Abstract
Traffic incident detection is one of the major research areas of intelligent transportation systems (ITSs). In recent years, many mega-cities suffer from heavy traffic flow and congestion. Therefore, monitoring traffic scenarios is a challenging issue due to the nature and the characteristics of a traffic incident. Reliable detection of traffic incidents and congestions provide useful information for enhancing traffic safety and indicate the characteristics of traffic incidents, traffic violation, driving pattern, etc. This paper investigates the estimation of traffic incident from a hybrid observer (HO) method, and detects a traffic incident by using an improved automatic incident detection (AID) technique based on the lane-changing speed mechanism in the highway traffic environment. First, we developed the connection between vehicles and roadside units (RSUs) by using a beacon mechanism. Then, they will exchange information once the vehicles get access to a wireless medium. Second, we utilized the probabilistic approach to collect the traffic information data, by using a vehicle to infrastructure (V2I) communication. Third, we estimated the traffic incident by using an HO method which can provide an accurate estimation of an event occurring. Finally, in order to detect traffic incident accurately, we applied the probabilistic data collected through V2I communication based on lane-changing speed mechanism. The experimental results and analysis obtained from simulations show that the proposed method outperforms other methods in terms of obtaining a better estimation of traffic incident which agrees well with the theoretical incident, around 30% faster detection of traffic incidents and 25% faster dissipation of traffic congestion. With regard to duration of an incident, the proposed system obtained a better Kaplan–Meier (KM) curve, influenced by the shortest duration of time to clear the traffic incident, in comparison with the other methods.
Highlights
In recent years, intelligent transportation systems (ITSs) draw a great deal of attention for the researcher of wireless and communication technology background. is raises concern to the transportation authorities because of the large number of vehicles on the road causing tra c incidents, congestions, road bottlenecks, etc
Many metropolitan cities are su ering from severe tra c congestions in the urban and highway tra c environments, which are caused by the tra c incident [3]
We used the collected tra c information from the roadside units (RSUs) related to vehicle speed changing, to evaluate whether or not the incident has occurred when the vehicle changing lane speed falls in the critical region of the de ned threshold values
Summary
Intelligent transportation systems (ITSs) draw a great deal of attention for the researcher of wireless and communication technology background. is raises concern to the transportation authorities because of the large number of vehicles on the road causing tra c incidents, congestions, road bottlenecks, etc. Popescu et al [33] introduced an AID scheme, in which the lane changing distance and lane changing speed mechanisms were utilized to detect the traffic incident based on the collection of traffic-information data by using V2I communication This method required a longer time to process the traffic data in terms of vehicle lane changing distance and this scheme cannot distinguish the road bottleneck caused by a traffic incident. Ird, in order to detect traffic incident accurately, the proposed method exploits the probabilistic approach to collect the traffic information data by using V2I communication based on the lane changing speed mechanism.
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