Optimizing urban mobility: A data-driven approach to strategic Mobility Hub placement

2025-03-04T12:28:51-08:00

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.

Optimizing urban mobility: A data-driven approach to strategic Mobility Hub placement2025-03-04T12:28:51-08:00

Quantifying safety impacts of V2X-enabled traffic systems (Phase 1)

2025-02-26T10:42:08-08:00

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.

Quantifying safety impacts of V2X-enabled traffic systems (Phase 1)2025-02-26T10:42:08-08:00

Data for Autonomous Transportation Awareness (DATA)

2025-01-28T11:57:22-08:00

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.

Data for Autonomous Transportation Awareness (DATA)2025-01-28T11:57:22-08:00

Developing a Safety-Centric Framework for the Integration of Autonomous Vehicles in Local Jurisdictions

2025-01-28T11:57:23-08:00

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.

Developing a Safety-Centric Framework for the Integration of Autonomous Vehicles in Local Jurisdictions2025-01-28T11:57:23-08:00

Stakeholder Engagement Campaign with LA and Austin

2025-01-16T16:46:29-08:00

The successful integration of Autonomous Vehicles (AVs) and new mobility solutions into urban environments faces challenges due to the complex interplay of technological advancements, diverse stakeholder interests, and unique local contexts. A lack of coordinated planning and collaboration among key stakeholders can lead to: - Fragmented approaches that lead to inefficient deployments, incompatible technologies, and missed opportunities to maximize the benefits of AVs and new mobility services. - Unforeseen consequences for land use, traffic flow, social impacts, and public acceptance. - Missing opportunities to use new automated vehicles and new mobility to address critical transportation challenges and achieve broader urban development goals. This project addresses this problem by facilitating collaborative, place-based planning processes that bring together stakeholders to develop comprehensive AV and new mobility strategies tailored to the specific needs and priorities of individual cities.

Stakeholder Engagement Campaign with LA and Austin2025-01-16T16:46:29-08:00
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