Reliable route guidance: A case study from Chicago

Reliable route guidance can be obtained by solving the reliable a priori shortest path problem, which finds paths that maximize the probability of arriving on time. The goal of this paper is to demonstrate the benefits and applicability of such route guidance using a case study. An adaptive discretization scheme is first proposed to improve the efficiency in computing convolution, a time-consuming step used in the reliable routing algorithm to obtain path travel time distributions. Methods to construct link travel time distributions from real data in the case study are then discussed. Particularly, the travel time distributions on arterial streets are estimated from linear regression models calibrated from expressway data. Numerical experiments demonstrate that optimal paths are substantially affected by the reliability requirement in rush hours, and that reliable route guidance could generate up to 5-15% of travel time savings. The study also verifies that existing algorithms can solve large-scale problems within a reasonable amount of time.     

Adaptive data dissemination for time-constrained messages in dynamic vehicular networks

With the advent of emerging wireless communication technologies, tremendous efforts have been put on promoting the safety and efficiency of transportation services by developing innovative applications. In particular, there has been significant interest in accessing information stored at RSUs (Roadside Units). The unique characteristics in vehicular networks, such as dynamic traffic factors including vehicle arrival rate, dwell time and data access patterns, bring us new challenges on data dissemination. This work dedicates to the investigation of timely and adaptive data dissemination in the dynamically changing traffic environment. Firstly, we derive an analytical model to explore and examine the effects of the dynamic traffic factors. In light of the theoretical results, an on-line scheduling algorithm is proposed for adaptive data dissemination. Finally, we evaluate performance of the new algorithm in a variety of circumstances. The simulation results demonstrate satisfactory performance of the proposed algorithm.     

Environmental life-cycle assessment of transit buses with alternative fuel technology

The paper presents a life-cycle assessment of costs and greenhouse gas emissions for transit buses deploying a hybrid input-output model to compare ultra-low sulfur diesel to hybrid diesel-electric, compressed natural gas, and hydrogen fuel-cell. We estimate the costs of emissions reductions from alternative fuel vehicles over the life cycle and examine the sensitivity of the results to changes in fuel prices, passenger demand, and to technological characteristics influencing performance and emissions. We find that the alternative fuel buses reduce operating costs and emissions, but increase life-cycle costs. The infrastructure requirement to deploy and operate alternative fuel buses is critical in the comparison of life-cycle emissions. Additionally, efficient bus choice is sensitive to passenger demand, but only moderately sensitive to technological characteristics, and that the relative efficiency of compressed natural gas buses is more sensitive to changes in fuel prices than that of the other bus types.     

Truck backhauling on two terminal networks

Truck backhauling reduces empty truck-miles by having drivers haul loads on trips back to their home terminal. This paper 1) examines the impact on backhauling opportunities of terminal locations and directional imbalances in the flow of freight from the terminals, and 2) develops a method for determining which truckloads should be backhauled. Backhauling is studied for two terminals sending full truckloads to many customers under steady-state conditions. This research develops two backhauling models. The first is a continuous model that makes simplifying assumptions about customer locations and travel distances. It results in formulae showing that 1) savings from backhauling increase at a decreasing rate as the directional flow of freight between two terminals becomes more balanced and 2) backhauling is an important, but often ignored, factor in terminal (e.g. trucking terminal, warehouse, or plant) location and supplier selection decisions. The second model is a more general discrete model that determines which loads should be backhauled to minimize empty truck-miles.     

A derived demand model of regional highway diesel fuel use

A regional, econometric model of heavy truck diesel fuel use is derived based on the theory of production. Input demand functions for new trucks and diesel fuel are specified and estimated. A simple, logistic scrappage model is estimated and used to estimate total heavy truck stocks and diesel-engine heavy truck stocks. Demand equations based on the AIDS almost ideal demand system flexible form cost function are estimated for new heavy truck demand and regional highway diesel fuel demand. New heavy truck demand is found to be elastic with respect to GNP, inelastic with respect to own price, and appears extremely sensitive to short term GNP trends. The short run price elasticity of diesel fuel demand is found to be very small.     

Modelling the impact of rail fare increases

Rail fares in South-East England have been increasing in real terms for several years, and are expected to continue to do so. In this paper, the impact of such increases is examined in terms of the choices of mode of travel, home and job location, and residential migration. Forecasts are made using a model in which the population is partitioned into four sets according to whether they have changed home and/ or job over the forecast period. The model allocates population to homes and workers to jobs, and commuters to the three modes of travel considered. The impact of an increase of 25% in real fares over a five-year period is examined and a number of conclusions are drawn. The model shows that rail patronage will decline even if transport costs remain constant in real terms, because of decentralisation of jobs and rising car ownership. The overall long-term rail fare elasticity is found to be –0.7, but this is the mean of a wide range of values for different parts of the study area. People ceasing to commute by rail would divide almost equally between car and bus, the latter being used particularly to Central London. Those people who commute to London who are seeking new homes would tend to choose to live nearer London than they would have otherwise. The paper concludes with a discussion of the findings in terms of the assumptions implied in the model.     

Testing probabilistic discrete choice models of travel demand by comparing predicted and observed aggregate choice shares

Probabilistic discrete choice models of travel demand often are tested for the presence of specification errors by comparing the models' predictions of aggregate choice shares in population strata with observed shares. A model is rejected as misspecified if the differences between its predictions and the observations are judged too large. This judgement usually is made on intuitive grounds without use of formal statistical methods and, therefore includes no systematic method for distinguishing the effects of specification errors on differences between predictions and observations from those of random sampling errors. This paper represents formal statistical tests for comparing predicted and observed aggregate chioce shares in population strata and reports the results of an investigation of the power of the tests. The test statistics are asymptotically χ² disturbed when the model being tested is correctly specified. The results of the power investigation suggests that greater power is obtained (i.e. there is ability to detect misspecified models) when all of the available data are used for both parameter estimation and specification testing than when the available data are divided into separate estimation and test data sets. Specification tests based on comparisons of predicted and observed aggregate choice shares appear to have less power than do likelihood ratio and likelihood ratio index specification tests when the alternative models required by the latter tests are correctly or approximately correctly specified. However, tests based on comparisons of predicted and observed shares ca have greater power than the other tests when the alternative models are seriouslymisspecified.     

Recent directions in automobile demand modeling

We identify seven areas in which recent research on auto demand has made significant progress. We discuss the importance of these areas in understanding and predicting auto demand and describe the methods that researchers have used to address them. Finally, we identify the issues that this research indicates require further investigation.     

Approaches to dynamic transport planning

Dynamic transport planning refers to the analysis of the problem of choice of implementation date of the construction or improvement of transport facilities. This analysis may also include consideration of stage construction or progressive improvements in quality and/or capacity over time, beginning from some relatively low standard. A transport facility is defined as a vehicle (e.g., automobile, airplane) or a supporting facility (e.g., highway, port).There appears at present to be a serious lack of any truly comprehensive evaluation of the essentials of the problem of choice of implementation date. It is the intent of the ensuing presentation to help to rectify that situation by introducing new concepts which structure the timing problem. The concepts are based on a suggested classification of future traffic and definitions of independent and indivisible facilities. In addition, volume of traffic and benefits of a transport facility are recognized to be dependent on calendar time and the facility's age.Presently, no uniform theoretical framework exists for establishing the optimal time for constructing new facilities or improving existing ones. A framework based on the aforementioned concepts is introduced. It distinguishes between the phasing of projects through time in the absence of budget constraints and this phasing in the presence of such restrictions. The specific procedures suggested in this paper for the analysis of the problem of choice of implementation date apply to any individual transport facility and tend to unify the concepts involved in dynamic transport planning.The article concludes with a survey of current approaches to dynamic transport planning and discusses these in the light of the above framework.The study was supported by the Urban Mass Administration, U.S. Department of Transportation.     

Telecommuting and travel: state of the practice,state of the art

This paper provides an overview of the status of telecommuting in the United States, especially as it relates to changes in travel behavior. Regarding the state of the practice, the paper discusses some refinements to the definition of telecommuting that have developed through increased operational experience. It reports several policy statements involving telecommuting, and explores the appeal of telecommuting as a public policy instrument. It highlights some trends in the implementation of home-based and work center-based telecommuting, and suggests that visible public-sector involvement has been crucial to the increased activity in this area.In sketching the state of the art, the paper outlines some frequently-stated hypotheses on telecommuting and travel behavior, and summarizes current empirical findings relating to those hypotheses. Finally, it suggests a variety of topics suitable for further research. These include studying factors influencing the ultimate adoption levels of telecommuting; impacts on energy/air quality, mode choice, and location/urban form; interactions with other transportation demand management strategies; relationships to the traditional urban travel demand forecasting process; cost/benefit tradeoffs; and telecommuting centers.