Smart Intersection Management for Connected and Automated Vehicles and Pedestrians

Connected and automated vehicles have the potential to increase both traffic safety and capacity, especially at intersection zones. In recent years, many studies about reservation-based intersection control systems that take advantage of the abilities of vehicle-to-vehicle and vehicle-to-infrastructure communication, have been published. In these studies, other road users such as pedestrians usually play a minor role or are not considered at all. However, many use cases of automated driving occur in urban environments, where vehicles share the road with pedestrians and bicyclists. This paper presents recent scientific developments about pedestrians at smart intersections and proposes various new control strategies for taking pedestrians into account in automated intersection management systems. In the developed strategies, conflicting trajectories of vehicles are resolved and turning movements of vehicles are not allowed while pedestrians are crossing the street. All control strategies are implemented and tested on a four-leg intersection using a microsimulation platform. Results show that it is possible to include pedestrians into an on-demand control while at the same time ensuring that maximum pedestrian waiting times are not exceeded. The level of service for both vehicles and pedestrians can be improved if pedestrians are detected at the intersection and reserve the intersection area they want to cross. However, the most suitable intersection control strategy in order to reduce vehicle delays and pedestrian waiting times varies according to the particular demand scenario.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: 19099773
  • Monograph Title: 2019 6th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS 2019)

Subject/Index Terms

Filing Info

  • Accession Number: 01744610
  • Record Type: Publication
  • ISBN: 9781538694855
  • Files: TRIS
  • Created Date: Jul 1 2020 9:49AM