Introducing congestion pricing on a new toll road

This paper proposes a demonstration project to test the effectiveness of congestion pricing in an urban area. It reviews the general theoretical case for such pricing and summarizes recent international interest in congestion pricing. Next, it sets forth the reasons why demonstration projects are needed, both to add to our knowledge about how effective congestion pricing may prove to be, and to address political and other public-acceptance barriers to implementation of the concept. The paper then defines a specific proposed test site for congestion pricing: a new toll road being planned for Orange County, California. It is proposed that instead of charging flat-rate tolls, the transportation agency could charge peak and off-peak tolls, increasing the level of the peak charge each year over a period of up to 10 years unless or until toll revenues decline below the levels forecast under the flat-rate toll alternative. Measurements of traffic flow and ride-sharing behavior would be made, as well as calculations of emission-reduction effects. The paper concludes with a brief discussion of marketing and political considerations involved in conducting such a demonstration.Abbreviations ARB Air Resources Board - AVI Automatic Vehicle Identification - CDMG Corridor Design Management Group - HOV High-occupancy vehicle - SJHTC San Joaquin Hills Transportation Corridor - TCA Transportation Corridor Agency - VMT Vehicle miles traveled     

Optimization of transport investment and pricing policies: the role of transport pricing in network design

This paper investigates the role of transport pricing in network design and describes two facts about flow pattern in a transportation system. The first, illustrated by an example of Braess paradox, is that adding a new link to the network does not necessarily minimize the total travel time. The second is that introducing of appropriate toll pricing may reduce not only the total network time but also the travel time for each individual traveller. It follows with the investigations of different system objectives and different pricing policies (only toll pricing and distance‐based pricing are considered), and shows how they affect the system performance and flow pattern. Lastly, a systematic optimization process is proposed for integrated planning of transport network and pricing policies.     

Solving a discrete multimodal transportation network design problem

This paper investigates the multimodal network design problem (MMNDP) that optimizes the auto network expansion scheme and bus network design scheme in an integrated manner. The problem is formulated as a single-level mathematical program with complementarity constraints (MPCC). The decision variables, including the expanded capacity of auto links, the layout of bus routes, the fare levels and the route frequencies, are transformed into multiple sets of binary variables. The layout of transit routes is explicitly modeled using an alternative approach by introducing a set of complementarity constraints. The congestion interaction among different travel modes is captured by an asymmetric multimodal user equilibrium problem (MUE). An active-set algorithm is employed to deal with the MPCC, by sequentially solving a relaxed MMNDP and a scheme updating problem. Numerical tests on nine-node and Sioux Falls networks are performed to demonstrate the proposed model and algorithm.     

Approximate algorithms for the discrete network design problem

The discrete network design problem is one of finding a set of feasible actions (projects) from among a collection of possible actions, that when implemented, optimizes some objective function(s). This is a combinatorial optimization problem that is very expensive to solve exactly. This paper proposes two algorithms for obtaining approximate solutions to the discrete network design problem with much less computational effeort. The computational savings are achieved by approximating the original problem with a new formulation which is easier to solve. The first algorithm proposed solves this approximate problem exactly, while the second is even more efficient, but provides only a near-optimal solution to the approximate problem. Experience with test problems indicates that these approximations can reduce the computational effort by a factor of 3–5, with little loss in solution accuracy.     

The multi-criteria road network design problem in an urban area

In this paper, urban network design is analysed through a heuristic multi-criteria technique based on genetic algorithms. Both network layout and link capacity (link layout and traffic lights) are optimised. Different optimisation criteria are included for users, non-users and public system managers. Demand is considered elastic with respect to mode choice; both morning and afternoon peak periods are taken into account. In addition, choice of parking location is simulated. The procedure is applied to a test and to a real transportation system.     

Error and optimism bias in toll road traffic forecasts

Traffic forecasts are employed in the toll road sector, inter alia, by private sector investors to gauge the bankability of candidate investment projects. Although much is written in the literature about the theory and practice of traffic forecasting, surprisingly little attention has been paid to the predictive accuracy of traffic forecasting models. This paper addresses that shortcoming by reporting the results from the largest study of toll road forecasting performance ever conducted. The author had access to commercial-in-confidence documentation released to project financiers and, over a 4-year period, compiled a database of predicted and actual traffic usage for over 100 international, privately financed toll road projects. The findings suggest that toll road traffic forecasts are characterised by large errors and considerable optimism bias. As a result, financial engineers need to ensure that transaction structuring remains flexible and retains liquidity such that material departures from traffic expectations can be accommodated.

Effect of advanced traveler information systems and road pricing in a network with non-recurrent congestion

The effect of the application of advanced transport information system (ATIS) and road pricing is studied in a transportation system under non-recurrent congestion. A stochastic network deterministic user equilibrium model (SNDUE) with elastic demand is formulated and used to evaluate the welfare and private impacts of different market penetrations of ATIS, together with road pricing for a simple network. Both marginal first-best road pricing and a second-best fixed road pricing are considered. The incentives of private users to use ATIS are analyzed and the characteristics of optimum tolls as a function of ATIS market penetration are shown. We conclude that ATIS is an efficient and necessary tool to reduce the effects of non-recurrent incidents in a transportation network, especially when non-recurrent congestion causes a significant deterioration of operational conditions of the network. If the impact of non-recurrent incidents on free flow costs is small or is reduced only to congestion effects, the use of road pricing would be more efficient. Social benefits obtained when jointly implementing ATIS and road pricing are practically the same whether first-best or second-best road pricing is used. Considering the private costs perceived by the network users, and the benefits experienced by equipped users, the maximum level of market penetration achieved could be limited because private benefits disappear after certain market penetration is obtained.     

Multi-objective optimization of a road diet network design

The present study focuses on the development of a model for the optimal design of a road diet plan within a transportation network, and is based on rigorous mathematical models. In most metropolitan areas, there is insufficient road space to dedicate a portion exclusively for cyclists without negatively affecting existing motorists. Thus, it is crucial to find an efficient way to implement a road diet plan that both maximizes the utility for cyclists and minimizes the negative effect on motorists. A network design problem (NDP), which is usually used to find the best option for providing extra road capacity, is adapted here to derive the best solution for limiting road capacity. The resultant NDP for a road diet (NDPRD) takes a bi-level form. The upper-level problem of the NDPRD is established as one of multi-objective optimization. The lower-level problem accommodates user equilibrium (UE) trip assignment with fixed and variable mode-shares. For the fixed mode-share model, the upper-level problem minimizes the total travel time of both cyclists and motorists. For the variable mode-share model, the upper-level problem includes minimization of both the automobile travel share and the average travel time per unit distance for motorists who keep using automobiles after the implementation of a road diet. A multi-objective genetic algorithm (MOGA) is mobilized to solve the proposed problem. The results of a case study, based on a test network, guarantee a robust approximate Pareto optimal front. The possibility that the proposed methodology could be adopted in the design of a road diet plan in a real transportation network is confirmed.     

A multi-commodity flow network design problem

There exist systems which can be usefully described by a network containingarcs through which a commodity of one type flows. This paper is concerned with finding a solution procedure for a particular multi-commodity flow network design problem. The problem is to identify a set of arcs in the network such that if travel is prohibited in them all flow travels by feasible paths and its total cost is minimal. The total flow in each arc may not exced its capacity, which is a known constant. Each arc and each node of the network has a non-negative constant unit traversal cost. Between each pair of distinct nodes there is a given non-negative rate of flow from the first vertex to the second which may be split up among a number of paths according to some constant traversal cost flow assignment process. The optimality criterion is the total traversal cost of all flow, which is to be minimized. Previous work on network design problems of this type is surveyed. The principal contribution of this paper is the presentation of a solution procedure for the above problem based on branch and bound enumeration. An illustrative numerical example is included. Computational experience gained in using the procedure with a FORTRAN IV program on an IBM 370 is favourable.     

An analysis of the Spanish high capacity road network criticality

The analysis of complex networks has been carried out in different fields using an ample variety of method and concepts. Recently, in the general literature of regional economics, the concepts of resilience, connectivity, vulnerability and criticality have been gaining their momentum. The aim of this paper is to provide an analytical framework, using well-known accessibility indicators, in order to calculate the critical links or road sections of the Spanish high-capacity road network. Our analysis will be based on approximately four hundred sections that will be classified in five different groups according to their criticality degree in the whole network. Our analysis will be complemented with the comparison of the results obtained in five different scenarios, namely the average criticality using the effects on the whole country, Madrid, Barcelona, Valencia and Pontevedra. Furthermore, the paper will also analyze what kind of intrinsic characteristics of the sections favor or not the links’ criticality using a method based on a classification and regression tree. This analysis is crucial to understand other important concepts that are recently being studied in network and spatial economics, like, for example, resilience and vulnerability. It is concluded that the number of relations or routes, being a trunk or not, the road density and the time to Madrid capital play an important role in the criticality of the roads section in the high capacity road network.     

The demand curve under road pricing and the problem of political feasibility: A comment

This paper contains a comment on an article by Professor Lave, recently published in this journal (Transpn Res. 28A, 83–91, 1994). Lave's approach towards analyzing the political feasibility of road pricing is challenged on several grounds. In a simple setting, where individual road users are identical in terms of private cost of driving and valuation of time, Lave's approach is seen to be, although less clear, in essence equivalent to the traditional textbook analysis. In a more complex setting, where differences across individuals are allowed for, his approach is seen to suffer from lacking recognition of differences in individual marginal utilities of income.     

Nonlinear pricing on private roads with congestion and toll collection costs

Nonlinear pricing (a form of second-degree price discrimination) is widely used in transportation and other industries but it has been largely overlooked in the road-pricing literature. This paper explores the incentives for a profit-maximizing toll-road operator to adopt some simple nonlinear pricing schemes when there is congestion and collecting tolls is costly. Users are assumed to differ in their demands to use the road. Regardless of the severity of congestion, an access fee is always profitable to implement either as part of a two-part tariff or as an alternative to paying a toll. Use of access fees for profit maximization can increase or decrease welfare relative to usage-only pricing for profit maximization. Hence a ban on access fees could reduce welfare.     

Bottleneck congestion pricing and modal split: Redistribution of toll revenue

The paper examines the question of the redistribution of toll revenue as seen in a bottleneck congestion model. Our objective is to analyse the impact of this redistribution on total cost and on modal split between railroad and road. Following Tabuchi’s two-mode model (Tabuchi, T., 1993. Bottleneck congestion and modal split. Journal of Urban Economics 34, 414-431.), we integrate a redistribution of toll revenue towards public transport into our study. In this context, we investigate two kinds of road toll regimes: a fine toll and a uniform toll. We will consider two types of railroad fare: when it is set equal to the marginal cost and when it is set equal to average cost. These models allow us to show that toll policy to be more efficient as long as toll revenue is directed towards public transport when the railroad fare is equal to average cost.     

Aggregation effects on the network design problem

This article examines the effects of various network extraction schemes on the network design problem. Given an original network, many criteria can be used to identify subnetworks on which the network design problem is solved. For the purposes of this article, these subnetworks are obtained using an extraction algorithm which preserves the magnitude of the user equilibrium flows on the links of these subnetworks. The results of the implementation of the network design problem on the original and the extracted subnetworks are presented and compared. We conclude that very good solutions to the network design problem can be obtained from the use of highly aggregate networks.     

Estimating commuter mode choice: A discrete choice analysis of the impact of road pricing and parking charges

Automobile use leads to external costs associated with emissions, congestion, noise and other impacts. One option for minimizing these costs is to introduce road pricing and parking charges to reduce demand for single occupant vehicle (SOV) use, while providing improvements to alternatives to encourage mode switching. However, the impact of these policies on urban mode choice is uncertain, and results reported from regions where charging has been introduced may not be transferable. In particular, revealed preference data associated with cost recovery tolls on single facilities may not provide a clear picture of driver response to tolls for demand management. To estimate commuter mode choice behaviour in response to such policies, 548 commuters from a Greater Vancouver suburb who presently drive alone to work completed an individually customized discrete choice experiment (DCE) in which they chose between driving alone, carpooling or taking a hypothetical express bus service when choices varied in terms of time and cost attributes. Attribute coefficients identified with the DCE were used in a predictive model to estimate commuter response to various policy oriented combinations of charges and incentives. Model results suggest that increases in drive alone costs will bring about greater reductions in SOV demand than increases in SOV travel time or improvements in the times and costs of alternatives beyond a base level of service. The methods described here provide an effective and efficient way for policy makers to develop an initial assessment of driver reactions to the introduction of pricing policies in their particular regions.     

货运服务业地方保护破局

地方保护的表现 当前货运服务业还存在哪些地方保护? 浙江省的绝大多数地方对货运配载、货运代理等货运服务业采取备案制管理.总体上来说,浙江的货运服务业是开放的,但是仍存在地方保护的现象,主要表现为两种形式:一是当地政府保护下的地方保护,如一些依托商品市场建立起来的货运市场,当地政府一股设有市场管理委员会进行封闭式专线管理,并严格控制货运市场及周边市场进入,有的甚至几年内没有新审批进入者;二是不透明管理引起的地方保护,如个别地方对外声称开放,但是进入程序和需要条件不公开,存在很大的人为因素,一旦有新经营者准备进入时又变相阻扰.     

Formulating and solving the network design problem by decomposition

The optimal transportation network design problem is formulated as a convex nonlinear programming problem and a solution method based on standard traffic assignment algorithms is presented. The technique can deal with network improvements which introduce new links, which increase the capacity of existing links, or which decrease the free-flow (uncongested) travel time on existing links (with or without simultaneously increasing link capacity). Preliminary computational experience with the method demonstrates that it is capable of solving very large problems with reasonable amounts of computer time.     

Profit maximization by a private toll road with cars and trucks

This paper examines the profit maximizing behavior of a private firm which operates a toll road competing against a free alternative in presence of cars and trucks. Trucks differ from cars in value of time (VOT), congestion externality, pavement damage, and link travel time function. We find that the firm takes either a car-strategy or a truck-strategy for profit maximization. For a traffic mix with relatively large car volume and small truck volume, the car-strategy results in no trucks using the toll road, while the truck-strategy results in all trucks using the toll road. We derive the equilibrium flow pattern under any combination of car-toll and truck-toll, based on which we identify a profit-maximizing frontier and a strategy-switching frontier in the car-toll and truck-toll two-dimensional space. By geometrically comparing the two frontiers, we establish general conditions under which each strategy will be taken, which suggest that the truck-to-car VOT ratio, the total traffic demand, and the difference in travel distance between the two roads are critical in shaping the firm's strategy.     

A reliability‐based network design problem

This paper presents a reliability‐based network design problem. A network reliability concept is embedded into the continuous network design problem in which travelers' route choice behavior follows the stochastic user equilibrium assumption. A new capacity‐reliability index is introduced to measure the probability that all of the network links are operated below their capacities when serving different traffic patterns deviating from the average condition. The reliability‐based network design problem is formulated as a bi‐level program in which the lower level sub‐program is the probit‐based stochastic user equilibrium problem and the upper level sub‐program is the maximization of the new capacity reliability index. The lower level sub‐program is solved by a variant of the method of successive averages using the exponential average to represent the learning process of network users on a daily basis that results in the daily variation of traffic‐flow pattern, and Monte Carlo stochastic loading. The upper level sub‐program is tackled by means of genetic algorithms. A numerical example is used to demonstrate the concept of the proposed framework.     

Application of Ant System to network design problem

Network design problem (NDP) is the problem of choosing from among a set of alternative projects which optimizes an objective (e.g., minimizes total travel time), while keeping consumption of resources (e.g., budget) within their limits. This problem is difficult to solve, because of its combinatorial nature and nonconvexity of the objective function. Many algorithms are presented to solve the problem more efficiently, while trading-off accuracy with computational speed. This increase in speed stems from certain approximations in the formulation of the problem, decomposition, or heuristics. This study adapts a meta – heuristic approach to solve NDP, namely Ant System (AS). The algorithm is first designed, and then calibrated to solve NDP for the Sioux Falls test network. The behavior of the algorithm is then investigated. The result seems encouraging.