ORCID

0000-0002-1943-1578

Keywords

Traffic Scenarios, Conflict Analysis, Pedestrian Safety, Surrogate Safety Measures, Drone Trajectory

Abstract

This study explores key traffic safety challenges by analyzing threshold discrepancies in rear-end conflicts under different weather conditions, conflict likelihood and severity at interconnected intersections, and interaction patterns between right-turning vehicles and pedestrians at signalized intersections. First, using CitySim trajectory data, the study examines the impact of weather conditions on surrogate safety measure (SSMs) thresholds for Modified Time to Collision (MTTC), Deceleration Rate to Avoid a Crash (DRAC), and Single-step Probabilistic Driving Risk Field (S-PDRF). Results indicate that MTTC and DRAC thresholds vary significantly under clear (2.3s v.s 3.0 m/s²) and rainy (4s v.s. 2.4 m/s²) conditions, whereas S-PDRF remains unaffected, supporting a universal threshold for this measure. Second, the study evaluates conflict risks at unsignalized intersections near signalized intersections using the Joint Generalized Linear Mixed Model (JGLMM) with drone-based trajectory data. The findings reveal that angled conflicts are common in weaving areas, longer right-turn queues help reduce conflicts, while increased left-turn lane queue lengths heighten risk.

Additionally, Structural Equation Modeling (SEM) confirms that higher upstream traffic volumes can mitigate downstream risks, highlighting the importance of enhanced lane markings and pre-intersection left-turn signage. Lastly, the study investigates right-turn vehicle-pedestrian conflicts through combined crash and conflict datasets, identifying four interaction patterns and demonstrating that Relative Time-to-Collision (RTTC) outperforms Post Encroachment Time (PET) for crash prediction. The study finds RTTC thresholds of 1.5s and 3.8s for Approach and Departure crosswalks, respectively, with vehicle speeds between 5-15 mph significantly increasing conflict severity. Countermeasures such as blank-out "No Right Turn" signs and dynamic "Yield to Pedestrians" signs are proposed to enhance pedestrian safety and optimize advanced driver-assistance systems (ADAS). These findings highlight the importance of data-driven safety interventions, helping to develop adaptive safety measures for traffic management, intersection design, and automated vehicle technologies.

Completion Date

2025

Semester

Spring

Committee Chair

Abdel-Aty, Mohamed

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Civil, Environmental and Construction Engineering

Identifier

DP0029328

Document Type

Dissertation/Thesis

Campus Location

Orlando (Main) Campus

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