Applied Sciences (Jan 2022)

Adaptive Cruise Control with Look-Ahead Anticipation for Driving on Freeways

  • Md Abdus Samad Kamal,
  • Kotaro Hashikura,
  • Tomohisa Hayakawa,
  • Kou Yamada,
  • Jun-ichi Imura

DOI
https://doi.org/10.3390/app12020929
Journal volume & issue
Vol. 12, no. 2
p. 929

Abstract

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This paper presents Adaptive Cruise Control (ACC) with look-ahead anticipation, based on the model of ACC used in recent commercial vehicles, to take early decisions in driving a vehicle on the freeway. The existing ACC found in the high-end cars has limited operating range as it often fails to respond smoothly in advance behind a decelerating vehicle. Although advanced techniques, such as model predictive control (MPC), can significantly improve a vehicle’s driving performance, they are associated with high computational complexity and have limited scopes for practical implementation. The proposed look-ahead anticipatory scheme of ACC predicts the relative states of the preceding vehicle using a conditional persistence prediction technique in an adaptive short horizon. With negligible computation cost, it determines the control input using parametric functions prudently for improving driving performance. The proposed scheme is evaluated on multiple vehicles in typical traffic scenarios to examine individual driving behavior and the stability of a vehicle string. Finally, we investigate the influences of a small part of vehicles with the proposed ACC on overall traffic using the AIMSUN traffic simulator and compare performances of overall traffic.

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