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

Abstract

Dramatically increasing travel demands and insufficient traffic facilities 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. With balanced 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 inferior tolling strategies degrade HOT lane system performance. First, an undersensitive tolling algorithm is incapable of handling the hysteretic properties of traffic systems and may cause severe response delays. Second, oversensitive characteristics of imperfect tolling strategies may cause unfavorable flow fluctuations in HOT and general-purpose lanes that disrupt traffic operations. A new feedback-based tolling algorithm to optimize HOT lane operations addresses these problems. To decompose the calculation complexity, a second-order control scheme is used in this algorithm. On the basis of traffic speed conditions and toll changing patterns, the optimal flow ratio for HOT lane use is calculated by using feedback control theory. The appropriate toll rate is then estimated backward by 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. 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.

Real-Time Predictive Control Strategy Optimization

“…The pricing decisions are based on real-time traffic conditions and the objective is to improve the free-flow travel service on the toll lanes while maximizing total throughput. Similar approaches -based on feedback controlhave been used to optimize for various other objectives like speed, travel time, delays, and revenues [11]- [13]. Morgul (2010) studied dynamic reactive pricing for different tolled links in a network by employing the traffic simulation software Paramics and TransModeler [14].…”

Adaptive Metering Algorithm for Electronic Commercial Vehicle Preclearance Systems

“…Ramp-metering strategies release vehicles from entry ramps using a traffic signal placed at the end of the entry ramp aiming at preventing flow breakdown [16], [17], [22]. Traffic metering also has been applied for dynamic traffic control in urban corridors, work zones, and toll plazas [18], [19], [21].…”

Real-time congestion pricing strategies for toll facilities

“…For example, Li and Govind (2002) developed a toll evaluation model to assess the optimal pricing strategies of the HOT lane that can accomplish different objectives such as ensuring a minimum speed on the HOT lane, or in the general-purpose lanes (GPL), or maximizing toll revenue. Zhang et al (2008) proposed the logit model to estimate dynamic toll rates of the HOT lane after calculating the optimal flow ratios by using feedback-based algorithm on the basis of keeping the HOT lane speed higher than 45 mph. Yin and Lou (2009) explored two approaches including feedback and self-learning methods to determine dynamic pricing strategies for the http HOT lane, and the comparative results showed that the self-learning controller is superior to the feedback controller in view of maintaining a free-flow traffic condition for managed lanes.…”