Design, specification, implementation and evaluation of a freeway queue warning system

Zhejun Liu, Peter Dirks, John Hourdos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The formation and propagation of queues on urban freeways is an unavoidable result of the ever-increasing traffic demand. This paper presents the design, specification, implementation and evaluation of an infrastructure based Queue Warning system (QWARN) that is capable of detecting dangerous traffic conditions, i.e. crash-prone conditions, on freeways and delivering warning messages to drivers, in order to increase their alertness to these traffic conditions and ultimately reduce the crash frequency on urban freeways. This study utilizes measurements of individual vehicle speeds and time headways at two fixed locations on the freeway mainline. The Queue Warning system was implemented at the right lane of a 1.7-mile-long freeway segment of Interstate 94 WB where the event frequency prior to the systems installation was 11.9 crashes per million vehicles traveled and 111.8 near crashes per million vehicles traveled. The control algorithm assesses the dangerousness of the given traffic condition and responds with a warning result based on a multi-metrics traffic evaluation model. The system translates the warning result into readable messages and delivers them to the two sets of signs located upstream of the detection zone. A three-month investigation of the operations of the QWARN system showed the event frequency reduced to 9.34 crashes per million vehicle traveled and 51.8 near crashes per million vehicle traveled. The result shows a 20% decrease of crash frequency and the feasibility of the proposed methodology.

Original languageEnglish (US)
Title of host publication5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages762-767
Number of pages6
ISBN (Electronic)9781509064847
DOIs
StatePublished - Aug 8 2017
Event5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Naples, Italy
Duration: Jun 26 2017Jun 28 2017

Publication series

Name5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings

Other

Other5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017
CountryItaly
CityNaples
Period6/26/176/28/17

Keywords

  • Active Traffic Management
  • Queue Warning

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