Manual Monitoring Reliability Model and Simulation of Unexpected Events along Expressway Tunnels

摘要

Manual monitoring, composed of video monitoring and manual patrolling, is one of the essential approaches for monitoring unexpected events along expressway tunnels. Detecting unexpected events along expressway tunnels in a timely manner plays a very important role in mitigating injury outcomes. In this study, the detection time and probability model of unexpected events under different monitoring situations was established. To optimize the manual monitoring model of unexpected events, the correction coefficients of the model were obtained based on the human cognitive reliability (HCR) model. Then the solution algorithm based on the Monte Carlo method was conducted. Finally, taking the actual monitoring system of the expressway extra-long tunnel in Shaanxi Province as an example, the different manual monitoring scenarios were compared. Results indicated that the probability of expressway tunnel unexpected events increases with time prolonging, time interval of patrol shortening and the inspection frequency raising. The detection time decreased effectively from 6.3 mins with one inspector to 4.2 mins with two inspectors monitoring screens separately. The expected values of detection time declined from 2.23 mins to 1.07 mins. As for the traditional manual patrolling, the detection time decreased from 165.83 mins to 26.81 mins, when the patrolling frequency was increased from 4 times per a day to 24 times per a day. The model can provide the guidance for the manual monitoring schemes and traffic safety enhancement of tunnels. This paper shows that the model plays a significant guiding role for problem solving and emergency evacuation.