Mobility Data Landscape: Review, Fusion, and Synthesis for Transportation Insights

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

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.

Mobility Data Landscape: Review, Fusion, and Synthesis for Transportation Insights2025-03-04T12:28:51-08:00

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

Scalable V2X Options into the Future: A Los Angeles Case Study

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

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.

Scalable V2X Options into the Future: A Los Angeles Case Study2025-01-28T11:57:23-08:00

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

Will New Mobility Services Fill Transit Service Gaps? (Phase 1)

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

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. 

Will New Mobility Services Fill Transit Service Gaps? (Phase 1)2025-01-28T11:57:22-08:00

Modeling and Simulation Testbeds: A Sandbox for Analysis of New Mobility Deployed at Scale

2025-01-27T23:02:11-08:00

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.   

Modeling and Simulation Testbeds: A Sandbox for Analysis of New Mobility Deployed at Scale2025-01-27T23:02:11-08:00

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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