Automatic Traffic Monitoring Method Based on Cellular Model

The occurrence of accidents on the freeway/highway has a significant impact on normal traffic manipulations and the reasons that cause accidents are admitted primarily due to the introduction of traffic incidents. Hence, automatic traffic monitoring system gradually attracts the attention of researchers in the field of intelligent transportation system. In this paper, a vision-based approach for automatic detection of traffic incident is proposed. Entropy-based features are extracted to create a cellular model that simulates the dynamic behavior of the traffic flow. When an unusual event happens on the vehicular lane, the system can detect it immediately and send out signals to the approaching vehicles to prevent accidents from happening. Experiments were conducted on various simulations and the results demonstrate the validity and effectiveness of the proposed approach on traffic incident detection.