Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Civil and Environmental Engineering

Committee Chair

Rui Ma

Committee Member

Michael D. Anderson

Committee Member

Abdullahi Salman

Committee Member

Sampson Gholston

Committee Member

Virginia Sisiopiku


Automated vehicles--Safety measures, Automated vehicles--Testing, Traffic safety


This dissertation evaluates the dynamics and conflicts between Autonomous Vehicles (AVs) and other road users, particularly focusing on the interactions at unsignalized crossings in urban settings and the implications of varying AV penetration rates on traffic performance. Utilizing a co-simulation approach which incorporates the autonomous vehicle simulator CARLA and the microscopic traffic simulation platform SUMO, this research comprehensively studied conflict scenarios at conflicting zones. Specifically, the influence of AV gap acceptance and waiting time thresholds on conflicts, such as collisions and lost time, was examined. Results showed that these thresholds significantly affect conflict performance indicators, highlighting a necessary tradeoff: designs with fewer collisions often result in higher lost times. Extending this, the study also incorporated insights from the Chicken Game Theory (CGT) to delve deeper into the decision-making, risk assessment, and cooperative strategies of AVs in relation to Surrogate Safety Measures (SSM). Our simulations successfully quantified key SSM values, like Time to Collision (TTC) and Post Encroachment Time (PET), which are pivotal in determining collision likelihoodsiii between AVs, bicycles, and other motor vehicles. For instance, an AV designed to initiate braking when reaching a TTC of 4.3 seconds or a PET of 1.7 seconds resulted in zero collisions, underscoring the effectiveness of this SSM-based strategy for AV safety. Lastly, by investigating AV penetration rates from 25% to 100% on traffic performance indicators, we identified a nuanced relationship between AV adoption and road safety and efficiency. Notably, even a 25% penetration rate significantly reduced near-miss incidents in some scenarios. However, the effect on queue length remained unchanged across all penetration levels, suggesting limitations in AV's ability to address certain congestion challenges, especially in saturated traffic systems. In summation, while AVs offer transformative potential for urban mobility, understanding their multifaceted interactions with current traffic systems is imperative. This research illuminates key areas of conflict and synergy, presenting insights for stakeholders ranging from policymakers and urban planners to technologists as we approach an era dominated by autonomous driving. Further investigations are essential to build upon these findings and fine-tune traffic systems for the future.



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