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Analysis of Traffic Flow with Mixed Manual and Semi-automated Vehicles

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  • Bose, Arnab
  • Ioannou, Petros

Abstract

During the last decade considerable research and development efforts have been devoted to automating vehicles in an effort to improve safety and efficiency of vehicle following. While dedicated highways with fully automated vehicles is a far in the future objective, the introduction of semi-automated vehicles on current highways designed to operate with manually driven vehicles is a realistic near term objective. The purpose of this paper is to analyze the effects on traffic flow characteristics and environment when semi-automated vehicles with automatic vehicle following capability (in the same lane) operate together with manually driven vehicles. We have shown that semi-automated vehicles do not contribute to the slinky effect phenomenon observed in today’s highway traffic when the lead manual vehicle performs smooth acceleration maneuvers. We have demonstrated that semi-automated vehicles smooth traffic flow by filtering the response of rapidly accelerating lead vehicles. The smooth response of the semi-automated vehicles designed for passenger comfort significantly reduces fuel consumption and levels of pollutants of following vehicles when the lead manual vehicle performs rapid acceleration maneuvers. We have demonstrated using simulations that the fuel consumption and pollution levels present in manual traffic simulated using a car following model that models the slinky effect behavior observed in manual driving can be reduced during rapid acceleration transients by 7.3% and 3.8%-47.3% respectively due to the presence of 10% semi-automated vehicles. Due to the randomness and uncertainties in human driving, the numbers obtained are qualitatively valid and demonstrate the beneficial effect of semi-automated vehicles in mixed traffic in improving air quality and fuel consumption.

Suggested Citation

  • Bose, Arnab & Ioannou, Petros, 1999. "Analysis of Traffic Flow with Mixed Manual and Semi-automated Vehicles," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt60t6z2mn, Institute of Transportation Studies, UC Berkeley.
    • Handle: RePEc:cdl:itsrrp:qt60t6z2mn
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    Cited by:

    1. Hedrick, J. K. & Sengupta, R. & Xu, Q. & Kang, Y. & Lee, C., 2003. "Enhanced AHS Safety Through the Integration of Vehicle Control and Communication," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0nm0d9dr, Institute of Transportation Studies, UC Berkeley.
    2. Diakaki, Christina & Papageorgiou, Markos & Papamichail, Ioannis & Nikolos, Ioannis, 2015. "Overview and analysis of Vehicle Automation and Communication Systems from a motorway traffic management perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 147-165.
    3. Wei, Yuguang & Avcı, Cafer & Liu, Jiangtao & Belezamo, Baloka & Aydın, Nizamettin & Li, Pengfei(Taylor) & Zhou, Xuesong, 2017. "Dynamic programming-based multi-vehicle longitudinal trajectory optimization with simplified car following models," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 102-129.
    4. Ioannou, Petros, 2003. "Evaluation of the Effects of Intelligent Cruise Control Vehicles in Mixed Traffic," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt7kp926x1, Institute of Transportation Studies, UC Berkeley.

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