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A self-adaptive toll rate algorithm for high occupancy toll (HOT) lane operations.
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    Final report.
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  • Abstract:
    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.

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