A Feedback-Based Dynamic Tolling Algorithm for High Occupancy Toll (HOT) Lane Operations

Dramatically increasing travel demands and insufficient traffic facility supplies have induced severe traffic congestion. High Occupancy Toll (HOT) lane operation has been proposed as one of the most applicable and acceptable countermeasures against freeway congestion. By balancing pricing and vehicle occupancy constraints, HOT lane operations can realize the optimal traffic allocation and enhance overall infrastructure efficiency. However, few previous studies have concentrated on optimal tolling strategies. Two major problems with the inferior tolling strategies degrade HOT lane system performance. First, the undersensitive tolling algorithm is incapable of handling the hysteresis properties of traffic systems and may cause severe response delays. Secondly, unfavorable flow fluctuation on HOT and GP lanes may be generated agitating traffic operations due to the over-sensitive characteristics of the imperfect tolling strategies. To address these problems, we develop a new feedback-based tolling algorithm to optimize HOT lane operations. To decompose the calculation complexity, a second-order control scheme is exploited in this algorithm. Based on traffic speed conditions and toll changing patterns, the optimum flow ratio for HOT lane utilization is calculated using feedback control theory. Then the appropriate toll rate is estimated backward using the discrete route choice model. This algorithm is simple, effective, and easy to implement. VISSIM-based simulation tests were conducted to examine its practicality and effectiveness. The test results show that the proposed tolling algorithm performed reasonably well in optimizing overall traffic operations of the HOT lane system under various traffic conditions.