How Do Humanlike Behaviors of Connected Autonomous Vehicles Affect Traffic Conditions in Mixed Traffic?

Yousuf Dinar (), Moeid Qurashi, Panagiotis Papantoniou and Constantinos Antoniou
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Yousuf Dinar: Institute for Transport Planning and Logistics, Hamburg University of Technology, 21073 Hamburg, Germany
Moeid Qurashi: Institute for Traffic Planning and Road Traffic, Technical University of Dresden, 01069 Dresden, Germany
Panagiotis Papantoniou: Department of Surveying and Geoinformatics Engineering, University of West Attica, 122 43 Egaleo, Greece
Constantinos Antoniou: Chair of Transportation Systems Engineering, Technical University of Munich, 80333 Munich, Germany

Sustainability, 2024, vol. 16, issue 6, 1-20

Abstract: Different methodologies are being used to study the effects of autonomous vehicles (AVs) in mixed traffic to exhibit the interactions between autonomous and human-driven vehicles (HVs). Microscopic simulation tools are popular in such an assessment, as they offer the possibility to experiment in economical, robust, and optimistic ways. A lack of reliable real-world data (also known as natural data) to calibrate and evaluate the connected autonomous vehicle (CAV) simulation model is a major challenge. To deal with this situation, one interesting methodology could be to deal with the CAVs as conventional human-driven vehicles and predict their possible characteristics based on the simulation inputs. The conventional human-driven vehicles from the real world, in this methodology, come to act as a benchmark to offer the measure of effectiveness (MoE) for the calibration and validation. For the three most common driving behaviors, a sensitivity analysis of the behaviors of AVs and an effective assessment of CAVs in a mixed traffic environment were performed to explore the humanlike behaviors of the autonomous technology. The findings show that, up to a certain point, which is directly related to the quantity of interacting vehicles, the impact of CAVs is typically favorable. This study validates the approach and supports past studies by showing that CAVs perform better than AVs in terms of their traffic performance and safety aspects. On top of that, the sensitivity analysis shows that enhancements in the technology are required to obtain the maximum advantages.

Keywords: autonomous vehicle; connected autonomous vehicle; traffic performance; sensitivity analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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