AI-Based Pedestrian Detection and Avoidance at Night Using an IR Camera, Radar, and a Video Camera

ZSB12017-SJAUXIn 2019, the United States experienced more than 6,500 pedestrian fatalities involving motor vehicles which resulted in a 67% rise in nighttime pedestrian fatalities and only a 10% rise in daytime pedestrian fatalities. In an effort to reduce fatalities, this research developed a pedestrian detection and alert system through the application of a visual camera, infrared camera, and radar sensors combined with machine learning. The research team designed the system concept to achieve a high level of accuracy in pedestrian detection and avoidance during both the day and at night to avoid potentially fatal accidents involving pedestrians crossing a street. The working prototype of pedestrian detection and collision avoidance can be installed in present day vehicles, with the visible camera used to detect pedestrians during the day and the infrared camera to detect pedestrians primarily during the night as well as at high glare from the sun during the day. The radar sensor is also used to detect the presence of a pedestrian and calculate their range and direction of motion relative to the vehicle. Through data fusion and deep learning, the ability to quickly analyze and classify a pedestrian\u2019s presence at all times in a real-time monitoring system is achieved. The system can also be extended to cyclist and animal detection and avoidance, and could be deployed in an autonomous vehicle to assist in automatic braking systems (ABS)

Understanding the Role of Transportation in Human Trafficking in California

69A3551747127Human trafficking, a form of modern slavery, is the recruitment, transport, and/or transfer of persons using force, fraud, or coercion to exploit them for acts of labor or sex. According to the International Labor Organization, human trafficking is the fastest growing organized crime with approximately $150 billion in annual profits and 40.3 million individuals trapped in slavelike conditions. While it is not compulsory to involve transportation for human trafficking, the transportation industry plays a critical role in combating human trafficking as traffickers often rely on the transportation system to recruit, move, or transfer victims. This multi-method study investigates the role of transportation in combatting human trafficking in California by conducting a survey followed up with semi-structured in-depth interviews with key stakeholders. The expert input is supplemented with labor violations and transit accessibility analysis. Experts emphasize the importance of education, training, and awareness efforts combined with partnership, data, and analysis. Screening transportation industry personnel for human trafficking is another step that the industry can take to combat this issue. Particularly, sharing perpetrator information and transportation related trends among transportation modalities and local groups could help all anti-trafficking practitioners. In addition, the transportation industry can support the victims and survivors in their exit attempts and post/exit life. Examples of this support include serving as a safe haven, and providing transportation to essential services. Transportation should ensure that all of these efforts are survivor-centric, inclusive for all types of trafficking, and tailored to the needs of the modality, population, and location

Pavement Condition Survey Using Drone Technology

ZSB12017-SJAUXTimely repairs of pavement defects are essential in protecting both public road and highway systems. Identification of pavement distresses is necessary for planning pavement repairs. This has previously been performed by engineers surveying the roadways visually in the field. As drone usage has progressed, it has become clear that drones are a valuable tool to enhance visual documentation, improve project communication, and provide various data for processing. The use of drone technology has improved both the speed and accuracy of capturing data. Available software has allowed the data to be processed and analyzed in an office environment. This report summarizes the use of drone technology for pavement evaluation for three case studies. Results from this study can be used to deepen understanding of drone use in the process of data gathering for timely repairs for transportation infrastructure

Attention-Based Data Analytic Models for Traffic Flow Predictions [Brief]

69A3551747127Traffic congestion makes Americans waste millions of hours and dollars each year. In this work, the authors analyze traffic flow data from the Caltrans Performance Measurement System (PeMS) and use deep learning algorithms to predict traffic flow accurately

The Central Valley Transportation Challenge

ZSB12017-SJAUXThe Central Valley Transportation Challenge provides underserved minority students, who are primarily from rural areas, with high quality transportation-related educational experiences so that they learn about transportation-related topics and opportunities in transportation careers. The CVTC is a project-based learning program that brings university faculty and students to K\u201312 classrooms in rural areas. The project operated with three main objectives: (1) support K\u201312 teachers\u2019 understanding and implementation of the CVTC programs; (2) connect K\u201312 students with university faculty and students, and transportation professionals through the CVTC program; and (3) develop an online hub with transportation-related lesson plans and sequences. The results of this study are reported as five case studies and a description of the online hub. The case studies illustrate how different pedagogical approaches and uses of technology were implemented and how the project connections between the schools, community members and professionals from transportation-related fields were developed. In addition, to support the sustainability of transportation-related learning across subsequent years, the research team created an online transportation resource repository. This hub was populated with lessons and units developed by pedagogical and content experts. The lessons cover the grades K\u201312 and range from brief lessons to very engaging and holistic two-week-long lesson sequences. The CVTC has proven to be a highly flexible and adaptive model due to the use of technology and the teachers\u2019 experience and pedagogical expertise. The timing of the program during the COVID-19 pandemic also provided the students that were learning from home with an engaging learning experience and some relief for teachers who were already dealing with a lot of adjustments. In that sense, the program reached traditionally underserved students, but did so in a critical time where these students faced even more obstacles

Incorporating Public Health into Transportation Decision Making

ZSB12017-SJAUXInvestments in transportation have the potential to significantly affect public health outcomes. Decisions to build highways, transit, or bikeways, for example, influence how residents and visitors move around a metropolitan area. Personal travel habits and proximity to transportation infrastructure play a role in how likely people are to be physically active or be exposed to dangerous traffic and toxic pollution. For this study, the research team reviewed the literature that links transportation infrastructure, the surrounding built environment context, and public health outcomes such as chronic heart and lung diseases, obesity, and death. The team then researched publicly available data that planners could use to inform decision-makers about the public health effects of funding certain investments. Finally, the team reviewed the guidelines of existing discretionary grant programs administered by the California Transportation Commission (CTC), and proposed improvements that would better incorporate available data on public health for consideration. These steps can positively influence funding decisionmaking for better public health outcomes in California

Large Eddy Simulations of Wind Shear From Passing Vehicles Under a Freeway Overpass

ZSB12017-SJAUXCalifornia is moving toward a 100% clean energy future, and expanded wind energy will be a major component of the state\u2019s future energy portfolio. Innovations in wind energy resources will move California closer to achieving its goal. To gain a better understanding of transient pressure and the wind shear generated at the bridge poles from passing vehicles, this study performed large-eddy simulations of a vehicle (also called an Ahmed body) moving under a freeway overpass at a distance of 0.75 w (width) from the bridge poles. Results include transient contours of mean velocity, turbulent kinetic energy, vorticity, and pressure around the vehicle and at the bridge poles at different time steps. Additionally, results indicate the vehicle\u2019s base pressure changes with time, indicating the impact of the poles' constraints on the vehicle's drag. On the bridge poles, the location of the stagnation point changes with the passing of the vehicle, and the poles experience a transient load, with the peak load associated with the passage of the vehicle's leading edge. The transient wind generated between the poles is mostly due to the vehicle\u2019s front and decreases with the passing of the vehicle. The pressure at this location oscillates between a peak positive and a peak negative, generating a force potential for possible electric power generation. This data indicates the potential of capturing vehicle-generated wind energy for electric power generation, which could help California meet its clean energy goals and mitigate the negative impacts of climate change

Electrical Vehicle Charging Infrastructure Design and Operations

ZSB12017-SJAUXCalifornia aims to achieve five million zero-emission vehicles (ZEVs) on the road by 2030 and 250,000 electrical vehicle (EV) charging stations by 2025. To reduce barriers in this process, the research team developed a simulation-based system for EV charging infrastructure design and operations. The increasing power demand due to the growing EV market requires advanced charging infrastructures and operating strategies. This study will deliver two modules in charging station design and operations, including a vehicle charging schedule and an infrastructure planning module for the solar-powered charging station. The objectives are to increase customers\u2019 satisfaction, reduce the power grid burden, and maximize the profitability of charging stations using state-of-the-art global optimization techniques, machine-learning-based solar power prediction, and model predictive control (MPC). The proposed research has broad societal impacts and significant intellectual merits. First, it meets the demand for green transportation by increasing the number of EV users and reducing the transportation sector\u2019s impacts on climate change. Second, an optimal scheduling tool enables fast charging of EVs and thus improves the mobility of passengers. Third, the designed planning tools enable an optimal design of charging stations equipped with a solar panel and battery energy storage system (BESS) to benefit nationwide transportation system development

What Do Americans Think About Federal Tax Options to Support Transportation? Results from Year Thirteen of a National Survey

69A3551747127This report summarizes the results from the thirteenth year of a national public opinion survey asking U.S. adults questions related to their views on federal transportation taxes. A nationally-representative sample of 2,620 respondents completed the online survey from January 31 to March 10, 2022

Using Thermal Remote Sensing to Quantify Impact of Traffic on Urban Heat Islands during COVID

69A3551747127A three-month lockdown in the U.S. at the beginning of the COVID-19 outbreak in 2020 greatly reduced the traffic volume in many cities, especially large metropolitan areas such as the San Francisco Bay Area. This research explores the impact of transportation on climate change by using remote sensing technology and statistical analysis during the COVID-19 lockdown. Using thermal satellite data, this research measures the intensity of the urban heat island, the main driver for climate change during the urbanization process. The research team acquired morning and afternoon MODIS data in the same periods in 2019 before the pandemic and 2020 during the pandemic. MODIS imagery provides a wall-to-wall land surface temperature map to precisely measure the dynamics of the urban heat effect. In situ meteorological data were also acquired to build an urban surface energy budget and construct statistical models between solar radiation and the intensity of heat dynamics. The team implemented this urban heat budget in six counties in Northern California. This research quantifies the impact of lockdown policies on heat intensity in urban areas and human mobility in the context of COVID-19 and future pandemics. The quantitative results obtained in this study provide critical information for analyses of climate change impact on an urban scale