An Efficient Context-Aware Vehicle Incidents Route Service Management for Intelligent Transport System

Abstract

The continuous urbanization with extensive dynamic situations on evolving cities, urban, and suburban areas, it is not feasible to categorize the navigation as fastest route, toll-free, and other variants. Metropolitan areas are more prone to traffic congestion, lane blocking, accidents, etc., due to the overcrowding and dynamic change of commuters’ arrival rates. In the metropolitan areas, most of the commuters’ use Google map to reach their desired destinations. It is quite often that route specified by navigation will not be reliable because sometimes due to the inability to update the sudden occurrence of incidents on the routes. Currently, Google map and GPS provide the time required to cover the distance and shortest route to reach the destination. The main issues with the existing Google map are it does not considers the impact of sudden occurrence of incidents, does not show the type of incidents that occurred, clearance time, and optimal routes. These issues are solved by designing an efficient context-aware vehicle incidents route service management for an intelligent transport system. The proposed system takes the context information of incidents, vehicles, weather conditions, roadside units, roads, and so on. This context information will be collected and shared with the nearby vehicles and roadside units using both mobile agents and dedicated short-range communication protocols. The proposed system suggests alternative routes with minimal delay and traffic clearance time and severity of incidents to the commuters. Also, it provides the incident information to the neighborhood vehicles, roadside units, nearby hospitals, ambulance, and members of the victims. The proposed system is exhaustively simulated in objective modular network testbed in C++, simulation of urban mobility, and Veins with different simulation parameters. The proposed system’s simulation results reduce the travel time (7 min) compared to the without the context information system (25 min), least collision rate (0.785%) compared to the existing system, minimizes the traffic clearance time in the incident zone, and uniform distribution of vehicle traffic on the estimated routes.