• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.44-49
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• 2013

This paper presents a lateral collision risk index between an ego vehicle and a rear-side vehicle. The lateral collision risk is designed to represent a lateral collision risk and provide the appropriate threshold value of activation of the lateral collision management system such as the Blind Spot Detection(BSD). The lateral collision risk index is designed using the Time to Line Crossing(TLC) and the longitudinal collision index at the predicted TLC. TLC and the longitudinal collision index are calculated with the signals from the exterior sensor such as the radar equipped on the rear-side of a vehicle and a vision sensor which detects the distance and time to the lane departure. For the robust situation assessment, the perception of driving environment determining whether the road is straighten or curved should be determined. The relative motion estimation method has been proposed with the road information via the integrated estimator using the environment sensors and vehicle sensor. A lateral collision risk index was composed with the estimated relative motion considering the relative yaw angle. The performance of the proposed lateral collision risk index is investigated via computer simulations conducted using the vehicle dynamics software CARSIM and Matlab/Simulink.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.1
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• pp.98-107
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• 2016

The purpose of this study is for Human error prevention to acquire Collision Risk Perception Index (CRPI) sensed by the Officer Of the Watch (OOW) when the approaching distances are reduced in six types of ship encountering situations (Head on, $045^{\circ}$, $090^{\circ}$, $135^{\circ}$, Overtaking, Overtaken) between own ship and a target ship and then to predict CRPI fitting coefficients with polynomials in the curve-fitting process. CRPI acquisition experiments are carried out on two coast-guard ships and with the total of 30 crew members. Analysing results shows that CRPI data have goodness of fit to the six types of encountering situation. Futhermore, the One-Way ANOVA results show that CRPI has a negative affect to the OOW's age, career and license grade as the approaching distances is reduced. The availability of CRPI curve fitting with 3 degrees of polynomial was testified through the RMSE as 1.19 to Head on, 0.87 to $045^{\circ}$, 0.81 to $090^{\circ}$, 0.71 to $135^{\circ}$, 1.29 to Overtaking and 0.87 to Overtaken.