The Research calibration process is a basic condition of traffic model which uses car following behaviors for road traffic studies. The transmission channel between moving vehicles in real time traffic environment is modeled in road traffic and neighboring environment of connected vehicles adjacent to the road. The choice of input parameters used in the calibration process reflects the success of the car calibration process itself; therefore, the main goal is to choose parameters which give a large influence on the modeling process. Connectivity to the road will provide information to drivers and vehicles to enhance decision making reliability at the operational level. This e-Road project achieves the main goal to enhance safety and efficiency in intelligent transportation systems. The decision to rebroadcast the message is also affected by the situation of the receiver, such as the distance to the original sender, speed, traffic density, and the interest table of neighboring vehicles i.e. history table. To ensure connectivity in a real-time traffic environment, the relation between communication range and vehicles should be considered. This paper describes a detailed analysis of car-following input parameters and its influence on the modeled traveling time. All these findings provide a novel study of traffic flow theory and traffic simulation and used to detect intelligent traffic system. It detects the malicious behavior of various vehicles. The algorithm was implemented in C# dot net and tested under Windows system.
Volume 11 | 02-Special Issue
Pages: 2103-2110