Prioritizing Cyclists at Signalized Intersections Using Observations from Connected Autonomous Vehicles

Alphonse Vial*, Maria Salomons, Winnie Daamen, Bart van Arem, Sascha Hoogendoorn-Lanser, Serge Hoogendoorn

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

When making trips in urban environments, cyclists lose time as they stop and idle at signalized intersections. The main objective of this study was to show how augmenting the situational awareness of traffic signal controllers, using observations from moving sensor platforms, can enable prioritization of cyclists and reduce lost time within the control cycle in an effective way. We investigated the potential of using observations from connected autonomous vehicles (CAVs) as a source of new information, using a revised vehicle-actuated controller. This controller exploits CAV-generated observations of cyclists to optimize the control for cyclists. The results from a simulation study indicated that with a low CAV penetration rate, prioritizing cyclists by tracking reduced cyclist delays and stops, even with a small field of view. As the delay of car directions were not taken into account in this study, the average car delay increased considerably with an increasing number of cyclists. Future work is needed to optimize the control that balances the delays and stops of cyclists and cars.

Original languageEnglish
Pages (from-to)29-43
Number of pages15
JournalTransportation Research Record
Volume2677
Issue number12
DOIs
Publication statusPublished - 2023

Keywords

  • advanced traffic management systems
  • bicycles
  • connected vehicle data applications
  • data fusion
  • signalized intersection

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