2019
DOI: 10.1016/j.aap.2019.05.004
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A forward collision avoidance algorithm based on driver braking behavior

Abstract: Measuring risk is critical for collision avoidance. The paper aims to develop an online risk level classification algorithm for forward collision avoidance systems. Assuming risk levels are reflected by braking profiles, deceleration curves from critical evasive braking events from the Virginia "100-car" database were first extracted. The curves are then clustered into different risk levels based on spectrum clustering, using curve distance and curve changing rate as dissimilarity metrics among deceleration cu… Show more

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Cited by 64 publications
(34 citation statements)
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“…The traditional forward collision warning system predicts the potential risk based on vehicle performance data (e.g., speed, time headway, time to collision, etc.) that is continuously collected from radars or visual sensors [ 45 , 46 ]. However, the results of this study suggest that the quantitative effects of mobile phone distracted driving conditions, the driving behavior characteristics of drivers, and the LV deceleration rate should be considered for the prediction of potential risk.…”
Section: Discussionmentioning
confidence: 99%
“…The traditional forward collision warning system predicts the potential risk based on vehicle performance data (e.g., speed, time headway, time to collision, etc.) that is continuously collected from radars or visual sensors [ 45 , 46 ]. However, the results of this study suggest that the quantitative effects of mobile phone distracted driving conditions, the driving behavior characteristics of drivers, and the LV deceleration rate should be considered for the prediction of potential risk.…”
Section: Discussionmentioning
confidence: 99%
“…Before we begin our research, we propose some hypotheses: a) The measure to avoid collision is braking. Steering and braking are often used by drivers to avoid collision [28]- [31]. Considering some special circumstances, the vehicle can't turn (for example, when the front vehicle is in emergency braking, there are vehicles in the left and right lanes of the rear vehicle).…”
Section: Methodsmentioning
confidence: 99%
“…Iranmanesh et al [20] designed an adaptive FCW framework based on detecting driver distraction. Xiong et al [21] proposed an FCW algorithm based on online risk level classification. The parameters reflecting the level of risk were identified using fuzzy logic rules.…”
Section: Introductionmentioning
confidence: 99%