Road Traffic Demand Elasticity Estimates: A Review

A brief summary of road traffic‐related elasticity estimates as reported in the international literature is given. An indication of the orders of magnitude of these elasticities is outlined and the variation in estimates commonly found is emphasized. The results of previous extensive surveys are collated, but a wider scope of traffic‐related research is provided by reviewing recent work and including research that has received less attention. A variety of elasticity measures related to car travel, car ownership, freight traffic and fuel demand are reported. Based on the review, some important themes underpinning the demand for road traffic are revealed.     

Exploring the relationship between perceived acceptability and referendum voting support for alternative road pricing schemes

A dominant theme in the debate on road pricing (RP) reform is securing buy in from all key stakeholders as a pre-condition for gaining support from politicians. This paper explores the key influences and the extent to which particular RP schemes are acceptable to the community at large, and how this translates into support if a scheme were subject to a vote in a referendum. Using data collected in Sydney in 2012 from a sample of car users, we estimate a recursive simultaneous bivariate probit model that recognises the endogeneity effect of scheme acceptability on voting plans. We find that there is a very strong link between voting intentions and scheme acceptability, and provide a series of direct elasticity estimates of the influence that the cost elements of RP reform schemes have on the joint probability of accepting and voting for a scheme.     

Bicyclist commuters’ choice of on-street versus off-street route segments

When using limited funds on bicycle facilities, it would be helpful to know the extent to which a new facility will be used. If a bicycle lane is added to a street, how many bicyclists will no longer use the adjacent sidewalk? If a separate bicycle path is constructed, how many bicyclists will move from the street or sidewalk? This study seeks to identify factors that explain a bicyclist’s choice between available facility choices—off-street (sidewalk and bicycle path) or on-street (bicycle lane and roadway). This paper investigates these issues through a survey of bicyclists headed to Purdue University in West Lafayette, IN, USA. The first data collected to address these questions were “site-based”. Bicyclists were interviewed on campus at the end of their trips and asked which part of the cross-sections along their routes they had used—on-street or off-street. The characteristics of a particular cross-section of street right-of-way were then compared against the characteristics of each bicyclist and his/her observed choice of street, sidewalk, lane, or path. Later, “route-based” serial data were also added. The study developed a mixed logit model to analyze the bicyclists’ facility preferences and capture the unobserved heterogeneity across the population. Effective sidewalk width, traffic signals, segment length, road functional class, street pavement condition, and one-way street configuration were found to be statistically significant. A bicycle path is found to be more attractive than a bicycle lane. Predictions from the model can indicate where investments in particular bicycle facilities would have the most desirable response from bicyclists.     

Transport and nation‐state governments worldwide: a further review

The review undertaken in this Paper shows how, in 1984, governments of nation‐states of the world deal with the important function of Transport. In all 115 countries are included and, with the information now given, it is possible to compare the situation with 1981–82, and also have a current global view of affairs affecting Transport as managed by governments. Such a review is part of the service which Transport Reviews provides for its readers. It is hoped to conduct a further review in 1988.     

Alternative Modeling Approaches Used for Examining Automobile Ownership: A Comprehensive Review

Abstract

Household vehicle ownership, and the associated dimensions including fleet size, vehicle type and usage, has been one of the most researched transport topics. This paper endeavors to provide a critical overview of the wide-ranging methodological approaches employed in vehicle ownership modeling depending on the ownership representation over the past two decades. The studies in the existing literature based on the vehicle ownership representation are classified as: exogenous static, exogenous dynamic, endogenous static and endogenous dynamic models. The methodological approaches applied range from simple linear regressions to complex econometrics formulations taking into account a rich set of covariates. In spite of the steady advancement and impressive evolution in terms of methodological approaches to examine the decision process, we identify complex issues that pose a formidable challenge to address the evolution of vehicle ownership in the coming years. Specifically, we discuss challenges with data availability and methodological framework selection. In light of these discussions, we provide a decision matrix for aiding researchers/practitioners in determining appropriate model frameworks for conducting vehicle ownership analysis.     

Review of computer software for traffic engineers

The mid‐1970s saw the initiation of several lengthy research and development programmes in the United Kingdom which culminated in a range of software for the traffic engineer. The early 1980s brought cheap, powerful microcomputers, thereby enabling the facilities offered by the software to be exploited to the full. This article describes the range of programs now available and in common usage for the design and appraisal of traffic management schemes in the United Kingdom, and suggests a few of the areas where some research and development effort is still needed.     

The use of demand correlation in the modeling of air carrier departure delays as first‐order autoregressive random processes

A method for modeling air carrier departure delays at commercial‐service airports as autoregressive random processes is presented. This method employs the correlation of a priori demand data to significantly reduce prediction error in the optimal least‐squares estimator for additive white noise. The reduction factor of the prediction error is demonstrated to be on the order of 10² over that of the unbiased estimator. Copyright © 2011 John Wiley & Sons, Ltd.     

Sub‐optimal decision‐making and the transportation problem

A modification to the transportation problem is outlined that aims to improve the quality of predictions of trip matrices, and at the same time, allow some behavioural and economic insights. A framework is suggested within which this modification may be made and a suitable statistic and iterative process are described. A simple example demonstrates the validity of the modification and suggests some areas of difficulty with the approach.     

Strategies to achieve deep reductions in metropolitan transportation GHG emissions: the case of Philadelphia

ABSTRACT

This paper investigates strategies that could achieve an 80% reduction in transportation emissions from current levels by 2050 in the City of Philadelphia. The baseline daily lifecycle emissions generated by road transportation in the Greater Philadelphia Region in 2012 were quantified using trip information from the 2012 Household Travel Survey (HTS). Emissions were projected to the year 2050 accounting for population growth and trends in vehicle technology for both the Greater Philadelphia Region and the City of Philadelphia. The impacts of vehicle technology and shifts in travel modes on greenhouse gas (GHG) emissions in 2050 were quantified using a scenario approach. The analysis of 12 different scenarios suggests that 80% reduction in emissions is technically feasible through a combination of active transportation, cleaner fuels for public transit vehicles, and a significant market penetration of battery-electric vehicles. The additional electricity demand associated with greater use of electric vehicles could amount to 10.8 TWh/year. The use of plug-in hybrid electric vehicles (PHEV) shows promising results due to high reductions in GHG emissions at a potentially manageable cost.