motivation of widely studying accessibility is that the transportation network of a city influences individuals’ mobility and therefore affects their daily activities. Despite all these, it is rare to assess its resilience considering the increasingly and frequently emergent natural hazards. This study aims to fill out this gap by developing an analytical research framework to examine the resilience of accessibility to emergency and lifesaving facilities under the threats of natural hazards such as earthquakes and wildfires. The results reveal whether the existing transportation network is resilient to potential impacts from natural disasters and point out the most vulnerable areas in terms of emergency accessibility. The findings will provide a new insight into the accessibility-based planning of promoting a safe and resilient city. With the widely used cumulative-opportunity approach, we measure accessibility by counting emergency and lifesaving facilities (including parks, schools, hospitals, roads, and fire stations) that can be reached by driving at the census tract level in San Fernando Valley, CA. With the calculated accessibility, certain simulations are conducted to collect a set of pseudo data for what would happen if an arbitrary road were damaged by a selected disaster. To check this impact, the above-mentioned approach is used to recalculate accessibility by taking out a street segment located in hazardous areas from the transportation network system, one at a time, until the number of simulations is large enough for statistical analysis. With the results, accessibility damage hotspots are identified to point out the most vulnerable locations and statistical analysis is used to identify those areas where accessibility is significantly reduced compared to the original status. A normalized difference accessibility index (NDAI) is further created to suggest plans and strategies to help those vulnerable areas through adding facilities/services or improving transportation infrastructure.

PI's Background: Dr. Hovannes Kulhandjian

Project's date: December, 2021

Abstract: The goal of this research work is to maximize the detection capabilities of pedestrians, especially at night, by effectively data fusing the information gathered from a thermal camera, a radar sensor and a video camera along with the use of advanced machine learning algorithms to detect and avoid pedestrian collision in real-time. Using this multi- dimensional valuable data, it could make intelligent decisions during different conditions of the road, be it during the day or at night. The proposed system could potentially be imbedded into a smart car system that provides real-time pedestrian detection and alerting mechanism by vibrating the driver’s wheel and display a message on a monitor/dashboard to warn the driver to avoid colliding into the pedestrian. The proposed system can be used both during the day and at night using the combination of thermal infrared camera, a radar system and a video camera. It could also be installed in an autonomous vehicle. The PI has research expertise in the area of sensing combined with Artificial Intelligence. His most recent FSTI research work was based on Artificial Intelligence and Machine Learning. Recently, he presented two conference papers, please refer to [11, 12] one was in a flagship Institute of Electrical and Electronics Engineers (IEEE) Global Communications Conference (GLOBECOM) held in Hawaii while the other was in an International Conference run by the Association for Computing Machinery (ACM) held in Atlanta, Georgia

Objective: One possible solution is to use a video camera, a radar system, or a LIDAR system in a vehicle. More recently, the advancement of thermal IR cameras has shown a potential possible solution. The research on pedestrian detection and avoidance is still in its infancy. Several methods have been explored to detect a pedestrian and avoid an accident. To the best of our knowledge, no prior research work has explored or experimented with the idea of using Data Fusion from multiple sensors (i.e., a thermal infrared camera, radar sensor, and a visible camera) combined with advanced Machine Learning (ML) for pedestrian detection and avoiding mechanize. Therefore, we believe that this research exploration could lead to new Artificial Intelligent-based application tools for drivers that could potentially save lives. We will be exploring state-of-the-art ML techniques combined with data fusion to achieve this objective. The goal of this research work is to maximize the detection capabilities of pedestrians, especially at night, by effectively data fusing the information gathered from a thermal camera, a radar sensor, and a video camera along with the use of advanced machine learning algorithms to detect and avoid pedestrian collision in real-time. Using this multi-dimensional valuable data, it could make intelligent decisions during different conditions of the road, be it during the day or at night. The proposed system could potentially be embedded into a smart vehicle system that provides real-time pedestrian detection and alerting mechanism by vibrating the driver’s wheel and display a message on a monitor/dashboard to warn the driver to avoid colliding into the pedestrian. The proposed system can be used both during the day and at night using the combination of a thermal infrared camera, a radar system, and a video camera. It could also be installed in an autonomous vehicle.

PI's Background: Dr. Shahab Tayeb

Project's date: December, 2021

Abstract: This study analyzes the security of a common in-vehicle network standard, the Controller Area Network (CAN). Due to its inherent vulnerabilities to various forms of cyber-attacks, CAN implementations can easily be targeted by cybercriminals. Such vulnerabilities range from eavesdropping, where the attacker can read the raw data traversing the vehicle, to spoofing, where the attacker can place fabricated traffic on the network. We, initially, perform a simulation of CAN traffic generation followed by hardware implementation of the same on a test vehicle. Due to the obscure nature of CAN, we reverse-engineered the missing parameters through a series of passive sniffing attacks on the network. Finally, we demonstrate the feasibility of the attack by placing fabricated frames on the CAN.

PI's Background: Dr. Julio Roa

Project's Start date: December, 2021

Project's End date: May, 2022

Executive Summary:  The objective of this project [A1] seeks to determine how Regional Air Mobility (RAM) using electric/hybrid electric aircraft can provide new high-speed transportation for high priority passenger and cargo movement within Fresno County and connections to coastal urban centers. It is achieved by researching the demand for regional air travel generating an inventory of existing infrastructure, studying new technology available, studying infrastructure requirements from the landside and the airside, and evaluating the potential for integration with, and enhancement of, current and planned ground transportation services. 
Regional Air Mobility (RAM) using electric aircraft will become a reality within the next 10 years and transform both air and ground transportation by offering a new service using existing, underutilized airports that will change them into vibrant hubs for zero emission transportation for the communities they serve. Using small 5-20 passenger all electric or electric-hybrid aircraft, RAM services will provide connectivity for both passengers and freight to communities where ground transportation currently provides the bulk for goods and people movement. 
The San Joaquin Valley is an area of California that could benefit greatly from RAM services due to the large land area of the region, the presence of over 30 general use airports from Bakersfield to Stockton, and the need for improved connectivity for communities within the region with the urban centers in the north and south. In spite of having many small airports near cities in the region, there is currently only limited commercial air service available, leaving most of the region reliant on ground transportation. Understanding the potential of RAM to become an economic engine for communities with these underutilized airport assets was an important outcome for this research. 

Project Objective and Motivation: Advances in electric aircraft development are providing opportunities for new Regional Air Mobility services that can enhance connectivity of regions by using underutilized existing airport infrastructure and integrating use of electrified ground transportation. This research project seeks to determine how RAM using electric/hybrid electric aircraft can provide new high-speed transportation for high priority passenger and cargo movement within Fresno County and connections to coastal urban centers. This project also seeks to study the potential opportunities and challenges to effectively implement (electric/hybrid) RAM in the San Joaquin Valley. 
This study covers a range of topics to help clarify what RAM is and why it matters. It should not be construed as the final, defining source of all knowledge when it comes to possibilities and best ways forward as they relate to RAM initiatives. Rather, this study is intended to start a conversation with the communities that will be participants in what is an evolving RAM deployment process. 
The focus of this study is what is needed in terms of RAM development in order to effectively implement RAM for high-priority cargo and passengers. 

Final Report

PI's Background: Dr. Maria Calahorra-Jimenez

Project's Start date: December, 2021

Project's End date: July, 2022

Abstract: Improving long-term performance in highway projects is an imperative goal for public administrations. Project delivery and procurement methods might provide an opportunity to align design and construction processes with this goal. Previous studies have explored whether project delivery methods impact the long-term performance of highway projects. However, these studies did not focus specifically on how core elements within the procurement might relate to long-term performance. Thus, this research aims to fill this gap by exploring to what extent and how long-term evaluation criteria are considered in design-build best-value procurement of highway projects. To this end, content analysis was conducted on 100 projects procured between 2009 and 2019 by 19 DOTs across the U.S. The analysis of 365 evaluation criteria found that (1) roughly 11% of them related to long-term performance. (2) The weight given to these criteria in the overall technical proposal was lower than 30%. (3) Sixty-five percent (65%) of long-term evaluation criteria focused on design while 15% related to materials and technology, respectively. The results of this study are a first steppingstone to initiate a deep exploration of the relationship between procurement practices and actual project performance. Currently, with sustainability and life cycle assessments being top concerns in infrastructure projects, this line of research might be of particular interest to DOTs and highway agencies across the U.S. and worldwide.

Objective: In this research, the objective of the content analysis is twofold. First, it aims to identify to what extent RFPs include long-term performance evaluation criteria. To this end, the researcher used quantitative content analysis. Second, the study seeks to explore how long-term goals and evaluation criteria relate to various assessment categories. To this end, the researchers conducted a qualitative content analysis.

Final Report

 

Year 5 (2022)

PI's Background: Dr. Aly Tawfik

Project's date: December, 2022

Abstract: Freight transportation represents a significant amount of traffic and all its associated externalities, such as traffic safety, congestion, energy demand, greenhouse, and air pollution emissions, and infrastructure costs. However, it also plays a primary role in the supply chains and the costs and availability of goods and is a major player of the economy. This study aims to identify, assess, and utilize different data sources to uncover and understand the patterns and movements of the different types of freight in different counties of the San Joaquin Valley. The San Joaquin Valley region consists of 8 counties naming San Joaquin, Stanislaus, Marced, Madera, Fresno, Kings, and Tulare. This research has explored some major datasets consisting of freight data such as GTA, PIERS, and Streetlight Data Insights for the year 2019, i.e., to get a clear insight on what the actual movement of freight looked like pre-covid. The primary softwares used for this analysis are MS Excel, MS Access, ArcGIS, and Jacob Streetlight Insight. This research investigated all modes of freight transportation for domestic and international trade which are air, water, rail, and road. Findings of this research are valuable for multiple different governments as well as private agencies for various use cases such as development of transportation infrastructure, freight business, and environment assessments.

PI's Background: Dr. Aly Tawfik

Project's date: May, 2022

Abstract: Over the past decades, different kinds of surveys have traditionally been the primary source of data for understanding travel demand (patterns and behaviors) in a region, and for developing the transportation planning models and designing the transportation infrastructure. However, the substantial evolution of communication technologies and the large market penetration of smartphones over the last decade have opened the door for novel types of data: cellphone trace big data. While traditional surveys will continue to provide value and answers that are not possible by cellphone trace big data, applications of this novel data source in transportation have been consistently growing and are expected to only grow further. This study utilizes cellphone trace big data (from Streetlight Data) to uncover the spatio-temporal distribution of travel demand (e.g. trips by mode) in the urban as well as rural areas in Fresno County, California. The study visualizes Origin-Destination (OD) patterns and OD trends by mode in the region and contrasts them with the existing transportation infrastructure. The study demonstrates the potential value of this novel data source as it provides additional and valuable information that can significantly improve our ability for understanding travel demand, and plan and design more efficient transportation systems to meet this travel demand.

Learning Objectives:
Articulate the advantages and limitations of travel surveys and cellphone trace big data for transportation planning Discuss methods for using cellphone trace big data to understand travel demand in urban and rural areas
Use cellphone trace big data to investigate the suitability of the existing transportation infrastructure for serving its travel demand

PI's Background: Dr. Aly Tawfik

Project's Start date: December, 2022

Abstract: The San Joaquin Valley (SJV) Electric Tractor Development & Demonstration project is aimed at the analysis and demonstration of the potential benefits of utilizing the advanced technology of electric tractors and trucks in agricultural application as an alternative to their diesel-powered counterparts. Fresno State Transportation Institute (FSTI) collaborated as the third-party data analyst with Project Clean Air, Humming Bird EV (HBEV) and Moonlight Companies to implement the SJV Electric Tractor Development & Demonstration for the California Air Resources Board (ARB) Off-Road Advanced Technology Demonstration Projects program.

The contribution of FSTI in the project can be summarized in the following tasks:
Providing a baseline report for current tractor fleet use and energy use at Moonlight Companies,
Working directly with HBEV, the original equipment manufacturer, Moonlight Companies, the main demonstration site, and other demonstration sites to collect necessary data for final analysis,
Preparing a comprehensive plan for the collection of data in compliance with California ARB’s requirements,
Designing data collection tools (i.e. surveys and logs) to collect and capture all required data,
Assigning personnel to conduct field studies to continuously observe use, operations, fueling process and efficiencies of the electric tractor versus the conventional fueled tractors,
Working with Project Clean Air to provide data for quarterly and final reports.

PI's Background: Dr. Aly Tawfik

Project's date: December 2022

Abstract: Traffic has a significant impact on public health. Traffic-related air pollution affects the health of individuals, especially when it comes to respiratory and cardiovascular health. A large number of people die due to respiratory and cardiovascular-related complications each year. According to the World Health Organization, 17.9 million people died because of cardiovascular diseases in 2016, representing 31% of all global death. Although the impact of the traffic- related air pollution on individuals is evident, the relationship between traffic-related air pollution and public health has been less investigated in the census tract level. The main goal of the study was to determine whether there was a relation between the health of a community, the traffic within them, and how they connect. Traffic and health data of the entire Fresno County were collected and then were analyzed at the census tract level. The results of this research showed a significant effect of traffic congestion on public health in the census tract level. The findings of this study could help in future planning and in the allocation of funds to help communities with health problems.

PI's Background: Dr. Aly Tawfik

Project's date: May, 2022

Abstract: Traffic congestion is possibly one of the major negative impacts of travel. A large number of people are adversely affected by congestion each day in California and worldwide. In addition to global impacts such as greenhouse gas emissions and energy demand, traffic congestion significantly affects the direct population in areas where it occurs. It causes environmental degradation, significant loss of productive time, health impacts, and significant economic impacts. Measuring and identifying the causes of traffic congestion are necessary steps for understanding and reducing congestion. This study attempts to uncover some of the major causes of traffic congestion. The study analyzes traffic congestion in six major metropolitan areas in California: San Francisco and the Bay Area, Los Angeles, San Diego, Sacramento, Fresno and Bakersfield. The study investigated the possible impact of 35 different attributes on different measures of traffic congestion in these six metropolitan areas. Different attributes were acquired from a variety of data sources (e.g. road networks were collected from local Metropolitan Planning Organizations, MPOs). ArcGIS was utilized for most of the attribute computations. The 35 attributes are classified into 5 main groups: infrastructure attributes (e.g. roadway or lane miles normalized by population or area), connectivity attributes (e.g. roadway links or nodes normalized by area), socioeconomic attributes (e.g. median income and population density), weather attributes (e.g. days of precipitation), and trip attributes (e.g. number of carpools per household). Four different measures of traffic congestion were utilized: Travel Time Index, Roadway Congestion Index, Delay per Auto Commuter, and Cost per Auto Commuter. The results of this work indicated that the roadway miles per population and the number of roadway links per area were the two most highly and consistently significant variables in determining congestion. Roadway miles per population had a negative relationship with traffic congestion and the roadway links per area had a positive relationship. Results of this work could be helpful in understanding and addressing traffic congestion in urban areas.

PI's Background: Dr. Hongwei Dong

Project's date: May, 2022

Abstract: The concept of smart transportation has received a lot of scholarly attention during the last decade. New mobility technologies and innovations, such as autonomous vehicles, electric cars, and shared mobilities, are revolutionizing the transportation industry and transforming American cities. To date, both the research and the implementation of smart transportation technologies have primarily focused on large urban and metropolitan areas. We have a limited understanding of the application and development of smart transportation technologies in small cities and rural areas. Can the promise of smart transportation be extended to small urban and rural communities? Will small urban and rural communities be left behind the smart transportation revolution? The objective of this study is to evaluate the development of smart transportation and smart city technologies in small urban and rural communities in California’s Central Valley, particularly those in Fresno County. 

Specifically, this study attempts to achieve three goals. First, we survey the state-of-the-art practices of smart transportation technologies in both large and small cities as well as in rural communities in the United States. Second, we evaluate the development of smart transportation and smart city technologies in small urban and rural communities in California’s Central Valley by conducting surveys and interviews with local experts, transportation engineers, urban planners, and policy makers. The first-hand data collected through surveys and interviews are complemented by the second-hand data that are available from local planning agencies and other public data sources such as the U.S. Census Bureau. The first- and second-hand data allow us to evaluate the extent to which smart transportation has been implemented as well as the barriers to implementing smart transportation technologies in small urban and rural communities in the Central Valley. Lastly, we propose policy suggestions based on the successful experiences outside of the Central Valley and our careful evaluation of the development of smart transportation in small urban and rural communities in the Central Valley.

PI's Background: Dr. Hovannes Kulhandjian

Project's date: November, 2022

Executive Summary: Pedestrian fatalities have surged in the United States over the past decade. During this 10-year period, pedestrian fatalities have increased by 46%, from 4,302 deaths in 2010 to an estimated 6,301 in 2019. The number of pedestrian fatalities at night grew by 54%, while daytime pedestrian fatalities climbed by just 16% during that same decade (NHTSA 2021). Of these fatal accidents, about 75% of them occurred after dark (Feese 2020). In addition, an American Automobile Association (AAA) research study that tested pedestrian detection in current vehicles found that the evaluated pedestrian detection systems that consisted of radar (radio detection and ranging), image sensors (camera), LIDAR (light detection and ranging), and ultrasonic sonar were ineffective during nighttime conditions (Edmonds 2019). The goal of this project is to reduce the number of nighttime pedestrian fatalities by combining data acquired from three separate sensors in real-time and using machine learning algorithms to detect pedestrians at night to alert the driver of the possibility of a collision with a pedestrian. The proposed project also has applications in autonomous vehicles where a signal can be developed to engage the automatic braking system if necessary. This project focuses on AI-based pedestrian detection and avoidance at night using an infrared (IR) camera, an RGB (red, green, and blue) video camera, and micro-Doppler RADAR. Specifically, this project will use machine learning with deep learning algorithms to detect humans at night and data fuse the information to alert the driver of a possible accident with a pedestrian. One possible solution is to use a video camera, a radar system, or a LIDAR system in a vehicle. More recently, the advancement of thermal IR cameras has shown a potential possible solution. The research on pedestrian detection and avoidance is still in its infancy. Several methods have been explored to detect a pedestrian and avoid an accident. The main contribution of this research work lies in utilizing three different sensors (i.e., a thermal infrared camera, radar sensor, and a visible camera) combined with advanced machine learning (ML) for pedestrian detection and avoidance. Therefore, we believe that this research could lead to new artificial intelligencebased application tools for drivers that can save lives. We will explore state-of-the-art ML techniques combined with data fusion to achieve this objective. The goal of this research work is to maximize pedestrian detection, especially at night, by effectively data fusing the information gathered from a thermal camera, a radar sensor, and a video camera along with the use of advanced machine learning algorithms to detect and avoid pedestrian collision in real-time. Using this multi-dimensional data, the system can make intelligent decisions during different conditions of the road, both during the day or at night. The proposed system can be embedded into a smart vehicle system that provides real-time pedestrian detection and alerting mechanisms by vibrating the driver’s wheel and displaying a message on a monitor/dashboard to warn the driver of an incoming pedestrian. The developed system can be used both during the day and at night using a combination of a thermal infrared camera, a radar system, and a video camera. The system can also be installed in an autonomous vehicle.

Final Report

PI's Background: Dr. Scott Peterson

Project's date: December, 2022

Abstract: Pavement performance investigation and evaluation is critical for pavement management systems (PMS) to maintain good driving conditions and prioritize maintenance or rehabilitation efforts and funding (Chun et al, 2021). For this purpose, agencies are interested in the type, extent, and severity of different distresses. The most important distresses include rutting, cracking (fatigue cracking and thermal cracking) for flexible pavement, and cracking and faulting for rigid pavement. There is specialized equipment available for the identification of pavement distresses and quantification of pavement condition. However, the specialized equipment generally has high variability, is subject to detection errors, and requires much labor, or costly efforts (Chun et al, 2021; Huang et al, 2014). Therefore, a reliable, accurate, time efficient, and cost‐effective way to collect pavement condition data and evaluate pavement performance is of interest. Recently, mobile phones and mobile electronic devices began adapting new camera and 3D sensing technologies. In 2020, the Apple iPad Pro and the Apple iPhone 12 Pro gained a new technology with a LiDAR sensor to help improve portrait mode photos in the day and night time. This new LiDAR sensor however has various not intended uses that need to be explored to identify further reaching capabilities that can be applied to many other applications, such as pavement performance.

PI's Background: Dr. Julio Roa

Project's date: December, 2022

Abstract: California is aggressively moving forward with efforts to deploy zero-emission transportation technology to fight climate change. However, to date, the investments California has made with Cap-and-Trade funding have focused on ground transportation and some marine sources. These sources are major contributors to climate change but do not represent the entirety of transportation modes in California. One mode of transport where California is lagging in recognizing the potential to reduce GHG emissions through electrification is air transport with the rapidly emerging development and deployment of zero-emission aircraft powered by battery/hybrid electric motors. There are over 140 public-use airports in California with 32 of those being in the San Joaquin Valley. Many of these airports are in close proximity to growing population and commerce centers, particularly in the San Joaquin Valley, but are underutilized. The development of advanced electric/hybrid electric is opening the door to using these airports for both passenger and freight movement through significantly reduced costs of operation associated with electric propulsion. Strategic investment in the supporting infrastructure to facilitate operations of these new aircraft in conjunction with zero- emission ground vehicles offers the potential to transform these existing airport assets into multi-modal, zero-emission transportation hubs for the communities they are located in; bringing enhanced mobility and increased economic activity to many communities currently isolated due to limited ground transportation connections. The objective of this project is to maximize opportunities for California’s cap-and-trade program to reduce the impact of greenhouse gas emission and transportation on climate change by comparing GHG emissions from both ground and air modes of transportation including evaluating new advances in air mobility being developed using electric/hybrid-electric propulsion for aircraft.

PI's Background: Dr. Fariborz Tehrani

Project's date: December, 2022

Abstract: The motivation for this research stems from the need for extending the service life, reducing the life cycle cost, and improving the safety and reliability of bridge abutments. This proposal endeavors to develop advanced solutions for application of rotary kiln manufactured lightweight aggregates in mechanically-stabilized earth (MSE) bridge abutments (Figure 1) to extend the service life of bridges and reduce the need for maintenance and rehabilitation of bridges, abutments, and approach and departure slabs on roadways. This solution identifies cost-effective MSE systems to delay or eliminate corrosion damages for long-term service life of roadways and bridges. The outcome of this proposal reduces the life-cycle cost, input energy, and greenhouse gas emissions associated with construction, maintenance, and rehabilitation of MSE bridge abutments and other backfills involving embedded steel products. The innovative approach of this proposal is the evolution of current testing methods to measure corrosion of reinforcing steel elelments as a function of electrochemical properties of backfill materials. This proposal extends and amends current national efforts led by the National Cooperative Highway Research Program (NCHRP), the American Association of State Highway and Transportation Officials (AASHTO) and several Departments of Transporation (DOT) highlighting past achievements in Fresno State and new possibilities for the State of California.

PI's Background: Dr. Fariborz Tehrani

Project's date: December, 2022

Abstract: Fresno, California is essentially the kind of a city that is continuously spreading out instead of building up with time. In the past decades, any of the locals can easily observe that the city has been spreading out to the north (e.g., those in the north from the Copper Ave) and east (e.g., those in the southeast from the Fowler Ave). The above-mentioned edge cities can be even found along Highway 41 toward Madera County, such as the new built Tesoro Viejo neighborhood, although there are some renewed apartments with a higher density structure found in the downtown area. To help Fresno move toward sustainability requires the understanding of the effects of varied transportation investments and land-use restrictions, such as the provision of public transit and bike lanes, high density zoning, and growth boundary. However, this had not been done in the past to provide a research framework to comprehensively evaluate either such a transportation or land-use policy for the promotion of a compact city toward sustainability, and therefore is needed.

PI's Background: Dr. Fariborz Tehrani

Project's date: December, 2022

Abstract: The San Joaquin Valley (SJV) has been known for poor air quality and high rates of respiratory-related illnesses. Veloz et al. (2020) conducted a study on perceptions about air quality in SJV residents and found that a majority of the participants are worried about air quality. Hence, promoting alternative forms of transportation is critical in our community. In this research, we propose to examine the baseline air pollution exposure of pedestrians, cyclists, drivers, and passengers during transportation. This study will provide valuable findings that are useful for planning transportation facilities more efficiently to protect people, promoting active transportation modes, and increasing awareness of clean air efforts in transportation for healthier communities.