Identification of Visual Cues and Quantification of Drivers' Perception of Proximity Risk to the Lead Vehicle in Car-Following Situations

Abstract

Longitudinal vehicle control and/or warning technologies that operate in accordance with drivers' subjective perception of risk need to be developed for driver-support systems, if such systems are to be used fully to achieve safer, more comfortable driving. In order to accomplish this goal, it is necessary to identify the visual cues utilized by drivers in their perception of risk when closing on the vehicle ahead in a car-following situation. It is also necessary to quantify the relation between the physical parameters defining the spatial relationship to the vehicle ahead and psychological metrics with regard to the risk perceived by the driver. This paper presents the results of an empirical study on quantification and formulization of drivers' subjective perception of risk based on experiments performed with a fixed-base driving simulator at the Nissan Research Center. Experiments were carried out to investigate the subjective perception of risk relative to the headway distance and closing velocity to the vehicle ahead using the magnitude estimation method. The experimental results showed that drivers' perception of risk was strongly affected by two variables: time headway, i.e., the distance to the lead vehicle divided by the following vehicle's velocity, and time to collision, i.e., the distance to the lead vehicle divided by relative velocity. It was also found that an equation for estimating drivers' perception of risk can be formulated as the summation of the time headway inverse and the time to collision inverse and that this expression can be applied to various approaching situations. Furthermore, the validity of this equation was examined based on real-world driver behavior data measured with an instrumented vehicle.

A farewell to brake reaction times? Kinematics-dependent brake response in naturalistic rear-end emergencies

“…Inverse tau is a visually available estimate of inverse TTC (Lee, 1976), and thus increases as the potential collision draws nearer. Furthermore, it has often been suggested that inverse tau and similar quantities play an important role in determining drivers' responses to obstacles and collision threats (Lee, 1976;Kiefer et al, 2003Kiefer et al, , 2005Fajen, 2005Fajen, , 2008Kondoh et al, 2008Kondoh et al, , 2014Jurecki & Stanczyk, 2009, 2014.…”

Temporal fluctuations in driving demand: The effect of traffic complexity on subjective measures of workload and driving performance

“…Research has shown that headway from the lead vehicle (Green, 2004), time to collision (Kondoh et al, 2007;Wada et al, 2010), and variation of speed (Cacciabue, 2007) are key factors examined for primary task demand relating to traffic. Although the aim of the study is to explore driver's temporal workload in response to changes in immediate traffic, understanding possible adaptation in driving behaviour may provide clarification of changes in driver workload and thus verify the utility of subjective measures in quantifying these external demands.…”

Driver Involvement in Lane-Change Decision Making for Maintaining Situation Awareness during Automated Driving

“…(1) Fixed-threshold: The automated driving system performs a lane change if the value of "Risk Perception" [12] is less than the fixed-threshold, where Risk Perception is a linear combination of inverse TTC (time to collision) and inverse THW (time headway). It is known that the value of Risk Perception is strongly related to the human's feeling of risk on rear-end collision [12].…”

“…It is known that the value of Risk Perception is strongly related to the human's feeling of risk on rear-end collision [12]. The threshold value is set at 1.35 in this experiment.…”