• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.5
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• pp.71-82
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• 2016

Information System for rear-end collision avoidance is a unit service of C-ITS pilot project. Road environment that the number of vehicles at the same driving high-speed has a possibility that the communication delay or failure caused by heavy load of vehicle to vehicle communication. In this study, effects of the road network about a communication failure rate of information system for rear-end collision avoidance was analyzed quantitatively with micro traffic simulation. The simulation was carried out in situation that crash of two vehicles are occurred at merging area with speed limit 80km/h and information of collision is prvoided to the rear vehicle. From simulation results, it can confirm the trend of the increasing 14% of potential conflict according to 10% increasing of the communication failure rate. C-ITS service has a goal of increasing safety. The coommunication failure rate increases due to heavy load of vehicle causes a fatal result in road safety administrator position. For the success of C-ITS project, a communication system developers side should perform the effort to reduce the communication failure rate.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.126-141
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• 2019

One of the Cooperative Intelligent Transportation System(C-ITS) priority services is collision prevention support service. Several studies have considered V2I2V communication-based collision prevention support services using Artificial Neural Networks(ANN). However, such services still show some issues due to a low penetration of C-ITS devices and large delay, particularly when loading massive traffic data into the server in the C-ITS center. This study proposes the Artificial Neural Network-based Collision Warning Service(ACWS), which allows upstream vehicle to update pre-determined weights involved in the ANN by using real-time sectional traffic information. This research evaluates the proposed service with respect to various penetration rates and delays. The evaluation result shows the performance of the ACWS increases as the penetration rate of the C-ITS devices in the vehicles increases or the delay decreases. Furthermore, it reveals a better performance is observed in more advanced ANN model-based ACWS for any given set of conditions.