@misc{das_samandar_autry_rouphail_2023, title={Surrogate Safety Measures: Review and Assessment in Real-World Mixed Traditional and Autonomous Vehicle Platoons}, volume={11}, ISSN={["2169-3536"]}, url={https://doi.org/10.1109/ACCESS.2023.3248628}, DOI={10.1109/ACCESS.2023.3248628}, abstractNote={Surrogate safety measures (SSMs) are critical tools for evaluating the safety performance of mixed traffic. Crashes are rare events, and historical crash data is scarce for mixed traffic that includes autonomous and/ or connected vehicles. Recent safety review papers focus on traditional human-driven vehicles (TVs) and do not encompass advanced technology vehicles such as Autonomous Vehicles (AVs), Connected Vehicles (CVs), and Connected-Autonomous Vehicles (CAVs). This study examines the development, implementation, and shortcomings of SSMs, and SSM-based models used for mixed traffic safety evaluation. It reviews the current relevant literature and applies a case study analysis using a real-world mixed traffic dataset. The study summarizes the fundamental SSM guiding concepts, as well as their most significant metrics including threshold values employed in the past for SSMs and SSM-based models. Primary benefits and limitations of examined SSMs and SSM-based models are also underlined. This review reveals significant gaps in the literature that might guide future research paths in SSM-based mixed traffic safety assessment. Critical gaps include the absence of robust SSM threshold selection criteria, the suitability of current SSMs in mixed traffic research, microsimulation modeling that lacks proper calibration and validation, and the absence of a framework for selecting or combining multiple SSMs.}, journal={IEEE ACCESS}, author={Das, Tanmay and Samandar, M. Shoaib and Autry, Meagan Kittle and Rouphail, Nagui M.}, year={2023}, pages={32682–32696} }
 @article{das_samandar_rouphail_2022, title={Longitudinal traffic conflict analysis of autonomous and traditional vehicle platoons in field tests via surrogate safety measures}, volume={177}, ISSN={["1879-2057"]}, DOI={10.1016/j.aap.2022.106822}, abstractNote={Autonomous vehicles (AVs) have been introduced into the traffic stream alongside traditional vehicles (TVs) with the expectation of improved transportation safety, efficiency, and reliability. The majority of AV safety research has been done through simulation. The results of such research on the safety performances of AVs are heavily influenced by the methodological framework, algorithms, and assumptions about AV driving characteristics in a simulated environment. There is a need for AV safety research based on real-world settings before any wide-scale deployment of this technology. This paper investigates the impact of the presence of SAE level 2 AVs in the traffic stream in reducing longitudinal traffic conflicts using Surrogate Safety Measures on a real-world open-source database of mixed traffic trajectories. The analysis is conducted for both AV-exclusive and mixed AV-TV platoons. Furthermore, we explore whether the presence of AVs decreases longitudinal traffic conflicts in two-vehicle platoons comprising AV and TV mixed leaders and followers. We find that an exclusive AV platoon behaves similarly to an exclusive TV platoon and produces similar longitudinal conflicts. However, mixed platoons with both AVs and TVs result in a higher number of longitudinal conflicts. Maintaining near-identical leader-follower conditions, we find that the number of conflicts in mixed platoons when an AV follows a TV is higher than when a TV follows an AV. The increase in conflict numbers in a TV-AV mixed platoon can be attributed to AV's longer response time lag. In summary, analyses conducted in this paper indicate that exclusive platoons and pairs of vehicles exhibit fewer longitudinal conflicts than mixed platoons and pairs.}, journal={ACCIDENT ANALYSIS AND PREVENTION}, author={Das, Tanmay and Samandar, M. Shoaib and Rouphail, Nagui}, year={2022}, month={Nov} }