In this paper, the performance of a vehicle information sharing (VIS) system for an intersection collision warning system (ICWS) is analyzed. The on-board unit (OBU) of the ICWS sharing obstacle detection sensor information (ICWS-ODSI) is mounted on a vehicle, and it obtains information about the surrounding vehicles, such as their position and velocity, by its in-vehicle obstacle detection sensors. These information are shared with other vehicles via an intervehicle communication network. In this analysis, a T-junction is assumed as the road environment for the theoretical analysis of the VIS performance in terms of the mean of entire vehicle information acquiring probability (MEVIAP). The MEVIAP on OBU penetration rate indicated that the ICWS-ODSI is superior to the conventional VIS system that only shares its own individual driving information via an intervehicle communication network. Furthermore, the MEVIAP on the sensing range of the ICWS-ODSI is analyzed, and it was found that the ISO15623 sensor used for the forward vehicle collision warning system becomes a candidate for the in-vehicle detection sensor of ICWS-ODSI.

This paper presents a method of predicting future human driving behavior under the condition that its resultant behavior and past observations are given. The proposed method makes use of a dynamic Bayesian network and the junction tree algorithm for probabilistic inference. The method is applied to behavior prediction for a vehicle assumed to stop at an intersection. Such a predictive system would facilitate warning and assistance to prevent dangerous activities, such as red-light violations, by allowing detection of a deviation from normal behavior.

Recently, studies and developments of Collision Warning System (CWS) have attracted widely a particular attention among various wave applications at 60 GHz frequency band. Major performance of the CWS is given by the maximum detection range, the minimum detectable width and accuracy of detection distance. Since the maximum detection range and the minimum detectable width depend on a size of a target, it is important to know Radar Cross Section (RCS) of the target. RCS data should be measured so-called far field condition (greater than a few hundreds meters), while CWS is usually used in the range of 20-100 m. Therefore, a measurement of the reflection characteristics in shorter distance should be necessarily known. In this study, we present reflection characteristics of a medium size truck and a passenger car measured in open field at 60 GHz frequency. It is concludingly described that the reflection characteristics of the passenger car and the medium size truck are 13-18 dBm2 and 15-32 dBm2, respectively, for a case of horizontal polarization.