Curve Negotiation: Identifying Driver Behavior Around Curves with the Driver Performance Database

Abstract

Summary:Approximately one quarter of all accidents outside city limits occur while driving around curves, where assistance systems could prevent the driver from negotiating curves with excessive speed. This study argues that the parameterizing of a Driving Assistant System could be realized with data from realistic, noncritical driving behavior offered by Naturalistic Driving Studies. The Driver Performance Database presented in this study provides a tool for observing normal, noncritical driving behavior. The Database contains results from road tests with an instrumented vehicle that were carried out on public road traffic on a predetermined route, which was precisely measured in advance. In addition to vehicle state parameters, we also collected data concerning the driving environment and physiological information. With the Driver Performance Database it is possible to generate different facets of human driving behavior in a descriptive and normative way, which is illustrated by driver behavior in curve negotiation.

Comparison of Anticipatory Glancing and Risk Mitigation of Novice Drivers and Exemplary Drivers when Approaching Curves

“…Over steering and under steering occur after cresting the curve. Anticipating and slowing before the curve is the optimal solution to both problems (Glennon et al, 1983;Mikolajetz, 2009). Glennon et al (1983) referred to the region three seconds before the curve as the critical region of operations.…”

“…Left curves have been cited as being less of a threat with less speed loss (Mikolajetz, et al, 2009). Right curves, longer curves and curves with smaller radii have been associated with greater crash risk (Anderson, et al, 2000;Glennon, et al, 1983).…”

Evaluation of a Training Intervention to Improve Novice Drivers’ Hazard Mitigation Behavior on Curves

“…Over steering and under steering occur after cresting the curve. Anticipating and slowing before the curve is the optimal solution to both problems (Glennon et al, 1983;Mikolajetz, 2009). Glennon et al (1983) referred to the region three seconds before the curve, as the critical region of speed selection.…”

“…There were two curve types that were of prime interest in the current effort, and were examined. Left curves have been cited as being less of a threat with less speed loss (Mikolajetz, et al, 2009). Right curves, longer curves and curves with smaller radii have been associated with greater crash risk (Anderson, et al, 2000).…”

Vehicle Dynamics Prediction Based on State Observers Entries Anticipation

“…While in Glaser et al (2007), a similar system is proposed taking into account the vehicle dynamics (bicycle model) and the driver behavior (under the form of a coefficient that expresses the value of acceleration the driver is up to accept). Nevertheless, there are also techniques based on knowledge extraction from databases like Mikolajetz et al (2005), which argues that the parameterizing of such ADAS could be realized with data from realistic, non-critical driving behavior, and Rey and Fogli (2009), where measures are obtained from a "watched" roadway path for modeling human attitudes. However, it seems to be an disadvantage because road monitoring could be expensive and impracticable.…”