A safety assessment of mixed fleets with Connected and Autonomous Vehicles using the Surrogate Safety Assessment Module

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Navreet Virdi - , University of New South Wales (Author)
  • Hanna Grzybowska - , University of New South Wales (Author)
  • S. Travis Waller - , University of New South Wales (Author)
  • Vinayak Dixit - , University of New South Wales, Academic in Residence IAG (Author)

Abstract

The transportation network can provide additional utility by addressing the safety concerns on roads. On-road fatalities are an unfortunate loss of life and lead to significant costs for society and the economy. Connected and Autonomous Vehicles (CAVs), envisaged as operating with idealised safety and cooperation, could be a means of mitigating these costs. This paper intends to provide insights into the safety improvements to be attained by incrementally transitioning the fleet to CAVs. This investigation is done by constructing a calibrated microsimulation environment in Vissim and deploying the custom developed Virdi CAV Control Protocol (VCCP) algorithm for CAV behaviour. The CAV behaviour is implemented using an application programming interface and a dynamic linking library. CAVs are introduced to the environment in 10% increments, and safety performance is assessed using the Surrogate Safety Assessment Module (SSAM). The results of this study show that CAVs at low penetrations result in an increase in conflicts at signalised intersections but a decrease at priority-controlled intersections. The initial 20% penetration of CAVs is accompanied by a +22%, −87%, −62% and +33% change in conflicts at the signalised, priority, roundabout and DDI intersection respectively. CAVs at high penetrations indicate a global reduction in conflicts. A 90% CAV penetration is accompanied by a −48%, −100%, −98% and −81% change in conflicts at the signalised, priority, roundabout and DDI intersection respectively.

Details

Original languageEnglish
Pages (from-to)95-111
Number of pages17
JournalAccident analysis and prevention
Volume131
Publication statusPublished - Oct 2019
Peer-reviewedYes
Externally publishedYes

External IDs

PubMed 31233998
ORCID /0000-0002-2939-2090/work/141543736

Keywords

Sustainable Development Goals

Keywords

  • Connected and Autonomous Vehicles, Microsimulation, Safety, SSAM, Surrogate Safety Assessment Module