Traffic incident recovery time prediction model based on cell transmission model

Effective incident management and traffic control measurements require a full understanding of the characteristics of incidents to accurately estimate incident durations and to help make more efficient decisions to reduce the impacts of non recurring congestion due to these accidents. The Incident duration includes four parts: detection time, response time, clearance time and recovery time. Many of the research did not take the recovery time into consideration. However, recovery time can not be neglected because it often accounts for larger proportion of the duration time especially in the city freeways. This paper develops a recovery model based on CTM, which has analytical simplicity and the ability to reproduce the traffic behavioral. By comparing with the real data which is collected from elevated freeways in Shanghai city, the simulation results show that this recovery time prediction model based on CTM has a higher accuracy.