A Pareto‐improving hybrid policy for transportation networks

This paper investigates an innovative Pareto‐improving hybrid policy that combines two policy instruments, that is, congestion pricing and road space rationing, and takes advantage of the synergistic effects between these instruments. Mathematical formulations for developing Pareto‐improving pure road space rationing schemes and hybrid policies are presented. Numerical examples demonstrate that the proposed hybrid policy offers greater flexibility and is more prominent in leading to Pareto improvement than both pure congestion pricing and road space rationing schemes. Copyright © 2013 John Wiley & Sons, Ltd.     

Pricing scheme design of ridesharing program in morning commute problem

This paper examines the dynamic user equilibrium of the morning commute problem in the presence of ridesharing program. Commuters simultaneously choose departure time from home and commute mode among three roles: solo driver, ridesharing driver, and ridesharing rider. Considering the congestion evolution over time, we propose a time-varying compensation scheme to maintain a positive ridesharing ridership at user equilibrium. To match the demand and the supply of ridesharing service over time, the compensation scheme should be set according to the inconvenience cost functions and the out-of-pocket cost functions. When the price charged per time unit is higher than the inconvenience cost per time unit perceived by the ridesharing drivers, the ridesharing participants will travel at the center of peak hours and solo drivers will commute at the two tails. Within the feasible region with positive ridership, the ridesharing program can reduce the congestion and all the commuters will be better off. To support system optimum (SO), we derive a time-varying toll combined with a flat ridesharing price from eliminating queuing delay. Under SO toll, the ridesharing program can attract more participants and have an enlarged feasible region. This reveals that the commuters are more tolerant to the inconvenience caused by sharing a ride at SO because of the lower travel time. Compared with no-toll equilibrium, both overall congestion and individual travel cost are further reduced at SO.     

Improving travel efficiency by parking permits distribution and trading

In this paper, we study various parking management schemes in a many-to-one network, where each origin is connected to the destination by a highway with a bottleneck and a parallel transit line. First, we derive a model to compute the morning commuting pattern when the destination has inadequate parking space to accommodate potential private cars. Second, we propose and compare the following three schemes of distributing parking permits to commuters residing in different origins: uniform, Pareto improving, and system optimum distribution of parking permits. Third, free trading of parking permits among commuters in a free market is introduced to better cater for commuters’ parking needs. Numerical examples show that parking permits distribution and trading are very efficient in traffic management.     

Toll pricing framework under logit‐based stochastic user equilibrium constraints

This paper addresses the toll pricing framework for the first‐best pricing with logit‐based stochastic user equilibrium (SUE) constraints. The first‐best pricing is usually known as marginal‐cost toll, which can be obtained by solving a traffic assignment problem based on the marginal cost functions. The marginal‐cost toll, however, has rarely been implemented in practice, because it requires every specific link on the network to be charged. Thus, it is necessary to search for a substitute of the marginal cost pricing scheme, which can reduce the toll locations but still minimize the total travel time. The toll pricing framework is the set of all the substitute toll patterns of the marginal cost pricing. Assuming the users' route choice behavior following the logit‐based SUE principle, this paper has first derived a mathematical expression for the toll pricing framework. Then, by proposing an origin‐based variational inequality model for the logit‐based SUE problem, another toll pricing framework is built, which avoids path enumeration/storage. Finally, the numerical test shows that many alternative pricing patterns can inherently reduce the charging locations and total toll collected, while achieving the same equilibrium link flow pattern. Copyright © 2013 John Wiley & Sons, Ltd.     

Park and ride facilities on light rail transit systems

There is now considerable interest in exploring the idea of strategic park and ride as a means of promoting the use of rail transit and encouraging a transfer of commuters from car to public transport. This is especially evident in North America, where extensive park and ride facilities have been installed on a number of light and heavy urban rail systems. There is a general consensus about the most suitable types of location for facilities, but less agreement on the development of a reliable method of forecasting demand and also on the required size of sites. Experience in practice indicates that although park and ride is attractive to commuters, schemes do not generally result in lasting reductions in highway congestion, due to rising car ownership and use and the phenomenon of generated traffic.Abbreviations Centro West Midlands Passenger Transport Executive - K&R Kiss and ride - LRT Light Rail Transit - PT Public Transport - RT Rapid Transit - TRRL Transport & Road Research Laboratory, UK     

Improved modeling of park‐and‐ride transfer time: Capturing the within‐day dynamics

An important factor that affects park‐and‐ride demand is transfer time. However, conventional park‐and‐ride demand models treat transfer time as a single value, without considering the time‐of‐day effect. Since early comers usually occupy spots closer to the entrance, their transfer times are shorter. Hence, there is a relationship between arrival time and transfer time. To analyze this relationship, a micro‐simulation model is developed. The model simulates the queuing system at the entrance and the pattern that parking spots are occupied in the parking lot over time. As expected, the model output illustrates an increasing relationship between arrival time and transfer time. This relationship has significant implication in mode choice models because it means that the attractiveness of park‐and‐ride depends on the time of arrival at the park‐and‐ride lot. This model of park‐and‐ride transfer time can potentially improve travel demand forecasting, as well as facilitate the operation and design of park‐and‐ride facilities.     

Existence of self-financing and Pareto-improving congestion pricing: Impact of value of time distribution

This paper considers a static congestion pricing model in which travelers select a mode from either, driving on highway or taking public transit, to minimize a combination of travel time, operating cost and toll. The focus is to examine how travelers’ value of time (VOT), which is continuously distributed in a population, affects the existence of a pricing-refunding scheme that is both self-financing (i.e. requiring no external subsidy) and Pareto-improving (i.e. reducing system travel time while making nobody worse off). A condition that insures the existence of a self-financing and Pareto-improving (SFPI) toll scheme is derived. Our derivation reveals that the toll authority can select a proper SFPI scheme to distribute the benefits from congestion pricing through a credit-based pricing scheme. Under mild assumptions, we prove that an SFPI toll always exists for concave VOT functions, of which the linear function corresponding to the uniform distribution is a special case. Existence conditions are also established for a class of rational functions. These results can be used to analyze more realistic VOT distributions such as log-normal distribution. A useful implication of our analysis is that the existence of an SFPI scheme is not guaranteed for general functional forms. Thus, external subsidies may be required to ensure Pareto-improving, even if policy-makers are willing to return all toll revenues to road users.     

Managing bottleneck congestion with tradable credits

We demonstrate the efficiency and effectiveness of a tradable credit system in managing the morning commute congestion with identical and nonidentical commuters. The credit system consists of a time-varying credit charged at the bottleneck and an initial credit distribution to the commuters, where the credits are universal in terms of time. Credits are tradable between the commuters and the credit price is determined by a competitive market. Under the assumption that late-arrival is not allowed, we prove that an optimal credit charging scheme, which completely eliminates the bottleneck queue, always exists despite how commuters vary in their value-of-time (VOT). The optimal charge rate is strictly increasing and convex with time, which therefore drives the commuters to depart in the increasing order of their VOT. The optimal credit charging scheme is pareto-improving, but may cause undesirable welfare distribution among the commuters. Our study shows that a combination of an initial credit distribution and an optimal credit charging scheme can simultaneously achieve system optimum and certain forms of equality (e.g., “numerical” or “proportional” equality), and that the commuters in the middle VOT bracket will receive the most credits under the proportionally equitable credit distribution.     

Design of income-equitable toll prices for high occupancy toll lanes in a single toll facility

Income inequity potentially exists under high occupancy toll (HOT) lanes whereby higher-income travelers may reap the benefits of the facility. An income-based multi-toll pricing approach is proposed for a single HOT lane facility in a network to maximize simultaneously the toll revenue and address the income equity concern, while ensuring a minimum level-of-service on the HOT lanes and that the toll prices do not exceed pre-specified thresholds. The problem is modeled as a bi-level optimization formulation. The upper level model maximizes revenue for the tolling authority subject to pre-specified upper bounds on tolls. The lower level model solves the stochastic user equilibrium problem. An agent-based solution approach is used to determine the toll prices by considering the tolling authority and commuters as agents. Results from numerical experiments indicate that a multi-toll pricing scheme is more equitable and can yield higher revenues compared to a single toll price scheme across travelers.     

Drivers’ willingness-to-pay to reduce travel time: evidence from the San Diego I-15 congestion pricing project

The adoption of congestion pricing depends fundamentally upon drivers’ willingness to pay to reduce travel time during the congested morning peak period. Using revealed preference data from a congestion pricing demonstration project in San Diego, we estimate that willingness to pay to reduce congested travel time is higher than previous stated preference results. Our estimate of median willingness to pay to reduce commute time is roughly $30 per hour, although this may be biased upward by drivers’ perception that the toll facility provides safer driving conditions. Drivers also use the posted toll as an indicator of abnormal congestion and increase their usage of the toll facility when tolls are higher than normal.     

Welfare effects of congestion pricing in Singapore

This paper examines the Singapore Area License Scheme. Changes in scheduling and choices of transportation mode by commuters are discussed. Although the toll is shown to reduce travel times for many commuters, many commuters are shown to incur scheduling costs as a result of the toll. Using estimated parameters of an indirect utility function, welfare functions are computed to compare welfare levels prior to, and just after, the toll was put into place. The evidence suggests that the toll may have reduced welfare.     

Time-dependent area-based pricing for multimodal systems with heterogeneous users in an agent-based environment

In this paper, we investigate an area-based pricing scheme for congested multimodal urban networks with the consideration of user heterogeneity. We propose a time-dependent pricing scheme where the tolls are iteratively adjusted through a Proportional–Integral type feedback controller, based on the level of vehicular traffic congestion and traveler’s behavioral adaptation to the cost of pricing. The level of congestion is described at the network level by a Macroscopic Fundamental Diagram, which has been recently applied to develop network-level traffic management strategies. Within this dynamic congestion pricing scheme, we differentiate two groups of users with respect to their value-of-time (which related to income levels). We then integrate incentives, such as improving public transport services or return part of the toll to some users, to motivate mode shift and increase the efficiency of pricing and to attain equitable savings for all users. A case study of a medium size network is carried out using an agent-based simulator. The developed pricing scheme demonstrates high efficiency in congestion reduction. Comparing to pricing schemes that utilize similar control mechanisms in literature which do not treat the adaptivity of users, the proposed pricing scheme shows higher flexibility in toll adjustment and a smooth behavioral stabilization in long-term operation. Significant differences in behavioral responses are found between the two user groups, highlighting the importance of equity treatment in the design of congestion pricing schemes. By integrating incentive programs for public transport using the collected toll revenue, more efficient pricing strategies can be developed where savings in travel time outweigh the cost of pricing, achieving substantial welfare gain.     

Joint road toll pricing and capacity development in discrete transport network design problem

The paper demonstrates a method to determine road network improvements that also involve the use of a road toll charge, taking the perspective of the government or authority. A general discrete network design problem with a road toll pricing scheme, to minimize the total travel time under a budget constraint, is proposed. This approach is taken in order to determine the appropriate level of road toll pricing whilst simultaneously addressing the need for capacity. The proposed approach is formulated as a bi-level programming problem. The optimal road capacity improvement and toll level scheme is investigated with respect to the available budget levels and toll revenues.     

Congestion pricing and roadspace rationing: an application to the San Francisco Bay Bridge corridor

This paper presents an empirical application of a congestion–alleviation strategy that C. Daganzo [Transportation Research B 29 (1995) 139–154] proposed as a “hybrid between rationing and pricing”. This strategy is applied to the San Francisco Bay Bridge corridor, in search of a practical and Pareto-improving solution to the Bridge's congestion. The work relies on a mode-split model for work trips across four different income groups residing in 459 origin zones, and it applies an equilibrium analysis based on Bridge performance. Results indicate that modal utilities (and thus choices) are sensitive to the specific combination of toll and rationing rate, as well as to the Bridge's travel-time (or performance) function, and the length of the congested section. Though no combination of tolls plus rationing rates was found to benefit all groups of travelers studied, further investigations may improve upon these results by refining some of the assumptions made here.     

A novel permit scheme for managing parking competition and bottleneck congestion

Morning commuters may have to depart from home earlier to secure a parking space when parking supply in the city center is insufficient. Recent studies show that parking reservations can reduce highway congestion and deadweight loss of parking competition simultaneously. This study develops a novel tradable parking permit scheme to realize or implement parking reservations when commuters are either homogeneous or heterogeneous in their values of time. It is found that an expirable parking permit scheme with an infinite number of steps, i.e., the ideal-scheme, is superior to a time-varying pricing scheme in the sense that designing a permit scheme does not require commuters’ value of time information and the performance of the scheme is robust to the variation of commuters’ value of time. Although it is impractical to implement the ideal-scheme with an infinite number of steps, the efficiency loss of a permit scheme with finite steps can be bounded in both cases of homogeneous and heterogeneous commuters. Moreover, considering the permit scheme may lead to an undesirable benefit distribution among commuters, we propose an equal cost-reduction distribution of parking permits where auto commuters with higher value of time will receive fewer permits.     

Expirable parking reservations for managing morning commute with parking space constraints

When total parking supply in an urban downtown area is insufficient, morning commuters would choose their departure times not only to trade off bottleneck congestion and schedule delays, but also to secure a parking space. Recent studies found that an appropriate combination of reserved and unreserved parking spaces can spread the departures of those morning commuters and hence reduce their total travel cost. To further mitigate both traffic congestion and social cost from competition for parking, this study considers a parking reservation scheme with expiration times, where commuters with a parking reservation have to arrive at parking spaces for the reservation before a predetermined expiration time. We first show that if all parking reservations have the same expiration time, it is socially preferable to set the reservations to be non-expirable, i.e., without expiration time. However, if differentiated expiration times are properly designed, the total travel cost can be further reduced as compared with the reservation scheme without expiration time, since the peak will be further smoothed out. We explore socially desirable equilibrium flow patterns under the parking reservation scheme with differentiated expiration times. Finally, efficiencies of the reservation schemes are examined.     

The evening commute with cars and transit: Duality results and user equilibrium for the combined morning and evening peaks

This paper extends Vickrey’s (1969) commute problem for commuters wishing to pass a bottleneck for both cars and transit that share finite road capacity. In addition to this more general framework considering two modes, the paper focuses on the evening rush, when commuters travel from work to home. Commuters choose which mode to use and when to travel in order to minimize the generalized cost of their own trips, including queueing delay and penalties for deviation from a preferred schedule of arrival and departure to and from work. The user equilibrium for the isolated morning and evening commutes are shown to be asymmetric because the schedule penalty in the morning is the difference between the departure and wished curves, and the schedule penalty in the evening is the difference between the arrival and wished curves. It is shown that the system optimum in the morning and evening peaks are symmetric because queueing delay is eliminated and the optimal arrival curves are the same as the departure curves.The paper then considers both the morning and evening peaks together for a single mode bottleneck (all cars) with identical travelers that share the same wished times. For a schedule penalty function of the morning departure and evening arrival times that is positive definite and has certain properties, a user equilibrium is shown to exist in which commuters travel in the same order in both peaks. The result is used to illustrate the user equilibrium for two cases: (i) commuters have decoupled schedule preferences in the morning and evening and (ii) commuters must work a fixed shift length but have flexibility when to start. Finally, a special case is considered with cars and transit: commuters have the same wished order in the morning and evening peaks. Commuters must use the same mode in both directions, and the complete user equilibrium solution reveals the number of commuters using cars and transit and the period in the middle of each rush when transit is used.     

Behavioral adjustments and equity effects of congestion pricing: Analysis of morning commutes during the Stockholm Trial

This paper assesses the horizontal and vertical equity effects of the Stockholm Trial with Congestion Pricing for morning commuters, in terms of both travel behavioral adjustments and welfare effects, as a result of the toll’s direct effects and the behavioral adjustments. We consider specifically two behavioral adjustments: mode choice and departure time choice. Initial car drivers crossing the toll cordon had a 15 percentage-points higher rate of switching to public transit as compared with those not crossing the cordon. We also find some evidence of peak spreading, in particular toward a later departure time, as a result of the charging scheme, but most people choose a departure time within 15 min both before and during the trial. In the welfare analysis, we found no clear pattern of increasing burden by either increasing income or decreasing income, and the increase in the Gini Coefficient was insignificant. We also found no significant difference in either the mode-switching behavior or the average welfare effect for women versus for men.     

A revised branch‐and‐price algorithm for dial‐a‐ride problems with the consideration of time‐dependent travel cost

Developing demand responsive transit systems are important with regard to meeting the travel needs for elderly people. Although Dial‐a‐ride Problems (DARP) have been discussed for several decades, most researchers have worked to develop algorithms with low computational cost under the minimal total travel costs, and fewer studies have considered how changes in travel time might affect the vehicle routes and service sequences. Ignoring such variations in travel time when design vehicle routes and schedules might lead to the production of inefficient vehicle routes, as well as incorrect actual vehicle arrival times at the related nodes. The purpose of this paper is to construct a DARP formulation with consideration of time‐dependent travel times and utilizes the traffic simulation software, DynaTAIWAN, to simulate the real traffic conditions in order to obtain the time‐dependent travel time matrices. The branch‐and‐price approach is introduced for the time‐dependent DARP and tested by examining the sub‐network of Kaohsiung City, Taiwan. The numerical results reveal that the length of the time window can significantly affect the vehicle routes and quantitative measurements. As the length of the time window increases, the objective value and the number of vehicles will reduce significantly. However, the CPU time, the average pickup delay time, the average delivery delay time and the average actual ride time (ART)/direct ride time (DRT) will increase significantly as the length of the time window increases. Designing the vehicle routes to reduce operating costs and satisfy the requirements of customers is a difficult task, and a trade‐off must be made between these goals. Copyright © 2014 John Wiley & Sons, Ltd.