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

Publikation: Beitrag zu KonferenzenPaperBeigetragenBegutachtung

Beitragende

  • Yousuf Dinar - , Technische Universität Hamburg (Autor:in)
  • M Qurashi - , Professur für Transport Modelling and Simulation (Autor:in)
  • Panagiotis Papantoniou - , University of West Attica (Autor:in)
  • C Antoniou - , Technische Universität München (Autor:in)

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.

Details

OriginalspracheEnglisch
Seitenumfang20
PublikationsstatusVeröffentlicht - März 2024
Peer-Review-StatusJa

Externe IDs

Scopus 85188988199
ORCID /0000-0002-0135-6450/work/158306062

Schlagworte

Ziele für nachhaltige Entwicklung

Schlagwörter

  • Autonomous vehicle, Connected autonomous vehicle, Sensitivity analysis, Traffic performance, traffic performance, sensitivity analysis, connected autonomous vehicle, autonomous vehicle