Highway pricing and capacity choice in a road network under a build–operate–transfer scheme

It is often argued lately that the private sector should be allowed to build and operate roads in a transportation network at its own expense, in return it should receive the revenue from road toll charge within some years, and then these roads will be transferred to the government. This type of build–operate–transfer (B–O–T) projects is currently fashionable worldwide, especially for developing countries short of funds for road construction. One of the important issues concerning a highway B–O–T project is the selection of the capacity and toll charge of the new road and the evaluation of the relevant benefits to the private investor, the road users and the whole society under various market conditions. This paper deals with the selection and evaluation of a highway project under such a B–O–T scheme. For a given road network with elastic demand, mathematical models are proposed to investigate the feasibility of a candidate project and ascertain the optimal capacity and level of toll charge of the new highway. The response of road users to the new B–O–T project is explicitly considered. The characteristic of the problem is illustrated graphically with a numerical example.     

Welfare evaluation with a road capacity constraint

Severe traffic congestion in and around many cities across the world has resulted in programmes of extensive road building and other capacity increasing projects. But traffic congestion has often not fallen in the long run and neither has journey speed increased. Demand for peak period road travel, particularly by car, has grown so strongly that increases in road capacity have been quickly matched by increased road use. This paper develops a model of a road network characterised by insatiable road passenger (car and bus) demand. The model parameters are calibrated on a typical urban road network, and a number of simulations conducted to determine social welfare after the introduction of a road capacity constraint into the optimisation process. The empirical results have an important policy implication for the evaluation of projects that increase road capacity, namely that standard methods of cost-benefit analysis may tend to overestimate the net benefits of such projects by a significant amount. Although the model is developed in the context of roads and road traffic congestion, it could also be applied to air travel.     

Explaining light vehicle demand evolution in interurban toll roads: a dynamic panel data analysis in Spain

Tolls have increasingly become a common mechanism to fund road projects in recent decades. Therefore, improving knowledge of demand behavior constitutes a key aspect for stakeholders dealing with the management of toll roads. However, the literature concerning demand elasticity estimates for interurban toll roads is still limited due to their relatively scarce number in the international context. Furthermore, existing research has left some aspects to be investigated, among others, the choice of GDP as the most common socioeconomic variable to explain traffic growth over time. This paper intends to determine the variables that better explain the evolution of light vehicle demand in toll roads throughout the years. To that end, we establish a dynamic panel data methodology aimed at identifying the key socioeconomic variables explaining changes in light vehicle demand over time. The results show that, despite some usefulness, GDP does not constitute the most appropriate explanatory variable, while other parameters such as employment or GDP per capita lead to more stable and consistent results. The methodology is applied to Spanish toll roads for the 1990–2011 period, which constitutes a very interesting case on variations in toll road use, as road demand has experienced a significant decrease since the beginning of the economic crisis in 2008.     

Rationing and pricing strategies for congestion mitigation: Behavioral theory,econometric model,and application in Beijing

Some travel demand management policies such as road pricing have been widely studied in literature. Rationing policies, including vehicle ownership quota and vehicle usage restrictions, have been implemented in several megaregions to address congestion and other negative transportation externalities, but not well explored in literature. Other strategies such as Vehicle Mileage Fee have not been well accepted by policy makers, but attract growing research interest. As policy makers face an increasing number of policy tools, a theoretical framework is needed to analyze these policies and provide a direct comparison of their welfare implications such as efficiency and equity. However, such a comprehensive framework does not exist in literature. To bridge this gap, this study develops an analytical framework for analyzing and comparing travel demand management policies, which consists of a mathematical model of joint household vehicle ownership and usage decisions and welfare analysis methods based on compensating variation and consumer surplus. Under the assumptions of homogenous users and single time period, this study finds that vehicle usage rationing performs better when relatively small percentages of users (i.e. low rationing ratio) are rationed off the roads and when induced demand elasticity resulting from congestion mitigation is low. When the amount of induced demand exceeds a certain level, it is shown analytically that vehicle usage restrictions will always cause welfare losses. When the policy goal is to reduce vehicle travel by a fixed portion, road pricing provides a larger welfare gain. The performance of different policies is influenced by network congestion and congestibility. This paper further generalizes the model to consider heterogenous users and demonstrates how it can be applied for policy analysis on a real network after careful calibration.     

Evolution over time of heavy vehicle volume in toll roads: A dynamic panel data to identify key explanatory variables in Spain

Improving the knowledge of demand evolution over time is a key aspect in the evaluation of transport policies and in forecasting future investment needs. It becomes even more critical for the case of toll roads, which in recent decades has become an increasingly common device to fund road projects. However, literature regarding demand elasticity estimates in toll roads is sparse and leaves some important aspects to be analyzed in greater detail. In particular, previous research on traffic analysis does not often disaggregate heavy vehicle demand from the total volume, so that the specific behavioral patterns of this traffic segment are not taken into account. Furthermore, GDP is the main socioeconomic variable most commonly chosen to explain road freight traffic growth over time. This paper seeks to determine the variables that better explain the evolution of heavy vehicle demand in toll roads over time. To that end, we present a dynamic panel data methodology aimed at identifying the key socioeconomic variables that explain the behavior of road freight traffic throughout the years. The results show that, despite the usual practice, GDP may not constitute a suitable explanatory variable for heavy vehicle demand. Rather, considering only the GDP of those sectors with a high impact on transport demand, such as construction or industry, leads to more consistent results. The methodology is applied to Spanish toll roads for the 1990–2011 period. This is an interesting case in the international context, as road freight demand has experienced an even greater reduction in Spain than elsewhere, since the beginning of the economic crisis in 2008.     

Measuring the benefits derived from a transportation investment

This paper reviews the problems associated with application of the concept of consumers' surplus to the measurement of benefits derived from a transportation investment. This review is warranted since such measurement is very complicated when alternative modes or different paths are available to the users and benefit measures have been proposed which, on the surface, appear not to agree. In particular, as Mohring (1976), Williams (1976) and Agnello (1977), among others, have discussed, demand curves for interdependent modes will shift in response to a modal specific improvement, i.e. a unimodal investment, thereby complicating the measurement of consumers' surplus. The perspective taken in this paper resolves seeming inconsistencies in the literature regarding the directions of demand shifts and the correct measure to be used in calculating changes in consumer's surplus following an investment. This is accomplished by introducing an aggregate, origin-destination demand curve which is independent of the alternative modes actually available and from which traditional modal demands can be derived. An approach for deriving the modal demands from the aggregate demand and the behavioral assumptions behind the aggregate supply is described; the aggregate demand is used to unequivocably determine the directions of shifts in the modal demand curves due to specific modal investments. The resulting consistency of modal and aggregate demand is shown to lead to an unambiguous measure of total consumers' surplus variation. Extensions to include producers' surplus are also given.     

Regulating inter-firm agreements: The case of airline codesharing in parallel networks

We compare aviation markets under conditions of competition, codesharing contracts and anti-trust immune alliances, assuming that demand for flights depends on both fares and the level of frequency offered. Using a hybrid competitive/cooperative game theoretic framework, we show that the stronger the inter-airline agreement on overlapping routes, the higher the producer surplus. On the other hand, consumer surplus and overall social welfare are maximized under limited codesharing agreements. Partial mergers appear preferable to no agreement in ‘thin’ markets, in which both demand and profit margins are relatively low. Inter-governmental agreements are also analyzed and we show that bilaterals create the least favorable market outcomes for consumers and producers. Finally, a realistic case study demonstrates that under asymmetric and uncertain demand, codesharing on parallel links may be preferable to competitive outcomes for multiple consumer types.     

The concept and impact analysis of a flexible mobility on demand system

This paper introduces an innovative transportation concept called Flexible Mobility on Demand (FMOD), which provides personalized services to passengers. FMOD is a demand responsive system in which a list of travel options is provided in real-time to each passenger request. The system provides passengers with flexibility to choose from a menu that is optimized in an assortment optimization framework. For operators, there is flexibility in terms of vehicle allocation to different service types: taxi, shared-taxi and mini-bus. The allocation of the available fleet to these three services is carried out dynamically so that vehicles can change roles during the day. The FMOD system is built based on a choice model and consumer surplus is taken into account in order to improve passenger satisfaction. Furthermore, profits of the operators are expected to increase since the system adapts to changing demand patterns. In this paper, we introduce the concept of FMOD and present preliminary simulation results. It is shown that the dynamic allocation of the vehicles to different services provides significant benefits over static allocation. Furthermore, it is observed that the trade-off between consumer surplus and operator’s profit is critical. The optimization model is adapted in order to take into account this trade-off by controlling the level of passenger satisfaction. It is shown that with such control mechanisms FMOD provides improved results in terms of both profit and consumer surplus.     

Estimating road network accessibility during a hurricane evacuation: A case study of hurricane Irma in Florida

Understanding the spatio-temporal road network accessibility during a hurricane evacuation—the level of ease of residents in an area in reaching evacuation destination sites through the road network—is a critical component of emergency management. While many studies have attempted to measure road accessibility (either in the scope of evacuation or beyond), few have considered both dynamic evacuation demand and characteristics of a hurricane. This study proposes a methodological framework to achieve this goal. In an interval of every six hours, the method first estimates the evacuation demand in terms of number of vehicles per household in each county subdivision (sub-county) by considering the hurricane’s wind radius and track. The closest facility analysis is then employed to model evacuees’ route choices towards the predefined evacuation destinations. The potential crowdedness index (PCI), a metric capturing the level of crowdedness of each road segment, is then computed by coupling the estimated evacuation demand and route choices. Finally, the road accessibility of each sub-county is measured by calculating the reciprocal of the sum of PCI values of corresponding roads connecting evacuees from the sub-county to the designated destinations. The method is applied to the entire state of Florida during Hurricane Irma in September 2017. Results show that I-75 and I-95 northbound have a high level of congestion, and sub-counties along the northbound I-95 suffer from the worst road accessibility. In addition, this research performs a sensitivity analysis for examining the impacts of different choices of behavioral response curves on accessibility results.     

Acceleration noise and level of service of urban roads - A case study

Capacity measurement of roads under mixed traffic conditions as prevailing in India is ambiguous as it varies with time, composition of traffic and roadway encroachments. High incidence of slow moving vehicles and tricycles adds to the problem. Volume - capacity ratio appears to be an inadequate measure of defining level of service under mixed traffic situations. An attempt is made in this paper to explore the possibility of presenting unconventional parameters like standard deviation of speed, co-efficient of variation of speed and acceleration noise as possible measures of level of service. Tentative ranges of acceleration noise are proposed in association with flow and speed to explain level of service of urban roads catering to mixed traffic. The results are based on a study conducted in Madras, a major metropolitan city of India.     

Commercially managed road funds: managing roads like a business,not like a bureaucracy

Nearly all countries are seriously short of revenues for investment and maintenance of roads. Improving utilization of the existing road budget has helped to narrow, but not eliminate, this financing gap. Requests for additional resources from the government's budget have fallen on deaf ears, because the road sector has grown too large to be fully-financed through general tax revenues. Government tax systems were not designed to finance major economic sectors like roads. Faced with an acute shortage of funds, many road agencies have introduced tolls on high-volume roads and have invited the private sector to build and operate such roads under concession agreements. Although this has narrowed the financing gap, tolling is only economic on a small part of the road network. Tolls have thus had a relatively small impact on the financing gap. Against this background, and mindful of the fact that roads are now 'big business' on the scale of the Fortune Global 500, a growing number of countries have started to 'bring roads into the market place, put them on a fee-for-service basis and manage them like a business.' The fee-for-service concept, though superficially like the user-pay principle and the associated road funds which became popular during the 1950s, differs from user-pay in a number of important respects. The key differences are that: (i) only road user charges go into the road fund (i.e., there are no earmarked taxes); (ii) the fund is managed by a representative board with half or more members representing road users and the business community; (iii) members are nominated by the constituencies they represent and there is an independent chairperson; (iv) financing arrangements are designed to ensure that money is not diverted from other sectors; (v) funds are managed pro-actively by a small secretariat; (vi) there are published financial regulations governing the way funds are managed; (vii) charges are adjusted regularly to meet agreed expenditure targets; and (viii) there are regular technical and financial audits. Other important characteristics are that most commercially managed road funds are managed through a separate road fund administration, funds are channeled to all roads (sometimes even to unclassified roads) and they are introduced as part of a wider agenda to commercialize road management. Some of these road funds have been set up as road public utilities under a board with powers to set their own tariffs.     

Analysis of the effectiveness of control measures to mitigate road dust emissions in a regional network

The effectiveness of control measures to reduce road dust emissions is analyzed using a year’s data of road dust emissions collected with a mobile sampling platform and a survey of road maintenance practices in the Lake Tahoe Basin of Nevada and California US. Attributes such as sweeping practices, anti-icing, shoulder improvement, pavement condition, trackout, and abrasive material from road segments were analyzed with a feature subset selection algorithm. Street sweeping was found to be an effective means of controlling dust emissions from roads. Road dust from dirty tertiary roads served as a continuous source of suspendable material for adjacent high-speed roads in the winter time. To be most effective, emission control strategies require that not only primary roads, but all roads be swept after snow storms to recover applied abrasive material.     

Large-scale road network vulnerability analysis: a sensitivity analysis based approach

Traditionally, an assessment of transport network vulnerability is a computationally intensive operation. This article proposes a sensitivity analysis-based approach to improve computational efficiency and allow for large-scale applications of road network vulnerability analysis. Various vulnerability measures can be used with the proposed method. For illustrative purposes, this article adopts the relative accessibility index (AI), which follows the Hansen integral index, as the network vulnerability measure for evaluating the socio-economic effects of link (or road segment) capacity degradation or closure. Critical links are ranked according to the differences in the AIs between normal and degraded networks. The proposed method only requires a single computation of the network equilibrium problem. The proposed technique significantly reduces computational burden and memory storage requirements compared with the traditional approach. The road networks of the Sioux Falls city and the Bangkok metropolitan area are used to demonstrate the applicability and efficiency of the proposed method. Network manager(s) or transport planner(s) can use this approach as a decision support tool for identifying critical links in road networks. By improving these critical links or constructing new bypass roads (or parallel paths) to increase capacity redundancy, the overall vulnerability of the networks can be reduced.     

Pareto-improving transportation network design and ownership regimes

Private provision of public roads signifies co-existence of free, public-tolled and private-tolled roads. This paper investigates the Pareto-improving transportation network design problem under various ownership regimes by allowing joint choice of road pricing and capacity enhancement on free links. The problem of interest is formulated as a bi-objective mathematical programming model that considers the travel cost of road users in each origin-destination pair and the investment return of the whole network. The non-dominated Pareto-improving solutions of toll and/or capacity enhancement schemes are sought for achieving a win-win situation. A sufficient condition is provided for the existence of the non-dominated Pareto-improving schemes and then the properties of those schemes are analyzed. It is found that, under some mild assumptions, the optimal capacity enhancement is uniquely determined by the link flow under any non-dominated Pareto-improving scheme. As a result, the joint road pricing and capacity enhancement problem reduces to a bi-objective second-best road pricing problem. A revenue distribution mechanism with return rate guarantee is proposed to implement the non-dominated Pareto-improving schemes.     

Demand and welfare effects in recreational travel models: Accounting for substitution between number of trips and days to stay

In this paper we present a non-linear demand system for households’ joint choice of number of trips and days to spend at a destination. The approach, which facilitates welfare analysis of exogenous policy and price changes, is used empirically to study the effects of an increased CO₂ tax. In particular, we focus on the effect of including substitution between households choice of the number of trips and days to spend at a destination in the welfare analysis. The analysis reveals that the equivalent variation (EV) measure, for the count data demand system, can be seen as an upper bound for the households welfare loss. Approximating the welfare loss by the change in consumer surplus, accounting for the positive effect from longer stays, imposes a lower bound on the households welfare loss. The difference in the estimated loss measures, from the considered CO₂ tax reform, is about 20%. This emphasizes the importance of accounting for substitutions toward longer stays in travel demand policy evaluations.     

Rail Infrastructure: Challenges for Cost–Benefit Analysis and Other ex ante Evaluations

Abstract

Cost–benefit analysis (CBA) plays a major role in the ex ante evaluation of rail projects in many western countries. At first sight carrying out a CBA for rail projects seems straightforward, since cost estimates are almost always available, and the most dominant benefits are generally known, being the travel time saved and the increase in consumer surplus due to induced demand. However, the practice is much more complex: the quality of current estimates for costs and benefits is often poor and several benefits-related aspects are ignored. This article gives an overview of the challenges in improving the quality of CBAs for rail projects.     

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.     

Sharing costs in Swedish road ownership associations

Usually transport systems, and roads in particular, are viewed as public goods. However, this is not always the case. In Sweden a large part of the road system is privately owned. Most of these privately owned roads are rural roads used by farmers and summer cottage owners, or used for forest transport. These roads are mainly provided by ownership associations.An important difference between public roads and these privately owned roads is that all investments- and maintenance decisions are made by the users themselves, who also have to pay the costs, whereas the usual case is that the owners/providers of a road-system are different agents than the users. Here the question is not how to charge the roads but how to split the costs of the roads among the users in an efficient and “fair” way.The motivation of this paper is the practical problem of how such an ownership association can divide the costs for the road network among the members in an efficient and “fair” way. The problem is treated from a game theoretical point of view, making use of the Shapley value. This means that the problem is associated with a game - a mathematical representation of the conflict situation. The Shapley value is a very important solution concept for cooperative games, like the game in this case. For games corresponding to this specific type of problems, it is shown that the Shapley value has excellent properties, such as beeing an element of the core, and beeing very easy to compute.     

Reserve capacity model based on variable demand for land-use development control

In this paper, the concept of reserve capacity has been extended to zone level to measure the land-use development potentiality of each trip generation zone. Bi-level programing models are proposed to determine the signal setting of individual intersections for maximizing possible increase in total travel demand and the corresponding reserve capacity for each zone. The change of the origin–destination pattern with the variation of upper level decision variables is presented through the combined distribution/assignment model under user equilibrium conditions. Both singly constrained and doubly constrained combined models are considered for different trip purposes and data information. Furthermore, we have introduced the continuous network design problem by increasing road capacity and examined its effect on the land-use development potentiality of trip generation zone. A numerical example is presented to illustrate the application of the models and how a genetic algorithm is applied to solve the problem.     

Optimal housing supply in a bid-rent equilibrium framework

In this study, we examine how the spatial distribution of housing supply impacts people’s residential choices and developers’ profitability. By optimally providing housing supply in a region, developers attempt to maximize their profits; on the other hand, if residents were given a chance to decide on housing supply, what patterns of housing supply they would prefer in order to maximize their consumer surpluses. This paper studies the interplay between these two perspectives. A nested multinomial-logit choice structure that encapsulates the bid-rent process is used to capture residents’ location and travel choices simultaneously, and the resultant rents at different locations. To investigate the optimal housing supply for these two stakeholders, we conduct sensitivity analyzes to explore the impact of different housing supply patterns on total rental profit and total consumer surplus. Specifically, analytical results are derived for a simple linear network with two residential locations and one destination under homogeneous and heterogeneous value(s) of time. The results of the sensitivity analyzes indicate that segregation of housing supplies at different locations for different income classes is, surprisingly, a “preferred” outcome by residents under consumer surplus maximization, whereas creating housing supply shortages at convenient locations is a natural outcome under housing profit maximization. These results provide insights on revealing the differences and tradeoffs in performance between these two different perspectives, and on where land use regulations may be needed to balance these two objectives.