%0 Journal Article
%T Predicting Driver Behavior Using Field Experiment Data and Driving Simulator Experiment Data: Assessing Impact of Elimination of Stop Regulation at Railway Crossings
%A Toshihisa Sato
%A Motoyuki Akamatsu
%A Toru Shibata
%A Shingo Matsumoto
%A Naoki Hatakeyama
%A Kazunori Hayama
%J International Journal of Vehicular Technology
%D 2013
%I Hindawi Publishing Corporation
%R 10.1155/2013/912860
%X We investigated the impact of deregulating the presence of stop signs at railway crossings on car driver behavior. We estimated the probability that a driver would stop inside the crossing, thereby obstructing the tracks, when a lead vehicle suddenly stopped after the crossing and a stop regulation was eliminated. We proposed a new assessment method of the driving behavior as follows: first, collecting driving behavior data in a driving simulator and in a real road environment; then, predicting the probability based on the collected data. In the simulator experiment, we measured the distances between a lead vehicle and the driver¡¯s vehicle and the driver¡¯s response time to the deceleration of the leading vehicle when entering the railway crossing. We investigated the influence of the presence of two leading vehicles on the driver¡¯s vehicle movements. The deceleration data were recorded in the field experiments. Slower driving speed led to a higher probability of stopping inside the railway crossing. The probability was higher when the vehicle in front of the leading vehicle did not slow down than when both the lead vehicle and the vehicle in front of it slowed down. Finally, advantages of our new assessment method were discussed. 1. Introduction Driving simulators have been used to evaluate driver behaviors and the influences of advanced driver assistance systems on the driving behaviors. The simulators are an essential tool in automotive human factors research. Advantages of using the driving simulator are a safety (no traffic accidents during the driving experiments), an easy collection of the driver behavior data, and a precise reproduction of road traffic environments within and between the drivers. The driving simulator has contributed to collecting driving behavior data under situations with potential risks for a traffic accident (e.g., situations where pedestrians or bicycles suddenly rush out in front of the driver¡¯s vehicle). The data collection and an assessment of the driver behavior when avoiding the incidents have led to developing advanced driver assistance systems and warning systems for reducing these accidents. However, the experiments under the risky conditions using the simulators have mainly two disadvantages: (1) a driving simulator cannot fully reproduce the driver behavior on a real road, and (2) once a driver experiences a target situation, he/she becomes cautious about similar situations and the behavior data under the same target situation and/or the other risky situations with different traffic conditions will never be
%U http://www.hindawi.com/journals/ijvt/2013/912860/