Title: Development of an autonomous vehicle highway merging strategy

Authors: Changwon Kim; Reza Langari

Addresses: Department of Mechanical Engineering, Texas A&M University, College Station, TX 77843-3123, USA ' Department of Mechanical Engineering, Texas A&M University, College Station, TX 77843-3123, USA

Abstract: In this paper, we propose a highway merging method to enhance vehicle autonomy in the highway travelling. The proposed decision making algorithm includes a Modified Intelligent Driver Model (MIDM) based vehicle distance adjustment and path prediction for collision avoidance. In order to maximise the safety and driving efficiency, a time optimal target is selected when the front and rear gap conditions that secure the merging safety are not satisfied. The suggested algorithm is implemented by a lane change manoeuvre and Adaptive Cruise Control (ACC) that are based on a control strategy inspired by the brain limbic system. In order to demonstrate the performance of the suggested merging strategy, the concept of Level of Service (LOS) is utilised in the simulations.

Keywords: highway merging; path prediction; MIDM; modified intelligent driver models; modelling; autonomous vehicles; decision making; distance adjustment; collision avoidance; vehicle safety; driving efficiency; lane change manoeuvres; adaptive cruise control; simulation; vehicle control; vehicle design.

DOI: 10.1504/IJVD.2012.050088

International Journal of Vehicle Design, 2012 Vol.60 No.3/4, pp.350 - 368

Received: 28 Apr 2011
Accepted: 19 Nov 2011
Published online: 23 Apr 2013 *

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