Emergence of a Cognitive Car-Following Driver Model: Application to Rear-End Crashes with a Stopped Lead Vehicle

Abstract

Rear-end crashes are a major roadway safety problem, and the potential of crash countermeasures to address this has long been recognized. High-frequency or severe-consequence scenarios are focused on the general lead-vehicle-not-moving (LVNM) case and specific crash scenarios. Operating scenarios are identified, and frequencies are assessed. From these, a small number of prevalent LVNM crash scenarios are identified as the focus for subsequent model development and crash counter-measure efforts. These scenarios suggest nominal atmospheric, roadway, lighting, vehicle, and driver conditions in designing cost-effective safety features to avoid LVNM rear-end crashes. From this, emergent models for cognitive car following are developed, based on fusing current knowledge. This will serve as a foundation for further model development efforts as well as for future human-factors experiments.

Test Road Experiment on Imminent Warning Rear Lighting and Signaling

“…Task 1 also included a review of the literature regarding methods for designing visual warnings to capture attention more quickly and theory as to how these methods function. The literature review revealed that (a) RE crashes are the most frequently occurring type of crash (e.g., General Motors, 1997;Wiacek & Najm, 1999); (b) lead vehicle stopped crashes are the most common type of RE crashes (e.g., Knipling et al, 1992); (c) the majority of RE crashes occur in daylight under good weather conditions (e.g., Misener, Tsao, Song, & Steinfeld, 2000); (d) inattention, distraction, and following too closely are the most commonly cited causes of RE crashes (e.g., Knipling et al, 1992); (e) there are a multitude of ideas for enhanced rear lighting systems (e.g., Mortimer, 1969Mortimer, ,1981Mortimer, ,1997); (f) many of these ideas are similar, contain overlapping features, and Lee, and Maryanne C. DeHart, Virginia Tech Transportation Institute, Virginia Tech, Blacksburg, Virginia, and Michael Perel, National Highway Traffic Safety Administration, Washington, D.C. Objective: This paper describes an experiment directed toward refinement and initial field testing of two potential countermeasures for the problem of rear-end (RE) crashes. The countermeasures consist of "imminent warning" signals intended to direct the following driver's visual glance to the lead vehicle as it brakes rapidly to a stop and for a short time thereafter.…”

Improve driver performance by experience of driver cognitive behavior model's practice

“…In addition to theoretical advances, cognitive modeling of human behavior has emerged as a powerful technique for exploring how users interact with complex systems [10] [11], and been widely employed to model human-computer interaction and human behavior more generally [9]. For example, driver behavior modeling and cognitive tools uses for assessing driver situation awareness [12]- [14].…”

Sensor-Friendly Vehicle and Roadway Cooperative Safety Systems: Benefits Estimation

“…Misener et al (19) identified the highest-frequency LVNM crash scenarios, primarily on the basis of the National Accident Sampling System GES data for 1997. The proportion of LVNM crashes is high:10,009 LVNM crashes from a sample of 55,562 represented crashes.…”