A Pareto-improving hybrid rationing and pricing policy with multiclass network equilibria

This paper extends the work on Pareto-improving hybrid rationing and pricing policy for general road networks by considering heterogeneous users with different values of time. Mathematical programming models are proposed to find a multiclass Pareto-improving pure road space rationing scheme (MPI-PR) and multiclass hybrid rationing and pricing schemes (MHPI and MHPI-S). A numerical example with a multimodal network is provided for comparing both the efficiency and equity of the three proposed policies. We discover that MHPI-S can achieve the largest reduction in total system delay, MHPI can induce the least spatial inequity and MHPI-S is a progressive policy which is appealing to policy makers. Furthermore, numerical results reveal that different classes of users react differently to the same hybrid policies and multiclass Pareto-improving hybrid schemes yield less delay reduction when compared to their single-class counterparts.     

Surrogate‐based optimization of cordon toll levels in congested traffic networks

The benefit, in terms of social surplus, from introducing congestion charging schemes in urban networks is depending on the design of the charging scheme. The literature on optimal design of congestion pricing schemes is to a large extent based on static traffic assignment, which is known for its deficiency in correctly predict travel times in networks with severe congestion. Dynamic traffic assignment can better predict travel times in a road network, but are more computational expensive. Thus, previously developed methods for the static case cannot be applied straightforward. Surrogate‐based optimization is commonly used for optimization problems with expensive‐to‐evaluate objective functions. In this paper, we evaluate the performance of a surrogate‐based optimization method, when the number of pricing schemes, which we can afford to evaluate (because of the computational time), are limited to between 20 and 40. A static traffic assignment model of Stockholm is used for evaluating a large number of different configurations of the surrogate‐based optimization method. Final evaluation is performed with the dynamic traffic assignment tool VisumDUE, coupled with the demand model Regent, for a Stockholm network including 1240 demand zones and 17 000 links. Our results show that the surrogate‐based optimization method can indeed be used for designing a congestion charging scheme, which return a high social surplus. Copyright © 2016 John Wiley & Sons, Ltd.     

A comparative analysis of US toll policy

In the US, there is a long tradition of toll roads, beginning with the Lancaster Turnpike that was built at the end of the 18th century connecting Philadelphia and Lancaster. There are currently more than 300 toll facilities in the US, which is probably the largest number of toll facilities in the world. These facilities represent a wide range of conditions, from hypercongested facilities in large metropolitan areas such as New York City to toll highways in rural areas. The toll structures are equally diverse, ranging from multi-tier price structures with frequent user, carpool, and time of day discounts; to simpler structures in which the only differentiation is made on the basis of the number of axles per vehicle. The toll rates are typically set by the agencies that operate or own the toll facilities. The rules or formulas by which these tolls are determined are not generally available to the public, though it is safe to say that toll decisions are made taking into account technical considerations, as well as the all important criterion of political acceptability. However, data on toll rates and how they change by vehicle types and by some other attributes are readily available.The overall objective of this paper is to analyze the toll data from various facilities across the US to gain insight into the overall factors affecting the tolls. A more specific objective is to assess—though in a rather approximate fashion—if the tolls by vehicle type, relative to each other, are appropriate and consistent with economic theory. This is achieved by comparing tolls to approximate indicators of road space consumption and pavement deterioration. The literature review confirmed that this is the first time such research has been conducted which is an important first step toward an analysis of the efficiency of current toll policies.The analyses in this paper are based on a random sample of all toll facilities across the US. The toll dataset, which include toll rates for passenger cars, busses, and three different truck types, is assembled mainly from the available information on the web sites of various toll agencies. After cleaning the data, the authors used econometric modeling to estimate a set of ordinary least squares (OLS) regression models that express tolls as functions of independent variables. Three families of models were estimated: linear models, models based on expansions of Taylor series, and models based on piece-wise linear approximations to non-linear effects. The resulting models were analyzed to identify the salient features of current toll policies towards different vehicle types.     

Identifying peer states for transportation system evaluation &; policy analyses

The majority of comparisons between state transportation systems do not control for characteristics that may vary greatly between states (e.g., vehicle miles traveled). A shortcoming of such analyses is that a state’s individual characteristics can be highly influential in determining how transportation policy is set and funds are spent. The purpose of this paper is to extend previous efforts to create groups of similar peer states by developing a new methodological framework that incorporates demographic, temporal, and locational variability into the peer group delineations. We collected historical data for 42 variables on transportation infrastructure, population, economy, growth, topography and weather. To examine trends before and after the passage of ISTEA we gathered data over two time periods: 1985 through 1990 and 1995 through 2000. Using principal components analysis (PCA) we reduced variables into seven components, and then statistically clustered states into peer groups for each time period based on the components and the remaining variables. We identified a range of cluster solutions and demonstrate how cluster statistics help to describe the contextual basis behind the peer grouping. The results of this study are to provide government agencies, researchers and the public with a systematic methodological framework for identifying peer states that reflect similar attributes contributing to the development and maintenance of state transportation systems.

Tradable credits scheme and transit investment optimization for a two‐mode traffic network

This paper proposes an optimization model to minimize the “system costs” and guide travelers' behavior by exploring the optimal bus investment and tradable credits scheme design in a bimodal transportation system. Travelers' transport mode choice behavior (car or bus) and the modal equilibrium conditions between these two forms of transport are studied in the tradable credits scheme. Public transport priority is highlighted by charging car travelers credits only. The economies of scale presented by the transit system under the tradable credit scheme are analyzed by comparing the marginal cost and average cost. Numerical examples are presented to demonstrate the model. Furthermore, the effects of tradable credits schemes on bus investment and travelers' modal choice behavior are explored based on scenario discussions. Copyright © 2016 John Wiley & Sons, Ltd.     

A quantum evolutionary algorithm for the second-best congestion pricing problem in urban traffic networks

This paper investigates the congestion pricing problem in urban traffic networks. A first-best strategy, a second-best strategy for toll leveling in closed cordons and a second-best strategy for determining both toll levels and toll points are considered. The problem is known to be a mixed integer programming model and formulated as a bi-level optimization problem, with an objective of maximizing the social welfare. A method is presented to solve the problem, based on a novel metaheuristic algorithm, namely quantum evolutionary algorithm (QEA). To verify the proposed method, the widely used genetic algorithm (GA) is also applied to solve the problem. The problem is solved for a medium-size urban traffic network and the results of the QEA are compared against the conventional GA. Computational results show that the QEA outperforms the GA in solution quality.     

Transport policy for London in 2001 The case for an integrated approach

The paper reports the results of a series of studies conducted to enable the London Planning Advisory Committee to provide advice on strategic transport policy for London. The analytical approach combined the use of an area-based, multi-modal strategic model (LAM) and professional judgment. The performance of LAM as a basis for providing rapid advice on complex issues in transport policy is assessed.The resulting policy advice advocated a coherent approach, involving new infrastructure, particularly for rail; improved management of the road and public transport networks; the use of subsidy to enhance public transport service levels; and road user charges to reduce the impact of private vehicles on congestion and the environment. Road user charges emerged as the pivotal issue in the policy; the paper discusses their role, and the questions which still need to be resolved before they can be implemented.The main message of the study is that no one element of transport policy can tackle London's problems alone; an integrated policy in which infrastructure provision, management and pricing are used to complement one another is shown to be far more effective.     

A hybrid scheme for real‐time prediction of bus trajectories

The uncertainty associated with public transport services can be partially counteracted by developing real‐time models to predict downstream service conditions. In this study, a hybrid approach for predicting bus trajectories by integrating multiple predictors is proposed. The prediction model combines schedule, instantaneous and historical data. The contribution of each predictor as well as values of respective parameters is estimated by minimizing the prediction error using a linear regression heuristic. The hybrid method was applied to five bus routes in Stockholm, Sweden, and Brisbane, Australia. The results indicate that the hybrid method consistently outperforms the timetable and delay conservation prediction method for different route layouts, passenger demands and operation practices. Model validation confirms model transferability and real‐time applicability. Generating more accurate predictions can help service users adjust their travel plans and service providers to deploy proactive management and control strategies to mitigate the negative effects of service disturbances. Copyright © 2017 John Wiley & Sons, Ltd.     

Impact analysis of cordon-based congestion pricing on mode-split for a bimodal transportation network

This paper investigates the impact of cordon-based congestion pricing scheme on the mode-split of a bimodal transportation network with auto and rail travel modes. For any given toll-charge pattern, its impact on the mode-split can be estimated by solving a combined mode-split and traffic-assignment problem. Using a binary logit model for the mode-split, the combined problem is converted into a traffic-assignment problem with elastic demand. Probit-based stochastic user equilibrium (SUE) principle is adopted for this traffic-assignment problem, and a continuously distributed value of time (VOT) is assumed to convert the toll charges and transit fares into time-units. This combined mode-split and traffic-assignment problem is then formulated as a fixed-point model, which can be solved by a convergent Cost Averaging method. The combined mode-split and traffic-assignment problem is then used to analyze a multimodal toll design problem for cordon-based congestion pricing scheme, with the aim of increasing the mode-share of public transport system to a targeted level. Taking the fixed-point model as a constraint, the multimodal toll design problem is thus formulated as a mathematical programming with equilibrium constraints (MPEC) model. A genetic algorithm (GA) is employed to solve this MPEC model, which is then numerical validated by a network example.     

Stationary ultracapacitors storage device for improving energy saving and voltage profile of light transportation networks

The installation of stationary ultracapacitor storage devices, as widely recognized, allows the recovery of the braking energy for increasing the energy efficiency as well as a better pantograph voltage profile. In the paper a new methodological mean is proposed for determining the fundamental characteristics of this kind of storage device, characterized by high power density, interfaced with the railroad by a bidirectional dc-dc converter. More specifically, the parameters of the storage system can be determined by employing an optimization technique which in a quite general way is able to take contemporaneously into account several aspects in an integrated manner. Some considerations are performed for properly taking into account the stochastic aspects of the design procedure. Numerical simulations with respect to a case study are presented, pointing out the potentiality of the tailored technique. Experimental results are also reported, with reference to an electromechanical simulator, in order to put in evidence the effectiveness and the actual implementation of the proposed optimization technique.     

A bi-objective bi-level signal control policy for transport of hazardous materials in urban road networks

A bi-objective bi-level signal control optimization for hazardous material (hazmat) transport is considered to assess trade-offs between travel cost and environment impacts such as public risk exposure. A least maxi-sum risk model with explicit signal delay is presented to determine generalized travel cost for hazmat carriers. Since the bi-level signal control problem is generally a non-convex program, a bundle method using generalized gradients is proposed. A bounding strategy is developed to stabilize solutions of the bi-level program and reduce relative gaps between iterations. Numerical comparisons are made with other risk-averse models. The results indicate that the proposed bi-objective bi-level model becomes even amiable to signal control policy makers since provides flexible solutions whilst is acceptable to carriers since takes account of travel delay at signal-controlled junctions. Moreover, the trade-offs between public risk and generalized travel costs are empirically investigated among different risk models with a variety of weights. As a result, the proposed model consistently exhibits highly considerable advantage on mitigation of public risk whilst incurred less cost loss as compared to other alternatives.     

Public financing of private freight rail infrastructure to reduce highway congestion: A case study of public policy and decision making in the United States

As goods movement continues to increase it is expected to outpace infrastructure capacity in the United States. Moving a larger share of goods by rail rather than truck is a potentially cost effective part of a solution. Freight rail not only offers a substitute for truck trips but is a cleaner, more energy efficient, and safer alternative. Recently a number of private freight rail projects have received public funding. The public funds are aimed at increasing freight rail capacity with the goal of diverting some goods currently moved by truck to rail. While the benefits of moving goods by rail are relatively clear, it is unclear if public decision makers can effectively identify strategic rail investments that will achieve their policy goals. This study critically examines the analytical methods, models, and data that are commonly used to support decisions to provide public funds for private freight rail projects. This is accomplished through a case study of California’s Trade Corridors Improvement Fund program which provided $680 million for 11 freight rail projects. The study’s contributions include identifying critical analytical flaws and challenges affecting the benefit estimates that public funding decisions rely on. Improvements to current evaluation methods are also identified as are regulatory reforms and policy interventions that may offer more effective and reliable outcomes.     

The transportation systems of Buenos Aires, Chicago and São Paulo: City centers, infrastructure and policy analysis

We compare the passenger transportation systems of Buenos Aires, Chicago and São Paulo. The selected cities represent distinctive combinations of land-use, infrastructure, and evolution of transport policy. Analysis is centered on accessibility to downtown areas, where transportation processes converge in an environment where space is scarce. In two of the three cities institutional arrays that legally establish unified decision making have shown little capacity to launch fare or physical coordination between modes. In two of the three cities the concentration of public transportation supply to historical downtowns has not been an attraction factor, and downtown uses have expanded to less accessible areas. Gentrification in Chicago is also another process showing that land use changes are related to many factors, transportation being only one of them, and not always a necessary one. In all three cases the use of railways, as a set of inherited infrastructures, has seen an increase whose magnitude suggests a link to modal reassignment due to increasing congestion. Scarcity of space in old downtown areas is being counteracted through more intense use, or through the expansion of vertical space for transportation operations.     

A dynamic route choice model for public transport networks with boarding queues

Abstract

The concepts of optimal strategy and hyperpath were born within the framework of static frequency-based public transport assignment, where it is assumed that travel times and frequencies do not change over time and no overcrowding occurs. However, the formation of queues at public transport stops can prevent passengers from boarding the first vehicle approaching and can thus lead to additional delays in their trip. Assuming that passengers know from previous experience that for certain stops/lines they will have to wait for the arrival of the 2nd, 3rd, …, k-th vehicle, they may alter their route choices, thus resulting in a different assignment of flows across the network. The aim of this paper is to investigate route choice behaviour changes as a result of the formation and dispersion of queues at stops within the framework of optimal travel strategies. A new model is developed, based on modifications of existing algorithms.     

A hybrid model of fuzzy and AHP for handling public assessments on transportation projects

Having an effective public participation in transportation planning and project development processes has been a major concern for developed countries. In the United States, for instance, all state Departments of Transportation are subject to the Transportation Equity Act (TEA-21) that formally requires public involvement in transportation planning. Since transportation planning involves public resources and values, judgments by the public should play a key role in determining final decisions. Therefore, all these agencies are required not only to disseminate information to the public, but also to solicit and consider public opinion in forming transportation policy. This work presents a decision support model, with public involvement and public oversight, to help policy makers select appropriate transportation projects for implementation. Since focus groups will face multiple objectives and inexact information in the process, a hybrid model of fuzzy logic and analytical hierarchy process (AHP) is proposed. A set of ‘if–then’ rules based on Weber’s psycho-physical law of 1834 is presented to reason from fuzzy numbers to capture essential subjective preferences, pairwise, among the alternatives. The AHP is then incorporated to estimate preference allotments among alternatives. An example application of the suggested method is provided seeking public approval of an appropriate public bus transportation system choosing between one run by municipal authorities and one run by private agencies to show how this procedure works.

A systemic overview of non‐motorized transportation for developing countries: An agenda for action

All through the twentieth century transportation planning and the implementation of transportation facilities in the developing world was heavily weighted toward motorized transportation (MT), despite the fact that non‐motorized transportation (NMT) constitutes a significant proportion of all trips. However, in the last two decades many researchers and practitioners all across the world have recognized the importance and advantages of NMT, and their investigations and findings have contributed toward identifying, if not mitigating, some of the more glaring problems in these countries. Unfortunately, most of these investigations have been performed in a piece‐meal and disjointed fashion. This paper explores the complex and sometimes poorly understood set of relationships between transportation and its links to a myriad of other factors, such as landuse, sustainability, safety, energy, ethical issues, value of time, telecommunication, environmental justice, and equity. The main objective of this paper is to provide a systemic overview of NMT by describing its multi‐dimensional aspects and to assist developing countries in formulating an “Agenda for Action”.     

Short‐term highway traffic flow prediction based on a hybrid strategy considering temporal–spatial information

Short‐term traffic flow prediction is fundamental for the intelligent transportation system and is proved to be a challenge. This paper proposed a hybrid strategy that is general and can make use of a large number of underlying machine learning or time‐series prediction models to capture the complex patterns beneath the traffic flow. With the strategy, four different combinations were implemented. To consider the spatial features of traffic phenomenon, several different state vectors including different observations were built. The performance of the proposed strategy was investigated using the traffic flow measurements from the Traffic Operation and Safety Laboratory in Wisconsin, USA. The results show the overall performance of hybrid strategy is better than a single model. Also, incorporating observations from adjacent junctions can improve prediction accuracy. Copyright © 2017 John Wiley & Sons, Ltd.     

A virtual environment for the formulation of policy packages

The interdependence and complexity of socio-technical systems and availability of a wide variety of policy measures to address policy problems make the process of policy formulation difficult. In order to formulate sustainable and efficient transport policies, development of new tools and techniques is necessary. One of the approaches gaining ground is policy packaging, which shifts focus from implementation of individual policy measures to implementation of combinations of measures with the aim of increasing efficiency and effectiveness of policy interventions by increasing synergies and reducing potential contradictions among policy measures. In this paper, we describe the development of a virtual environment for the exploration and analysis of different configurations of policy measures in order to build policy packages. By developing systematic approaches it is possible to examine more alternatives at a greater depth, decrease the time required for the overall analysis, provide real-time assessment and feedback on the effect of changes in the configurations, and ultimately form more effective policies. The results from this research demonstrate the usefulness of computational approaches in addressing the complexity inherent in the formulation of policy packages. This new approach has been applied to the formulation of policies to advance sustainable transportation.     

A commuting model for the analysis of the impacts of a tramway project: application to the Lens area

Road congestion is not only an issue for major European urban agglomerations, but also for smaller ones. It is also the case of the Lens urban area, where car use is much higher than the average for medium-sized urban agglomerations in France. Local authorities put forward tramway projects to deal with the strongly negative externalities of congestion: travel time losses and pollution. To analyse its medium-term impact, we have developed a commuting with congestion model, inspired by the four-step traditional model, but with data made available from an origin–destination matrix. The results are encouraging but insufficient, and it is necessary to adopt supplementary measures in order to retrieve and justify the sizeable investments needed. Some measures prove to be very efficient, such as parking fees and urban tolls. Other measures, such as the subsidization of public transport, are partially efficient since they have an impact mainly on intra-urban commutes.     

A comparative study of a hybrid Logit–Fratar and neural network models for trip distribution: case of the city of Isfahan

This paper introduces a new procedure to forecast the future O/D demand. It is a hybrid of logit and Fratar model. The hybrid model has the long run, policy sensitive, characteristic of a logit model, calibrated at sector‐level with little/no zero O/D cells. This feature, joint with a Fratar‐type operation at zonal level within a sector, gives a better performance to this model than either of the two types of the models alone. The performance of the hybrid model is contrasted with a neural network model, and shows encouraging results in a real case. Copyright © 2010 John Wiley & Sons, Ltd.