Advanced Mobility and Safety Analytics Applications Using High-resolution Vehicle Trajectory Data
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Authors
Mora Campos, Ericka Maria
Issue Date
2025
Type
Dissertation
Language
en_US
Keywords
Safety Evaluation , Traffic Operations , Vehicle Trajectory Data
Alternative Title
Abstract
The increasing availability of high-resolution vehicle trajectory data has opened new ways for advancing mobility and safety analytics in transportation research. This dissertation explores the application of such data across three critical areas: traffic signal timing, complete streets design, and driver behavior at roundabouts. Each application addresses a gap in current methodologies by leveraging automated vehicle trajectory data to enhance traditional evaluation techniques.First, this research presents a method for evaluating traffic signal timing performance using vehicle trajectory data to determine the minimum number of travel runs required to evaluate its performance. Through cluster analysis and probability, the study offers an approach to balance resources demands for floating-car investigations while maintaining robust performance evaluation. The final recommendation is to perform five travel runs per direction per timing plan.
Second, the dissertation examines the effectiveness of complete streets design (CSD), which aims to provide safe access for all people in roadways and related infrastructure. This research analyzed driver speed and acceleration/deceleration behavior across three Nevada corridors with varying levels of CSD implementation, as well as deceleration rates at crosswalks for both CSD and partially implemented CSD corridors. Results indicate that both CSD and non-CSD corridors exhibited 85th percentile speeds significantly higher than the posted speed limits, and deceleration rates at partially-CSD crosswalks were significantly more aggressive than at fully-CSD crosswalks. These findings highlight the need to evaluate whether current CSD implementations are achieving their intended outcomes, especially regarding speed management and safety.
Finally, the study evaluates driver compliance and maneuvering behavior at multilane roundabouts using high-resolution trajectory data. By employing geofencing, trajectory classification, and behavior-based metrics, this work identifies distinct patterns between maneuver A, which follows road signage and markings, and maneuver B, which refers to trajectories that do not follow signage or road markings, potentially creating conflict points. Notably, maneuver type B were more frequent at approaches where single lanes transitioned into multiple lanes, creating ambiguity and increasing the likelihood of lane selection errors.
Together, these applications demonstrate the potential of high-resolution vehicle trajectory data to inform policy, optimize infrastructure, and support evidence-based design interventions aimed at safer and more efficient mobility systems.