Publications 

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Project Summary:

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.

 Objectives: 

To investigate how each of the transportation investments and land-use restrictions can guide the future development toward a compact urban form ti achieve sustainability. 
To better understand how much effort in transportation investments and land-use restrictions is required to make the proposed urban reform to take place in Fresno; 
To provide planning information for promoting California’s cap-and-trade program to reduce the impact of greenhouse gas emission and transportation on climate change. 

The report will be available in year 2023.

Project Summary:

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.

The report will be available in year 2023.

Project Summary:

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 the 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.

This research proposal is aligned with the following SB-1 objective:

“Objective 1: Leverage new technologies, including vehicle automation, and innovative processes to achieve a seamless, multimodal surface transportation system that integrates with other “smart city” investments.”

The report will be available in year 2023.

Project Summary:

There are over 590,000 bridges strewn across the network of highways stretching across the United States, alone. The Federal Highway Act (FHWA) of 1968 mandates that each bridge with a length of 20 feet or more must be inspected at least once every 24 months. Each inspection must align the criteria outlined by the National Bridge Inspection Standards (NBIS) [1].

Additionally, a bridge inspection will identify major structural issues that require follow-up, quantify the overall condition of the bridge to prioritize capital needs, identify routine maintenance, and catalog a history of the bridge’s condition. Inspecting bridges has been a labor-intensive and a very costly process. 

Drones can potentially cut costs, provide better data, and improve worker safety during bridge inspections. Using drones for bridge inspections greatly reduces the costs associated with the inspection. 

In this research work we propose to implement an AI-based bridge and road inspection framework using drones with multiple sensor collecting capabilities. It is not sufficient to do inspection using cameras, we plan to utilize infrared (IR) camera along with a high resolution optical camera. The IR camera can provide more details to the interior structural damages of a bridge compared to an optical camera that is more ideal for inspecting damages on the surface of a bridge. In addition to that our drone inspection system is equipped with computer on chip that runs Machine Learning algorithms that enables autonomous driving of the drone and taking images of the bridge or the road structure whenever it detects any damages. Instead of having a person operate the drone it will self-operate and carry out the inspection process on its own using advanced AI algorithms we are developing.

 

 

The report will be available in year 2023.

Project Summary:

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.

The report will be available in year 2023.

Project Summary:

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.

The report will be available in year 2023.

Project Summary:

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.

This proposal is aligned to address three objectives in SB‐1 objectives ‐ Objective 1, 2 and 3 which incorporate 1) new technologies, 2) cost‐effective maintenance and decision‐making of roads, and 3) long term maintenance and pavement rehabilitation needs.

The report will be available in year 2023.

Project Summary:

Objectives:

Show the average % change in accessibility to E&L facilities over the region for earthquake and wildfire.

Reveal the hotspots with statistically significant impacts to accessibility.

Examine which public investment is needed to improve the resilience of accessibility.

Explore possible mitigation measures using new technology.

Full report will be available soon.

Project Summary:

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.

Full report will be available soon.

Project Summary:

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.

Full report will be available soon.

 

Project Summary:

RAM focuses on building upon existing airport infrastructure to transport people and goods using innovative aircraft that offer a huge improvement in efficiency, affordability, and community-friendly integration over existing regional transportation options. These aircraft, which typically carry less than 20 passengers or an equivalent weight in cargo, are flexible in terms of where they can take off and land, even using existing runways and infrastructure to maximize compatibility with today’s airports.

This project proposes to discover the feasibility of RAM supporting high-speed transportation for high-priority passenger and cargo movement within Fresno County and connection to coastal urban centers.  Some examples of high-priority passengers and cargo could include, but be limited to, medical patients needing specialized and/or emergency treatment, organ transport, and critical medical supply deliveries. 

Electrification of aviation is happening, and Fresno County has the potential to combine our existing closely spaced underutilized airport infrastructure, early demonstration, and experience with electric aircraft, renewable energy opportunities, central location within the state, and the need to open the door for new industry opportunities for our youth to take advantage of this “Third Revolution” in aviation.

Full report will be available soon.

Project Summary:

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

Full report will be available soon.

Project Summary:

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.

Full report will be available soon.

Executive Summary:

The main purpose of this research is to reveal (1) what factors affect people’s choice of walking or cycling, and (2) what factors encourage walkers and cyclists do so more frequently. We focus on the effects of accessibility to multi-use paths and the clustering effect.  Accessibility to multi-use paths (MUPs) by walking or cycling is calculated for Salt Lake City, Utah; the accessibility measure indicates the total length of multi-use paths (walkway and bikeway) a resident could reach from the household location within a 15-min walking distance or a 20-min cycling distance based on the average travel time from the 2012 Utah Travel Survey. We estimate two spatial models at two levels to understand the impact of MUP accessibility and the clustering effect (spatial autocorrelation) on people’s active travel behavior. First, a spatial probit model is estimated to identify whether and why people walk or cycle. Second, a spatial autoregressive model is estimated to examine what factors would encourage walkers or cyclists to spend more time walking and cycling. Our main methodological contribution is the consideration of all typical categories of explanatory variables (individual and household socioeconomics, local built-environment features, and travel and residential choice attitudes) as well as two new variables (MUP accessibility and the clustering effect) which have often been neglected in past travel behavior studies. Interestingly, the modeling results reveal that a resident who bikes more likely lives with their neighbors who do not do so. Further, residents who have been cycling or walking are likely to do so more when they see others doing so. Moreover, MUP accessibility by walking or cycling only has an influence on those who have been walking or cycling. In other words, residents would not necessarily cycle or walk just because they live in a neighborhood with good accessibility to multi-use paths, implying that it is necessary to combine other non-physical measures for the promotion of active transportation. These results suggest that decisionmakers should design and implement active transportation policies and plans differently for the doers (walkers and cyclists) and non-doers. 

To see the report, please click here.

To see the report, please click here.

Executive Summary: 

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 consolidated data-driven transportation information to the public. The relevant and timely information from data facilitates the improvement of decision-making processes for the establishment of public policy and urban planning for sustainable growth, and for promoting public health in the region. For the characterization of the spatial variation of transportation-emitted air pollution in the Fresno/Clovis neighborhood in California, various species of particulate matters emitted from traffic sources were measured using real-time monitors and GPS loggers at over 100 neighborhood walking routes within 58 census tracts from the previous research, Children’s Health to Air Pollution Study - San Joaquin Valley (CHAPS-SJV). Roadside air pollution data show that PM2.5, black carbon, and PAHs were significantly elevated in the neighborhood walking air samples compared to indoor air or the ambient monitoring station in the Central Fresno area due to the immediate source proximity. The simultaneous parallel measurements in two neighborhoods which are distinctively different areas (High diesel High poverty vs. Low diesel Low poverty) showed that the higher pollution levels were observed when more frequent vehicular activities were occurring around the neighborhoods. Elevated PM2.5 concentrations near the roadways were evident with a high volume of traffic and in regions with more unpaved areas. Neighborhood walking air samples were influenced by immediate roadway traffic conditions, such as encounters with diesel trucks, approaching in close proximity to freeways and/or busy roadways, passing cigarette smokers, and gardening activity. The elevated black carbon concentrations occur near the highway corridors and regions with high diesel traffic and high industry.

 

This project provides consolidated data-driven transportation information to the public including:

1. Transportation-related particle pollution data

2. Spatial analyses of geocoded vehicle emissions

3. Neighborhood characterization for the built environment such as cities, buildings, roads, parks, walkways, etc.  

To see the report, please click here.

To see the report, please click here. 

It will be available soon. 

Executive Summary: 

Driving while drowsy is one of the most prevalent causes of motor vehicle accidents. Driver drowsiness is reported to be responsible for 1–2% of all motor vehicle accidents (Owens et al, 2018), however, other studies reveal that the number of reported accidents is considered to be conservative. Although the effects of drowsiness and fatigue are often compared to the impairment caused by drinking alcohol, the evidence of drowsiness in the event of a crash are unreliable and often go unseen. “Drowsiness is similar to alcohol in how it compromises driving ability by reducing alertness and attentiveness, delaying reaction times, and hindering decision-making skills,” said Dr. Nathaniel Watson, spokesperson for the American Academy of Sleep Medicine. “Drowsy driving is deadly, but it can be prevented” (American Academy of Sleep Medicine, 2015). A research brief by the American Automobile Association (AAA) Foundation for Traffic Safety, states that standard police reports cannot be used as the sole source of data in estimating the number of crashes involving driver drowsiness due to two main reasons: firstly, the presence of drowsiness after a crash may be entirely absent given what the driver(s) have just endured. Secondly, drivers involved in motor vehicle crashes are hesitant to admit to their drowsy state. In an effort to determine the prevalence of drowsy driving, the AAA Foundation for Traffic Safety obtained naturalistic driving data by placing video cameras in 3,593 subject’s vehicles for roughly a three year period. A total of 701 police reportable crashes were recorded. The results demonstrated that the percentage of crashes where drowsiness was involved was between 10.6–10.8% (Owens et al., 2018), as opposed to the NHTSA’s estimated 1.4% (NHTSA, 2017). To understand how underreported driver drowsiness is, we can apply the two percentages (i.e., 10.6–10.8%) to the total number of reported crashes for 2018. In doing so, the resulting values are to be considered generous given the absence of unreported occurrences where driver drowsiness may have been involved. The NHTSA estimates that in 2018, there were 6.73 million police-reported crashes in the United States (National Center for Statistics and Analysis, 2018). Applying the NHTSA’s estimated total percentage of driver drowsiness crashes to the total number of accidents reported in 2018 results in approximately 94,000 cases, while applying the more probable percentage determined by the AAA results in over 700,000 cases. An astounding 700% increase in the number of crashes where driver drowsiness may have played a role, but failed to be reported. Drowsy driving is defined by the American Academy of Sleep Medicine as the moment at which a person who is operating a motor vehicle becomes too tired to remain alert and as a result may have slow reaction times, reduced vigilance, and impaired thinking (American Academy of Sleep Medicine, 2015). There are many symptoms of drowsiness and fatigue one must be aware of when thinking about operating a motor vehicle. The signs include: yawning, inability to keep your eyes open, nodding off, inability to remember driving the last few miles, and drifting into other lanes or onto the shoulder (American Academy of Sleep Medicine, 2015). 

In this research, we provide a reliable solution to address the issue of driver drowsiness. Our driver drowsiness detection system uses image data recorded by a webcam and signatures returned from a micro-Doppler radar, combined with deep learning, to classify the state of alertness of the driver. In order to determine a driver’s level of alertness, facial images sent from the webcam will serve as the input to the Deep Convolution Neural Network (DCNN) algorithm. The DCNN classifies the state of the driver’s eyes, mouth, and head position. Through these classifications, patterns resembling symptoms of drowsiness can be detected and then used to alert the driver when they are or may become drowsy. The micro-Doppler sensor is also used to track the motion of the driver’s head; since nodding off is a common symptom of drowsiness. The sensory data from the micro-Doppler also serves as input to a second DCNN architecture that will classify the driver as drowsy, and alert them promptly. A vibration of the steering wheel is used to alert the driver when the system detects the driver is about to doze off. 

To see the report, please click here.

Executive Summary:

By using the data from the confidential version of the 2010–2012 California Household Travel Survey (CHTS) along with several other data sets of vehicle sales prices and fuel efficiency, this study evaluates the impact of transit-oriented development (TOD) on household transportation expenditures in the four largest California metropolitan regions: the San Francisco Bay area, the greater Los Angeles region, the San Diego metropolitan area, and the Sacramento metropolitan area. The study estimates transportation expenditures at the individual household level and breaks down household transportation expenditures into sub-categories such as vehicle ownership cost, vehicle operating cost, and transit cost. The study quantifies the impacts of TOD on household transportation expenditures by comparing TOD households with two groups of control households that are identified by propensity score matching. The first control group consists of non-TOD households that are very similar to TOD households by socio-demographic variables. The second control group consists of non-TOD households similar to TOD households by both socio-demographic characteristics and neighborhood environment and location. The study shows that households living in TODs are significantly different from households who live outside of TODs in terms of household demographics and neighborhood environment. They tend to own fewer but more fuel-efficient cars, drive fewer miles, and use transit more. The transportation expenditures of the typical TOD household are about 40% lower than the typical non-TOD household. When controlling for household demographics, TOD households own fewer and more fuel-efficient cars, drive fewer miles, and use transit more. On average, they save $1,232 per year on transportation expenditures compared to non-TOD households with similar demographics, accounting for 18% of their total annual transportation expenditures. When controlling for both demographics and neighborhood environment, TOD households still own slightly fewer and more fuel-efficient cars and use transit more, but they drive fewer miles compared to non-TOD households. TOD households save $429 per year on transportation expenditures compared to non-TOD households with similar demographics and neighborhood environment, accounting for about 6% of their total annual transportation expenditures. This study confirms that Californian households save money on transportation costs by living in TODs. TOD households save money on transportation costs mainly because they own fewer cars than non-TOD households. About two-thirds of the savings can be attributed to transit-friendly neighborhood environment and one-third to access to rail transit, suggesting the importance of integrating a rail transit system with supportive land use planning and neighborhood design. 

By using data from the confidential version of the 2010–2012 California Household Travel Survey (CHTS), this study compares the transportation costs of individual households living in TODs with a control group of non-TOD households that are identified via propensity score matching. We draw data from several sources to build a database of vehicle fuel efficiency and purchase prices, which allows this study to decompose transportation expenditures at the individual household level into a few sub-categories such as vehicle ownership costs, operating costs, and transit cost; we then compare each item between TOD and non-TOD households. The decomposition of transportation costs helps us to understand how exactly TODs influence transportation costs. The report is organized as follows: Section 2 introduces the conceptual framework of this study and reviews previous studies, Section 3 describes the data and methods, Section 4 presents the main findings of this study, and Section 5 concludes and discusses policy implications.

To see the report, please click here.

Executive Summary:

To stay ahead of novel attacks, cybersecurity professionals are developing new software programs and systems using machine learning techniques. Neural network architectures improve such systems, including Intrusion Detection System (IDSs), by implementing anomaly detection, which differentiates benign packets from malicious packets. For an IDS to best predict anomalies, the model’s training dataset is typically pre-processed through normalization and feature selection/reduction. Pre-processing techniques play an important role in training a neural network to optimize its performance. In this study, we extend the current research on the importance of data normalization through developing, training, and testing a Deep Neural Network on CIDDS network data. To this end, we evaluate the effect of Z-Score and Min-Max normalization on the model’s accuracy, loss, FScore, and AUC-ROC. Additionally, an analysis and comparison of the performance of the model on the NSL-KDD and CIDDS datasets are carried out. 

To see the report, please click here.

Summary:

This research comprised of an experimental characterization of the material properties of recycled concrete aggregate (RCA) and residual cement mortar (RCM) in RCA. The material properties of the RCA and RCM studied include RCM content, as well as specific gravity and absorption of RCA and RCM. Using 100% virgin aggregate as control hot mix asphalt (HMA) mix, this study evaluated the effects of the RCA and/or RCM properties on the performance of HMA when RCA was used to partially replace the virgin aggregate (RCA-HMA).

To see the report, please click here.

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. The research team measures the total length of multi-use paths (walkway and bikeway) a resident could reach from their 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 transportation investments. • The GWR results are embedded into a multi-objective optimization modeling framework to improve accessibility to multi-use paths across 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 and  economically efficient and socially equitable active transportation plan to foster public health.

To see the report, please click here.

Executive Summary:

The Fresno State Transportation Challenge (FSTC) uses an action civics approach to support K–8 students to develop transportation-related projects that have a positive impact on the community. The culminating outcome is a community showcase, where students present their work to the public. After an initial pilot phase in spring 2019, in an afterschool setting during the normal school year, the Fresno State Transportation Institute (FSTI) supported two cycles of the Transportation Challenge during the summer and fall of 2019: an intense three week program during summer school, and an eight to ten week program during classroom instructional time during the normal school year. Our research examining these two cycles found strong evidence that the Transportation Challenge can teach elementary and middle school students about transportation, about transportationrelated careers, and empower them to apply this knowledge in addressing transportation related issues in their community. Participating university students, who supported the K–8 students in their work on these projects, had a positive influence on the young students’ learning experience and served as inspiring role models. Likewise, the university students appreciated the opportunity to interact with younger students and engage in meaningful learning. The pedagogical approaches of action civics and eduScrum, which frame the Transportation Challenge, were found to be an engaging framework that, on one hand, created a meaningful context for the program, and allowed all students to engage in the work on the other. The K–8 students reported that they felt they had a chance to be creative and work on meaningful projects to improve their community and learned how to collaborate better, work in a team, develop their critical thinking, and overcome challenges when working on the project. Overall, action civics approaches such as the Transportation Challenge are an effective way to involve youth in learning about transportation and empower them to have a positive impact on their community.

To see the report, please click here.

To see the report, please click here.

Executive Summary:

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 Safe TREC 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.1 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.2 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 suggests that the utilization of expansive horizon time framing and promotionfocused 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.

To see the report, please click here.  

Executive Summary:

The development of chemical kinetic models has become a main area of combustion research, necessitated by the fact that these models describe the chemical kinetics of combustion processes more accurately than global reaction models. 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 kinetic 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 overcome two main challenges. The first challenge is that simulating main combustion properties such as ignition delay time and laminar burning velocity require different types of numerical models, as these are two separate combustion problems that occur at different settings. Simultaneous simulations of such properties require exploring a potential link. Such a link can particularly facilitate estimation of the flame propagation behavior of fuels from knowledge of their auto-ignition behavior, which are two separate combustion problems. The second challenge is reducing 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.2 The motivation behind the 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. This work provides an attempt to address these two challenges. To address the challenge of linking auto-ignition and flame propagation simulations, a characteristic flame time, defined in the thermal flame theory, is determined from thermal diffusivity and laminar burning velocity. Parametric dependence of flame time and ignition delay time on pressure, temperature and equivalence ratio is examined based on validated chemical kinetic mechanisms for methane, propane, and ethanol. This is done to explore similarities and differences between the two characteristic times and their dependence on combustion conditions, and eventually to developing a correlation between flame time and ignition delay time. Such a correlation enables the prediction of laminar burning velocity of a given fuel under a specific condition based on ignition delay time knowledge, and it therefore enables simultaneous simulation of both properties.

The second challenge is addressed in a chemical kinetic modeling study of the hightemperature ignition behavior of Tetrahydrofuran (THF), a promising second-generation transportation biofuel. THF was chosen as the fuel of interest to represent second-generation biofuels, an environmentally friendly alternative to fossil fuels and one which can replace them without major engine modifications. Such biofuels have a great potential for production from sugars and biomass,3 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 global energy consumption.4 The Stochastic Species Elimination (SSE) reduction approach is implemented to develop multiple skeletal versions of a chemical kinetic model of THF based on ignition delay time simulations at various pressures and temperatures as detailed in the literature. The developed skeletal versions are combined into a global skeletal model. Ignition delay times are simulated using detailed and skeletal models, with good agreement observed at higher temperatures. Sensitivity analysis is then performed to identify the most important reactions responsible for the performance of the skeletal model. Reaction rate parameter modification is performed for such reactions in order to improve the agreement of detailed and reduced model predictions with experimental ignition data from the literature. The proper chemical kinetic modeling of the combustion and emission behavior of secondgeneration biofuels would identify potentially favorable characteristics of such fuels relative to conventional fossil fuels used in the transportation sector, both qualitatively and quantitatively. This work contributes toward improved understanding and modeling of the oxidation kinetics of conventional and bio-derived transportation biofuels, as well as the estimation of laminar burning velocity that can be encountered in turbulent combustion simulations. 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-andtrade program (SB-1 Objective 5). The findings of such modeling effort would provide invaluable information that can support and improve the decision-making processes surrounding 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 Resources Board, with respect 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. 

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Executive Summary:

In this research work, the author develop a visible light communication (VLC) framework that can be used for intelligent transportation systems (ITSs). ITS has been motivated by the need to reduce traffic congestion and offer better user experience in navigation and locationspecific services. Recently, VLC has drawn a lot of attention by the research community in the areas of high data rate transmission, secure communications, and indoor localization systems as well in ITS. The use of VLC in ITS could lead to potential new useful applications. Traffic lights have been used to control traffic flow and are often located at a particular place, and they are rarely moved. It would be of great use to enable the traffic lights to be able to talk to the vehicles in their proximity and convey important information about the traffic conditions. In this project, the aim is to develop a framework that can support infrastructure-to-vehicle (I2V) and vehicle-to-infrastructure (V2I) communication: in this context the infrastructure refers to traffic lights using VLC. Specifically, traffic lights are used to not only to orderly provide traffic flow, but also to share some important information to the cars. The developed smart 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 take a detour from 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 for analysis and to provide smarter traffic control. The focus is on the development of VLC infrastructure to establish communications between the traffic lights and vehicles for better traffic management. To begin with, the researchers establish a visible light communication link between a traffic light and a vehicle which is capable of receiving the information. To do that, the research team first develops transmitter circuitry that is composed of an embedded system and optical electronics fast-switching network. The traffic lights not only will be performing its functionalities i.e., providing traffic light signals to pedestrians, drivers, but also sending out pertinent coded information to the vehicles through light pulses. After presenting the transmitter side circuitry, the authors will then present the receiver circuitry that is composed of optical electronics circuitry in which the photodiode along with other circuitry is used for detecting and decoding the VLC signal coming from the traffic lights. The received signal is passed through an analog-to-digital (ADC) interface before sending them to the embedded system to receive and decode the transmitted signals. The authors have also developed and experimented a novel optical code-division multiple-access (CDMA) scheme for overloaded optical CDMA transmission in which the optical codes will be uniquely decoded. This new coding system could potentially provide higher data rates and can support larger numbers of users in the visible light communication protocol establishment. After developing the system, the researchers conducted actual experimentation using a traffic light model/prototype and experimented with the VLC framework to test its functionality and have been working on improving its performance.

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Executive Summary:

Research on the relationship between urbanicity and physical activity has yielded mixed results, despite many studies consistently showing that residents tend 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 f iner geographic scales in the entire nation, with and without controlling for the built and social environment at the neighborhood level. This study takes advantage of several new questions that were added to the 2017 National Household Travel Survey (NHTS) regarding people’s physical activity and their walking 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 non-metropolitan areas (urban and rural). The researchers conducted both descriptive and modeling analyses to evaluate the intra- and inter-metropolitan patterns of physical activity and active travel in the United States. The researchers also differentiated walk and bike trips that were strictly for exercise from walk and bike trips undertaken for other purposes This study shows that the relationship between urbanicity and physical activity demonstrates a flat U-shape. Residents were more physically active when they lived in 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 very slight geographic variation in the weekly rates of walking and bike trips that are strictly for exercise. There is much more variation of the weekly rates of walk and bike trips that are undertaken for non-exercise purposes. Walkers and cyclists in the eight different geographic locations reported different infrastructure and safety barriers that kept them from walking 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 trails was the prominent infrastructural 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 condition 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 for walkers in other locations. Insufficient lighting at night was consistently reported as the most prominent safety barrier to walking more in various 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 to 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 have focused on urban and suburban residents. Our understanding of rural residents’ active travel and physical activity is limited. More research needs to study how rural residents travel in non-motorized modes and how they manage to take more walking trips than mid-ring and outer-ring suburbanites.

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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.

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Report will be available soon. 

Executive Summary:

Over the past few years, there have been notable trends in the areas of tracking public opinion, especially in public issues such as transportation. Such powerful processes continue to be a critical (and often mandated) component of the democratic process as they help policy makers connect with affected constituencies. This study explores travel trends and transportation preferences of a sample of adults in the California Central Valley of Fresno, an increasingly congested region that is also heavily agricultural and regarded as an expected launching pad for California’s first high-speed rail system. Relying on an e-survey modeled off a statewide polling project, this study used a modified electronic survey as a valuable predictor of public opinion. Findings include preferences skewing toward concern about local issues (road conditions, safety, accessible active transport) and a lack of knowledge about future mobility options (high-speed rail, driverless cars). Based on these results, Fresno should be viewed as a prime area for focused public information campaigns to foster behavior change and attitudes about potential transportation improvements.

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Executive Summary:

The application of Tire-Derived Aggregates (TDA) as a green, durable, and economicallyefficient material, enhances the sustainability of transportation infrastructure. Throughout the course of this research study, the application of TDA in combination with expanded clay (EC) aggregates will be investigated in concrete slabs used in road pavements and bridge decks serving non-auto traffic, such as bicycle routes, through a set of experimental tests and life-cycle cost analyses. To this end, TDA, which is obtained from recycled tires, and EC, produced in rotary kilns, substitute coarse aggregates in conventional concrete. The final product, also known as lightweight rubberized concrete, is durable and economically-efficient. It also enhances the sustainability of transportation infrastructure by mitigating the necessary maintenance and rehabilitation needs of these slabs. In this report, an experimental study has been undertaken to first estimate mechanical properties of lightweight rubberized concrete using 100% EC, 100% TDA, and a mixture of 20% EC – 80% TDA; the TDA was replaced by the volume of the EC aggregates. Next, a series of static flexural and dynamic impactfatigue tests were performed on simply-supported beam specimens and slab assemblies, respectively, to measure both modulus of rupture and durability when subjected to the applied loads. The cyclic testing results confirmed a lower flexural strength of the rubberized concrete specimens. However, the specimens exhibited an ability to withstand larger plastic deformations up until the point of failure. Using the results of impact-fatigue tests, a life-cycle cost analysis was also performed, which confirmed long-term benefits of constructing green and durable infrastructure, using TDA and EC, on transportation investments. In conclusion, using these durable materials in infrastructural construction will lessen their maintenance and rehabilitation needs. Further, this application will divert waste tires from landfills.

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Executive Summary:

Monitoring the health of bridges uses various sensors and techniques and provides quantitative and reliable data on the condition of bridges. Among measurable quantities, vibration induced by traffic loads has been known as a good indicator of the condition of bridges, serviceability to pedestrians, fatigue analysis, etc. Here we use non-metric, off-the-shelf, Digital Single-Lens Reflex camera (DSLR) as a sensor and apply a photogrammetric approach to measure three bridges live load traffic vibration. We first tested our approach with shake-table equipment and showed the reliability of the  methodology we use through measuring magnitude and frequency of the shake-table, which was then applied to two highway and one local bridges. The results show that vibrational magnitudes are well within the design recommendations of the American Association of State highway Transportation (AASHTO) and that frequencies are in the range of similar bridges that previously published.  Furthermore, by providing velocity and acceleration computed from camera derived displacement, we showed that the proposed method is cost-effective and feasible as well as having a good potential for bridge health monitoring.

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Executive Summary:

This research comprised of an experimental characterization of the material properties of recycled concrete aggregate (RCA) and residual cement mortar (RCM) in RCA. The material properties of the RCA and RCM studied include RCM content, as well as specific gravity and absorption of RCA and RCM. Using 100% virgin aggregate as control hot mix asphalt (HMA) mix, this study evaluated the effects of the RCA and/or RCM properties on the performance of HMA when RCA was used to partially replace the virgin aggregate (RCA-HMA).

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Executive Summary:

• This study aims to examine whether transportation inequity exists in Fresno, which aligns with the SB 1 Objective 4 that “everyone should share the same opportunities for learning, living, labor, and leisure.”

• A GIS-based cumulate opportunity approach was developed to measure the accessibility to a variety of urban opportunities (jobs, physical activities and dining, social interactions, and public facilities) by two non-auto (green) transportation modes (public transit and cycling).

• The service area for each block group in the city was defined, using the recently completed “open street” data, in a 10-, 20-, 30-, 45-, and 60-minute travel time by transit or cycling.

• The defined service area was then used to count the number of each type of urban opportunities (jobs, restaurants, parks, multi-use paths, schools, libraries, and schools).

• The two sample t-test approach was used to compare accessibility between better- and worse-off neighborhoods, using the 25th, 50th, and 75th percentile as thresholds for a set of socioeconomic factors (income, property value, school enrollment,vehicle ownerships, race, and age). We consider that this is an innovation in this study because it creates a platform to flexibly group neighborhoods into two for comparison.

• The mapping of the accessibility points to a need to improve the efficiency of the current bus service in Fresno to be at the same level of cycling.

• The comparison results suggest that the current green (non-auto) transportation network do help with the accessibility for economically disadvantaged neighborhoods.

• This study suggests to focus on students for further study to better understand their needs because the calculated accessibility for them did not show a consistent pattern.

• The results also suggest that there is a need to put more efforts on providing multi-use paths to improve the accessibility by cycling for neighborhoods with a high share of non-white and adolescent populations.

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