Phase 2 of the project Quantifying Safety Impacts of V2X-Enabled Traffic Systems aims to advance, extend, and communicate a structured, context-sensitive framework for quantifying and visualizing the safety impacts of V2X-enabled traffic systems.
Transportation agencies and researchers struggle with fragmented, incomplete, or unavailable mobility data, making it difficult to accurately model mobility patterns and predict future transportation demand. While various datasets exist—such as GPS trajectories, public transit records, traffic sensors, and household travel surveys—they are often disconnected, limited in scope, or proprietary, preventing cities from making fully informed planning decisions. These datasets, when properly integrated, have the potential to improve urban planning, transportation optimization, and system operations. This project aims to review available mobility data sources critical for mobility pattern analysis, build a mobility data fusion pipeline by using multiple cross-domain data sources, allowing for detailed synthesis and modeling of urban and rural activities, travel behavior, demand, and trajectories, as well as estimation/generation of network-wide travel patterns. Ultimately, this project will provide a scalable, transferable data fusion framework that agencies can use for demand prediction, transportation planning, and network optimization.
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.
AV deployments are rapidly expanding across multiple urban environments, yet current AV operations and planning are often hindered by limited access to standardized, real-time municipal data. Cities produce a wide range of data that could critically inform AV routing and decision-making, including 911 call logs, real-time street closures, construction activities, and emergency response events. However, these data are rarely available in a consistent standardized format suitable for AV consumption. The Data for Autonomous Transportation Awareness (DATA) project aims to close this gap by identifying key municipal data sources, evaluating existing data standards, and developing a scalable, standardized data-sharing framework that can be integrated into AV operational systems. Through stakeholder engagement and data standards analysis, the project will enable AVs to proactively avoid potentially problematic areas (e.g., emergency incidents or active construction zones), thereby reducing conflicts with first responders, improving roadway safety, and optimizing traffic operations. Ultimately, the DATA project will foster replicability, support widespread industry adoption, and ensure that AVs can leverage city data efficiently and consistently, avoiding a fragmented “patchwork” of standards across different regions.
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 varied 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 inform future deployments by Caltrans or other cities across the U.S.
Transit accessibility remains an issue for many residents. 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.
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 identify performance metrics, risk tolerance levels, and deployment criteria that decisionmakers may consider. The framework may help local/state agencies understand and implement the good safety management practices for AV integration, balancing innovation with public welfare. Outcomes will include comprehensive policy considerations, refined safety performance metrics, and an enhanced AV safety framework tailorable 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.
Public agencies and state and local governments often impose various regulations on shared mobility services. These regulations vary widely by place and mode, and the costs and benefits of these regulations are poorly understood. This project aims to categorize shared mobility regulations, identify their intents and impacts, and to better understand the balance of regulations.
A key problem in urban mobility is determining the most effective and sustainable approach to shared mobility. This research addresses the challenge of evaluating the comparative effectiveness of community-based, market-based, and public-private partnership (P3) models in achieving urban mobility goals.
