Dramatically increasing travel demands and insufficient traffic facility supplies have resulted in severe traffic congestion. High Occupancy Toll (HOT) lane operations have been proposed as one of the most applicable and cost-effective countermeasures against freeway congestion. By allowing Single Occupancy Vehicles (SOVs) to use High Occupancy Vehicle (HOV) lanes with a toll, excess capacities of HOV lanes can be utilized. Through balancing pricing and vehicle occupancy constraints, an HOT lane system can optimize traffic allocations between HOT and General Purpose (GP) lanes and hence enhance the overall infrastructure efficiency if a proper tolling strategy is employed. Although there exist several tolling strategies, two major problems with these tolling strategies may significantly degrade the HOT lane system performance. First, the under-sensitive tolling algorithm is incapable of handling the hysteresis properties of traffic systems and may cause severe response delays. Secondly, unfavorable flow fluctuation on both HOT and GP lanes may result from over-sensitive tolling strategies and generate agitating traffic operations. To address these problems, a new self-adaptive dynamic tolling algorithm is developed in this study to optimize HOT lane operations. To reduce the computational 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. To examine the effectiveness of the proposed tolling algorithm, simulation experiments were conducted. A microscopic traffic simulation software tool, VISSIM, is utilized. The proposed algorithm is implemented and integrated with the VISSIM package through an external module specifically developed for this study. Data from the Washington State Route (SR) 167 HOT lane system is used to build and calibrate the simulation model. The simulation experiment results show that the proposed tolling algorithm is capable of responding to traffic changes promptly and effectively. It performed reasonably well in optimizing overall traffic operations of the HOT lane system under various traffic conditions. This algorithm is logically straightforward and not difficult to implement.
Self-Adaptive Toll Rate Algorithm for High Occupancy Toll (HOT) Lane Operations
2009
85 pages
Report
Keine Angabe
Englisch
Transportation , Transportation & Traffic Planning , Road Transportation , Traffic lanes , Congestion pricing , Travel demands , Freeway congestion , Feedback , Control theory , Simulation model , Managed lanes , Single Occupancy Vehicles(SOV) , High Occupancy Vehicles(HOV) , High Occupancy Toll(HOT) , Dynamic tolling
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