Journal of Intelligent and Connected Vehicles 2019, 2(2): 67-77 https://doi.org/10.1108/JICV-06-2019-0007

Research paper |

Open Access | Issue | Published: 30 December 2019

An adaptive model predictive approach for automated vehicle control in fallback procedure based on virtual vehicle scheme

Show Author's Information Hide Author's Information Wei Xue^¹(

), Rencheng Zheng^¹, Bo Yang^¹, Zheng Wang^¹, Tsutomu Kaizuka^¹, Kimihiko Nakano^{¹^,²}

Institute of Industrial Science, The University of Tokyo, Tokyo, Japan

Interfaculty Initiative in Information Studies, The University of Tokyo, Tokyo, Japan

Keywords:

Model predictive control, Automated vehicles, Fallback, Sensor failure, Virtual vehicle scheme

Cite this article:

Xue W, Zheng R, Yang B, et al. An adaptive model predictive approach for automated vehicle control in fallback procedure based on virtual vehicle scheme. Journal of Intelligent and Connected Vehicles, 2019, 2(2): 67-77. https://doi.org/10.1108/JICV-06-2019-0007

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Abstract Full text About this article

Abstract

Purpose

Automated driving systems (ADSs) are being developed to avoid human error and improve driving safety. However, limited focus has been given to the fallback behavior of automated vehicles, which act as a fail-safe mechanism to deal with safety issues resulting from sensor failure. Therefore, this study aims to establish a fallback control approach aimed at driving an automated vehicle to a safe parking lane under perceptive sensor malfunction.

Design/methodology/approach

Owing to an undetected area resulting from a front sensor malfunction, the proposed ADS first creates virtual vehicles to replace existing vehicles in the undetected area. Afterward, the virtual vehicles are assumed to perform the most hazardous driving behavior toward the host vehicle; an adaptive model predictive control algorithm is then presented to optimize the control task during the fallback procedure, avoiding potential collisions with surrounding vehicles. This fallback approach was tested in typical cases related to car-following and lane changes.

Findings

It is confirmed that the host vehicle avoid collision with the surrounding vehicles during the fallback procedure, revealing that the proposed method is effective for the test scenarios.

Originality/value

This study presents a model for the path-planning problem regarding an automated vehicle under perceptive sensor failure, and it proposes an original path-planning approach based on virtual vehicle scheme to improve the safety of an automated vehicle during a fallback procedure. This proposal gives a different view on the fallback safety problem from the normal strategy, in which the mode is switched to manual if a driver is available or the vehicle is instantly stopped.

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About this article

An adaptive model predictive approach for automated vehicle control in fallback procedure based on virtual vehicle scheme

Show Author's information Hide Author's Information Wei Xue^¹(

), Rencheng Zheng^¹, Bo Yang^¹, Zheng Wang^¹, Tsutomu Kaizuka^¹, Kimihiko Nakano^{¹^,²}

Institute of Industrial Science, The University of Tokyo, Tokyo, Japan

Interfaculty Initiative in Information Studies, The University of Tokyo, Tokyo, Japan

Abstract

Purpose

Design/methodology/approach

Findings

It is confirmed that the host vehicle avoid collision with the surrounding vehicles during the fallback procedure, revealing that the proposed method is effective for the test scenarios.

Originality/value

Keywords: Model predictive control, Automated vehicles, Fallback, Sensor failure, Virtual vehicle scheme

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Publication history

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Publication history

Received: 08 June 2019

Revised: 24 September 2019

Accepted: 24 October 2019

Published: 30 December 2019

Issue date: December 2019

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