End-to-End Adaptive Cruise Control Based on Timing Network

Cao, Zhong; Yang, Daoguo; Jiang, Kun; Wang, Tinghan; Jiao, Xinyu; Xiao, Zhongyang

doi:10.1007/978-981-10-8506-2_56

Cited by 4 publications

(1 citation statement)

References 12 publications

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“…13216 Neural network is used to design the end-to-end controller in order to reduce the computational workload. Cao et al 13 developed an end-to-end ACC controller based on timing neural network, which was trained with big driving data in a machine learning framework. The only input of controller is camera images.…”

Section: End-to-end Controllermentioning

confidence: 99%

Researches on Adaptive Cruise Control system: A state of the art review

Wang

2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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Adaptive Cruise Control (ACC) is one of Advanced Driver Assistance Systems (ADAS) which takes over vehicle longitudinal control under necessary driving scenarios. Vehicle in ACC mode automatically adjusts speed to follow the preceding vehicle based on evaluation of the surrounding traffic. ACC reduces drivers’ workload as well as improves driving safety, energy economy, and traffic flow. This article provides a comprehensive review of the researches on ACC. Firstly, an overview of ACC controller and applied control theories are introduced. Their principles and performances are discussed. Secondly, several application cases of ACC control algorithms are presented. Then validation work including simulation, Hardware-in-the-Loop (HiL) test and on-road experiment is descripted to provide ideas for testing ACC systems for different aims and fidelities. In addition, studies on human-machine interaction are also summarized in this review to provide insights on development of ACC from the perspective of users. At last, challenges and potential directions in this field is discussed, including consideration of vehicle dynamics properties, contradiction between algorithm performance and computation as well as integration of ACC to other intelligent functions on vehicles.

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Section: End-to-end Controllermentioning

confidence: 99%