Projects

Autonomous vehicles, both individual and shared shuttles, offer significant mobility benefit to people with disabilities and others who lack use of a personal vehicle. However, they may also exacerbate existing barriers to human-driven shared ride services, such as policy violations, rendezvous failures, and poor curb location selection. We seek to address these barriers by developing recommendations for policy decisionmakers and service providers.

The rapid advancement of autonomous vehicle (AV) technologies presents both unprecedented opportunities and significant safety challenges for local jurisdictions. Recent approvals by the California Public Utilities Commission (CPUC) for companies like Waymo to operate highly automated vehicle services in Los Angeles and San Francisco have ignited substantial public concern over safety and regulatory inconsistencies. This project proposes the development of a safety-centric, risk-based management framework to facilitate the at-scale integration of AVs into existing transportation systems while ensuring public safety is paramount. By engaging stakeholders, analyzing current policies, and collaborating with transportation authorities such as the San Francisco County Transportation Authority (SFCTA), we aim to establish clear performance metrics, risk tolerance levels, and deployment criteria. The framework will guide agencies in understanding and implementing the best safety management practices for AV integration, balancing innovation with public welfare. Outcomes will include comprehensive policy recommendations, refined safety performance metrics, and an enhanced AV safety framework tailored for local jurisdictions.

In the absence of extensive real-world data on operational strategies and new mobility solutions, including automated vehicles and emerging mobility options, the adoption of modeling and simulation testbeds emerges as a pivotal tool for evaluation at scale. However, while there is a substantial body of research on modeling and simulating new mobility solutions, much of this work remains theoretical and disconnected from the practical needs of practitioners and policymakers. There is a critical need for more applicable, robust, and validated simulation testbeds that can bridge the gap between research and real-world applications. These testbeds should be designed to meet the specific requirements of practitioners and policymakers, enabling them to evaluate new mobility solutions effectively and make informed decisions to improve accessibility, efficiency and sustainability of transportation systems.   

Cities would need to facilitate a multi-modal mobility platform, which provides travelers with seamless access to a range of emerging mobility options, such as fixed-route or flex-route public transit, micro-transit, ride-sharing, car rentals, bike-sharing, scooters, moped, and walking routes. Those options altogether have potential to improve accessibility to essential resources regarding employment, health care and food. This research acquires mobility service data to understand travel behavior in choosing mobility options, optimize design of such a platform by optimally placing mobility hubs with multiple mobility options, with the ultimate goals of improving accessibility, sustainability and efficiency for underserved populations.

Scalable Vehicle-to-Everything (V2X) solutions are essential for enhancing road safety and traffic efficiency in our communities. This project investigates scalable V2X options by considering global advancements and diverse technological ecosystems, utilizing all forms of V2X connectivity—including Cellular V2X (C-V2X), Mobile Edge Computing (MEC), and cellular networks—with Los Angeles serving as a case study. Currently, there’s no comprehensive plan to implement these advanced vehicle communication technologies. Our aim is to develop a strategic plan to deploy V2X technology in Los Angeles and Ventura Counties, improving safety, reducing traffic congestion, and preparing for major events like the 2028 Olympic Games. By engaging with various stakeholders and building a practical plan, we hope to create a reference that can guide future deployments by Caltrans or other cities across the U.S.

As autonomous vehicles (AVs) and shared mobility gain traction, there’s an urgent need to quantify their land use impacts and reassess zoning requirements. The demand for traditional auto-serving facilities like gas stations, repair shops, and car dealerships is expected to wane, while the need for new types of spaces, such as fleet servicing centers and storage, will rise. This shift also redefines the layout and size of freight logistics areas to accommodate the integration of AV technology. Understanding these dynamics is crucial for urban planners and policymakers as they adapt zoning regulations to meet the evolving needs of urban landscapes. This research aims to provide concrete data on land use changes and propose zoning adjustments that support the transition towards a future where AVs and shared mobility solutions are prevalent, ensuring cities are prepared for a sustainable and efficient transformation in urban land utilization.

Transit accessibility remains an issue for many residents, particularly in low-income and minority areas. Additionally, empty buses run during off-peak or late-night hours and in suburban areas to meet coverage requirements, often resulting in inefficient resource allocation. This project will assess the potential for new mobility services (e.g., AVs and micromobility) to fill gaps in transit service and improve operational efficiency. 

There is a significant interest in researching methods to improve V2X cost-benefit analysis (CBA) and the development of a decision support tool for deployment for different stakeholders. To develop a framework that allows the assessment of the safety and traffic impacts of V2X technology and provides actionable insights for deriving safety, reliability, and connectivity requirements.

Identifying the role and responsibilities of fleet operators in addressing safety risks of Automated Driving Systems fleets in passenger transport applications.