2011•IET Intelligent Transport SystemsRequires access

Traffic control and intelligent vehicle highway systems: a survey

Lakshmi Dhevi Baskar, Bart De Schutter, J. Hellendoorn, Z. Papp

Open publisher page 183 citations

Abstract

Traffic congestion in highway networks is one of the main issues to be addressed by today's traffic management schemes. Automation combined with the increasing market penetration of on-line communication, navigation and advanced driver assistance systems will ultimately result in intelligent vehicle highway systems (IVHS) that distribute intelligence between roadside infrastructure and vehicles and that - in particular on the longer term - are one of the most promising solutions to the traffic congestion problem. In this study, the authors present a survey on traffic management and control frameworks for IVHS. First, they give a short overview of the main currently used traffic control methods for freeways. Next, they discuss IVHS-based traffic control measures. Then, various traffic management architectures for IVHS such as PATH, Dolphin, Auto21 CDS etc. are discussed and a comparison of the various frameworks is presented. Finally, the authors sketch how existing traffic control methodologies could fit in an IVHS-based traffic control set-up. © 2011 The Institution of Engineering and Technology.

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Traffic congestion in highway networks is one of the main issues to be addressed by today's traffic management schemes. Automation combined with the increasing market penetration of on-line communication, navigation and advanced driver assistance systems will ultimately result in intelligent vehicle highway systems (IVHS) that distribute intelligence between roadside infrastructure and vehicles and that - in particular on the longer term - are one of the most promising solutions to the traffic congestion problem. In this study, the authors present a survey on traffic management and control frameworks for IVHS. First, they give a short overview of the main currently used traffic control methods for freeways. Next, they discuss IVHS-based traffic control measures. Then, various traffic management architectures for IVHS such as PATH, Dolphin, Auto21 CDS etc. are discussed and a comparison of the various frameworks is presented. Finally, the authors sketch how existing traffic control methodologies could fit in an IVHS-based traffic control set-up. © 2011 The Institution of Engineering and Technology.

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Available abstract

Traffic congestion in highway networks is one of the main issues to be addressed by today's traffic management schemes. Automation combined with the increasing market penetration of on-line communication, navigation and advanced driver assistance systems will ultimately result in intelligent vehicle highway systems (IVHS) that distribute intelligence between roadside infrastructure and vehicles and that - in particular on the longer term - are one of the most promising solutions to the traffic congestion problem. In this study, the authors present a survey on traffic management and control frameworks for IVHS. First, they give a short overview of the main currently used traffic control methods for freeways. Next, they discuss IVHS-based traffic control measures. Then, various traffic management architectures for IVHS such as PATH, Dolphin, Auto21 CDS etc. are discussed and a comparison of the various frameworks is presented. Finally, the authors sketch how existing traffic control methodologies could fit in an IVHS-based traffic control set-up. © 2011 The Institution of Engineering and Technology.

Key concepts: Transport engineering, Intelligent transportation system, Control (management), Computer science, Highway system, Vehicle Information and Communication System, Automotive engineering, Engineering

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