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.
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.
This proposed National V2X Deployment Plan is a call to [...]
In September 2015, the U.S. Department of Transportation (USDOT) Intelligent [...]
In 2022, the Partnership for Analytics Research in Traffic Safety [...]
Cities would need to facilitate a multi-modal mobility platform, which provides travelers with a range of flexible mobility options, such as fixed-route or flex-route public transit, micro-transit, ride-sharing, car rentals, bike-sharing, scooters, and walking routes, some of which can be potentially served by automated vehicles. Those options altogether have potential to help residents reach businesses, employment, health care and other essential points of interest. 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 system efficiency, increasing ridership, reducing system cost and enhancing travel safety.
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.
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.
The successful deployment of Autonomous Vehicles (AVs) and new mobility solutions in cities like Los Angeles and Austin faces challenges due to the interplay of rapid technological change, diverse stakeholder interests, and unique local contexts. Without coordinated planning and collaboration, these efforts risk: - Fragmented deployments leading to inefficient operations, incompatible technologies, and missed opportunities to maximize benefits. - Safety and regulatory gaps where first responders, policymakers, and the public lack clear standards, certification processes, and communication protocols. - Infrastructure misalignments as AVs struggle with temporary traffic controls, construction zones, and emergency scenarios. - Limited data sharing and digital infrastructure that hinder collaboration, transparency, and interoperability across city and industry systems. - Broader urban impacts such as unforeseen consequences for land use, congestion, accessibility, public transit investment, and community acceptance. This project addresses these issues by bringing together government agencies, industry leaders, and researchers to establish shared standards, advance digital infrastructure, and develop collaborative strategies for safe, inclusive, and context-sensitive AV deployment.
