Vehicle Position Awareness in Roadside-to-Vehicle Communication

The roadside-to-vehicle communication system is an infrastructure network to be deployed along the roads, which is an important part of the vehicular Ad Hoc networks for future intelligent transportation systems. Vehicle position estimation is a key technology for roadside-to-vehicle communication. In this study, a roadside-to-vehicle communication system is proposed where a camera is fixed on the roadside infrastructure for taking snapshoot of the target vehicle. Then target detecting and pixels counting is performed through certain image processing technology. After that, the function relationship between the vehicular pixels and the distance between the vehicle and the infrastructure is obtained by using the machine learning method, whose training data comes from our field trial. The vehicle position information acquired will be used for the parameters selection of OFDM transmission. The simulation results show that in the vehicular wireless fading channel model, the roadside-to-vehicle system which has position awareness can effectively implement adaptive modulation and coding scheme and, thereby, achieve greater throughput over a fixed modulation and coding scheme.