Comparing the Benefits of Connected and Automated Vehicles to Only Automated Vehicles by Considering a Multi-Vehicle Communication System

Connected and automated vehicles (CAVs) are expected to improve both traffic efficiency and safety by reducing the human drivers’ errors. Recently, researchers have focused on the simulation-based approach to evaluate the benefits of CAVs due to the lack of real-world data. However, none of them have attempted to differentiate the benefits of CAVs over automated vehicles (AVs) by incorporating multi-vehicle communication system. This paper aims to fill the existing gap by utilizing separate car-following models for both CAVs and AVs in order to approximate their driving behavior in the Aimsun Next simulation platform. Additionally, a different car-following model is used for the connected vehicles (CVs) without automation by addressing the human driver compliance factor. A well calibrated and validated simulation testbed is developed for the deployment of CAV technologies. To this end, the impacts of CAVs, AVs, and CVs are evaluated based on both traffic efficiency (i.e., travel time) and safety (i.e., traffic conflicts) under various market penetration rates (MPRs). A generalized estimating equation (GEE) model is developed to quantify the travel time improvement for CAVs, AVs, and CVs which suggests that at the same MPR, CAV significantly outperforms AV. For the safety assessment, traffic conflicts are estimated which is further used to develop a Bayesian zero-inflated negative binomial model where results show that CAVs can reduce crash risk more compared to AVs at the same MPR. Also, crash risk analysis based on different vehicle types (CAVs, AVs) shows that CAVs driving behavior is safer compared to the AVs.

Language

  • English

Media Info

  • Media Type: Web
  • Features: Figures; References; Tables;
  • Pagination: 23p

Subject/Index Terms

Filing Info

  • Accession Number: 01764033
  • Record Type: Publication
  • Report/Paper Numbers: TRBAM-21-02902
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 23 2020 11:18AM