A simple vehicle dispatching policy with non-stationary stochastic arrival rates

This paper provides an impulsive stochastic control approach to the vehicle dispatching problem with non-stationary and stochastic arrival rates. Both necessary and sufficient conditions for optimal dispatches are given with proofs given in appendices. It is shown by means of examples that stationary solutions previously considered are a special case of the theory outlined here. In addition, a discussion of other dispatching rules is included in the conclusion together with their effect on the mathematical optimality of vehicle dispatching.     

A review of the impact of parking policy measures on travel demand

This paper reviews the empirical evidence relating to the impact of parking policy measures on the demand for parking and for travel. Disaggregate modal choice models, disaggregate parking location models and site‐specific studies of parking behaviour are examined. With regard to modal choice models, it is concluded that few studies deal adequately with parking factors, but that there is some support for the view that parking policy measures are a relatively important influence on modal choice. When parking location models are examined parking policy variables are shown to have a substantial impact on choice of parking location. With regard to site‐specific studies, the paper concludes that there is a great variation in the parking price elasticities quoted, which reflects partly the methodological problems associated with such studies. Suggestions to improve model specification are made.     

Envisioning an emission diet: application of travel demand mechanisms to facilitate policy decision making

Emission reduction strategies are gaining attention as planning agencies work towards adherence to air quality conformity standards. Policymakers struggling to reduce greenhouse gases (GHG) must grapple with a growing number of travel demand policies. To consider any of these emerging demand mechanisms as a viable option to meet emission targets, planners and policymakers need tools to better understand the implications of such policies on travel behavior. In this paper we present an integrated multimodal travel demand and emission model of four policy strategies; presenting GHG and air pollutant reduction results at a very detailed level. Multiple policy outcomes are compared within a single modeling framework and study area. The results reveal that while no one demand mechanism is likely to reduce emissions to a level that meets policy-maker’s goals; a first-best pricing strategy that incorporates marginal social costs is the most effective emission reduction mechanism. Implementing such a mechanism may offer total emission reductions of up to 24 %. However, the efficacy of this strategy must be weighed against difficulties of establishing efficient pricing, a costly implementation, and substantial negative impacts to non-highway facilities. Decision makers must select a mixture of pricing and land use strategies to achieve emission goals on all road facilities.     

Optimization of traffic demand management policy in China: towards a sustainable mode split

The rapid increase in private car use in large metropolitan areas has led to irrational travel mode splits and severe traffic problems. Traffic demand management (TDM) is an effective policy to achieve a more sustainable development of traffic systems. This study analyzes the relationships between TDM policy, mode split, and travel mode choice using Stackelberg game theory. Then, using 0–1 programming, it establishes a combination of TDM policy instruments that can achieve a more sustainable mode split in a city and provides a case study in China. The method presented in this research has strong theoretical implications for TDM policymakers.     

Analysis of regulation and policy of private toll roads in a build-operate-transfer scheme under demand uncertainty

The build-operate-transfer (BOT) approach is one of the privatization mechanisms for promoting transportation infrastructure developments by using private funds to construct new infrastructure facilities. In a BOT scheme, it often involves three parties: the government, whose objective is to maximize the benefit defined in terms of social welfare added to the society; the private investors, whose objective is to maximize the profit generated from the investment; and the road users, whose objective is to minimize the inequality of benefit distribution among the road users traveling from different origin–destination pairs. Each of these parties has different objectives that often conflict with each other. In this paper, we develop various optimal road pricing models under demand uncertainty for analyzing the tradeoffs among the three objectives. In addition, a project evaluation framework is developed for assessing the effects of government policy and regulation on the BOT project. Seven cases of the BOT road pricing problem are analyzed: (1) BOT without regulation, (2) BOT with price control regulation, (3) BOT with equity regulation, (4) BOT with construction cost subsidy, (5) BOT with concession period extension, (6) BOT with construction cost subsidy and concession period extension, and (7) BOT with multiple objectives. Numerical results using a real case study of the Ban Pong–Kanchananburi Motorway (BMK) in Thailand are provided to examine the above seven cases.     

Transport policy in Eastern Europe a case study of Hungary

This paper analyses the development of transport policy making in Eastern Europe over the last forty years and describes the role of the CMEA in determining national developments in Poland, Romania, East Germany, Czechoslovakia, Hungary and Bulgaria. The USSR, Albania and Yugoslavia are excluded. The planning system as operated in the Eastern Block, is described, followed by a particular case study of Hungarian policy making with respect to the transport sector. Specific tansport issues relating to Hungary are outlined before conclusions are drawn in terms of future developments in relation with the European Community.     

Steering short-term demand for car-sharing: a mode choice and policy impact analysis by trip distance

Transportation - Car-sharing could have substantial benefits. However, there is not enough evidence about if more people choosing car-sharing would reduce private car usage or public transport...     

The transaction cost approach to modeling the demand for automobiles

The purchase of an automobile involves significant transaction costs in addition to the purchase price. Therefore, the assumptions implied by static car holding models are invalid. This paper describes a dynamic approach to the modeling of level-of-ownership and auto-type choice, based on a transaction choice model which utilizes information on past car ownership. The cost or disutility of a transaction depends on the attributes of the household and the purchased car, as well as on past car-ownership characteristics. A set of assumptions underlying the incorporation of transaction costs in the model is presented. The paper discusses the econometric implications of omitting the dynamic attributes (i.e., past ownership characteristics). A disaggregate model was estimated, using a choice-based sample consisting of a random sample of households enriched with a sample of households which transacted in the car market during the study period. This sampling method combined with a random choice of a subset of the car alternatives provides for a cost-effective method to estimate a transaction model.     

Managing a smart bicycle system when demand outstrips supply: the case of the university community in Seville

Of the many public initiatives used to promote the use of bicycles in the urban environment, the one that has achieved the most spectacular results in a short period of time is the public bicycle hire system. The experience of Seville is one of the most successful internationally, where 6.6 % of mechanised trips were being made by bicycle within 30 months. This paper analyses this experience in the university community, which represents one-third of system users. We conclude that the people who are most satisfied with the system are those who use it for leisure and recreation activities, non-residents of the city, more environmentally aware people and those who have no alternative mode of transportation. Their satisfaction is also closely linked to their appreciation of the bicycles’ level of comfort, the ease with which users can hire bicycles and return them and the small amount of paperwork involved required to sign up for the system. However, user appreciation has fallen over time because the system’s rapid success has caused it to become overloaded. This experience therefore provides one main lesson: the system’s success can result in eventual difficulties.     

An integrated, dynamic approach to travel demand forecasting

This paper presents a unified approach for improving travel demand models through the application and extension of supernetwork models of multi-dimensional travel choices. Proposed quite some time ago, supernetwork models solved to stochastic user equilibrium can provide a simultaneous solution to trip generation, distribution, mode choice, and assignment that is consistent with disaggregate models and predicts their aggregate effects. The extension to incorporate the time dimension through the use of dynamic equilibrium assignment methods is proposed as an enhancement that is necessary in order to produce realistic models. A variety of theoretical and practical problems are identified whose solution underlies implementation of this approach. Recommended future research includes improved algorithms for stochastic and dynamic equilibrium assignment, new methods for calibrating assignment models, and the use of Geographic Information Systems (GIS) technology for data and model management.     

Forecasting petrol demand and assessing the impact of selective strategies to reduce fuel consumption

Abstract

The use of fossil fuels in transportation is an important topic as a result of growing concerns over global warming. Automobile petrol demand has been of particular interest to researchers and policy-makers, given that the automobile is a major contributor to the enhanced greenhouse effect. This paper forecasts Australia's automobile petrol demand up to the year 2020 based on the best performing forecasting model selected out of eight models. In order to establish ways to reduce the demand for petrol, and the consequent by-product of reducing the amount of greenhouse gas emissions, we have estimated the impact on CO₂ for several potential policy instruments, using Transportation and Environment Strategy Impact Simulator (an integrated transport, land use and environmental strategy impact simulation programme). We find that a carbon tax of AU$0.50/kg can reduce automobile kilometres by 5.9%, resulting in reduced demand for petrol and a reduction in CO₂ of 1.5%.     

Understanding the role of the forecast-maker in overestimation forecasts of policy impacts: The case of Travel Demand Management policies

Forecasting the impacts of a proposed policy is an important component of the transportation planning and decision making process. Although scientific tools are often used in transportation forecasts, biases and, more specifically, overestimations of the expected impact are often observed. This study explores the correlations between forecast-maker’s characteristics and forecast bias creation and reduction. The study examines two transport-related policies aiming at the reduction of car use: telecommuting and carsharing. Both are Travel Demand Management (TDM) policies, which attract much attention from transport experts. We tested the extent to which the forecast-maker’s beliefs about the policy at stake affected the forecast bias. We found that attitudes and beliefs associates not only with overestimation bias but also with its reduction over time. We also tested the extent to which the forecast-maker’s affiliation, the performing institute and the publication type were correlated with the biases of the forecast and with the forecaster attitudes and beliefs. These characteristics are intuitively used by the forecast user as tools to assess the ‘objectivity’ of the forecast, but our analysis found no association between these characteristics and the forecast bias.     

An integrated transportation decision support system for transportation policy decisions: The case of Turkey

From the point of view of the feasibility of providing growth in road capacity parallel to the predicted growth in traffic as well in terms of impact on the environment and health, current trends in transportation are unsustainable. Transport problems are expected to worsen due to the fact that worldwide automobile ownership tripled between 1970 and 2000, and the movement of goods is projected to increase by 50% by 2010. Similar trends can be seen in an even more dramatic way in Turkey. The Turkish transport network has not followed a planned growth strategy, due to political factors. There is no transportation master plan which aims to integrate the transport modes in order to provide a balanced, multimodal system. This study proposes a decision support system that guides transportation policy makers in their future strategic decisions and facilitates analysis of the possible consequences of a specific policy on changing the share of transportation modes for both passenger and freight transportation. For this purpose, based on the wide spectrum of critical issues encountered in the transportation sector, several scenarios have been built and analysed.     

Impacts of the urban parking system on cruising traffic and policy development: the case of Zurich downtown area,Switzerland

Transportation - Cruising-for-parking is a common phenomenon in many urban areas worldwide. Properly understanding and mitigating cruising can reduce travel times, alleviate traffic congestion, and...     

Estimating the demand for urban bus travel

The disadvantages of conventional transportation study models, in particular their large data requirements and their weaknesses in dealing with changes in trip generation rates have led to a need for a simple model that can quickly and at low cost examine alternative public transport strategies.This paper investigates simple economic models of bus demand, examines alternative variables that can be used and discusses some alternative model forms. It demonstrates the results of a model using data from twelve urban bus operators in Britain and compares the results with those from other types of study. The model utilises fare and service quality elasticities to explain the decline in passengers on urban bus services, and derives an average elasticity with respect to fare changes of –0.31 and with respect to service quality changes of +0.62. It is estimated that fare rises accounted for 13% of the 43% decline in passengers over the last fifteen years, vehicle mileage reductions for 14.3% and that only 15.7% was due to such factors as rising car ownership which are often given as the cause of declining bus patronage.The results, by showing that passengers are far more sensitive to changes in service than they are to fare rises, are a useful guide to the broader public transport policy issues, and the paper concludes that the model does provide a useful method of forecasting public transport demand at a strategic level. Further work is needed, however, to establish more accurate forecasts for different types of passenger and studies are now being undertaken to establish these and to construct an operational forecasting model that can be applied with only limited data requirements     

Meta-analysis of public transport demand

The present study uses meta-regression in order to explain the wide variation in elasticity estimates obtained in previous demand studies, and provide summaries of several bus demand elasticities.One important finding as to the price elasticity is that the often cited rule of thumb of −0.3 holds good if quality of service represented by vehicle-kilometres is treated as an exogenous variable, but not when it is treated as endogenous.Based on the results it is recommended that demand models should include car ownership, price of petrol, own price, income and some measure of service among the explanatory variables and that the service variable should be treated as endogenous.In previous meta-studies in this field focus has been on own price elasticity only while this study also includes elasticities with respect to, level of service, income, price of petrol and car ownership. The short run for the US are found to be −0.59, 1.05, −0.62, 0.4 and −1.48 respectively.     

The accuracy of the multinomial logit model as an approximation to the multinomial probit model of travel demand

The multinomial probit model of travel demand is considerably more general but much less tractable than the better-known multinomial logit model. In an effort to determine the effects of using the relatively simple logit model in situations where the assumptions of probit modeling are satisfied but those of logit modeling are not, the accuracy of the multinomial logit model as an approximation to a variety of three-alternative probit models has been evaluated. Multinomial logit can give highly erroneous estimates of the choice probabilities of multinomial probit models. However, logit models appear to give asymptotically accurate estimates of the ratios of the coefficients of the systematic components of probit utility functions, even when the logit choice probabilities differ greatly from the probit ones. Large estimation data sets are not necessarily needed to enable likelihood ratio tests to distinguish three-alternative probit models from logit models that give seriously erroneous estimates of the probit choice probabilities. Inclusion of alternative-specific dummy variables in logit utility functions cannot be relied upon to reduce significantly the errors of logit approximations to the choice probabilities of probit models whose utility functions do not contain the dummies.     

Sensitivity of prices to demand shocks: A natural experiment in the San Francisco Bay Area

We analyze the impact of a freeway interchange collapse in the San Francisco Bay Area on the difference in airfare quotes for travel into the area’s main airports. The incident temporarily made Oakland airport a less attractive choice for traveling to San Francisco, so we hypothesize that fares for travel into Oakland will be relatively lower while the freeway interchange was out of service. We test our contention using a sample of fare quotes collected on-line, and find the expected effect of a magnitude of 6–7%. Our results imply the following important conclusions. First, the demand-side shock was well absorbed by the supply side. Second, adjustment of prices and return to the status quo once the shock vanished was swift.