State-of-the art of freight forecast modeling: lessons learned and the road ahead

In this paper we review freight forecasting models and current advances and needs with respect to data and model development. We then present a case study to suggest which models should be developed for the State of California in the US. We suggest several alternatives including an aggregate commodity flow model, a disaggregate regional logistics model and a hybrid regional logistics model with a truck touring model. We point out however, that the data requirements for the latter model would be extensive. In addition, the development of hybrid models, for example progress in the integration of regional logistics models with urban truck touring models, will introduce new problems such as reconciling the outputs of multiple models for consistency.     

Robo-Taxi service fleet sizing: assessing the impact of user trust and willingness-to-use

The first commercial fleets of Robo-Taxis will be on the road soon. Today important efforts are made to anticipate future Robo-Taxi services. Fleet size is one of the key parameters considered in the planning phase of service design and configuration. Based on multi-agent approaches, the fleet size can be explored using dynamic demand response simulations. Time and cost are the most common variables considered in such simulation approaches. However, personal taste variation can affect the demand and consequently the required fleet size. In this paper, we explore the impact of user trust and willingness-to-use on the Robo-Taxi fleet size. This research is based upon simulating the transportation system of the Rouen-Normandie metropolitan area in France using MATSim, a multi-agent activity-based simulator. A local survey is made in order to explore the variation of user trust and their willingness-to-use future Robo-Taxis according to the sociodemographic attributes. Integrating survey data in the model shows the significant importance of traveler trust and willingness-to-use varying the Robo-Taxi use and the required fleet size.

     

A human factors systems approach to examining oil spills in tankbarge operations: analysis and reappraisal of management policies

An important problem in the US maritime industry is the large number of oil spills that occur as a result of oil transfer operations involving tankbarges. Recently, the US Coast Guard initiated a new programme entitled Prevention Through People that represents a concerted effort towards preventing human errors leading to casualities and oil spills. The purpose of the study reported in this paper was to explore tankbarge oil transfer operations from the standpoint of regulatory, management, and operational perspectives in order to determine the likelihood that this new initiative will indeed result in a better understanding of the causal basis for human error in these operations and, more generally, in the maritime industry. The results of this novel study are discussed and summarized in terms of four broad classes of recommendations.     

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.     

Effect of traffic information on commuters' propensity to change route and departure time

Considerable public and private resources are devoted to the collection and dissemination of real-time traffic information in the Chicago area. Such information is intended to help individuals make more informed travel decisions, yet its effect on behavior remains largely unexplored. This study evaluates the effect of traffic information on travelers' route and departure time changes and provides a stronger basis for developing advanced information systems. Downtown Chicago automobile commuters were surveyed during the AM peak period. The results indicate that a majority of the respondents access, use and respond to information. For example, individuals use travel information to reduce their anxiety—even if they do not change travel decisions; this indicates that information may have “intrinsic” value. That is, simply knowing traffic conditions is valued by travelers. More than 60% of the respondents had used traffic information to modify their travel decisions. Multivariate analysis using the ordered probit model showed that individuals were more likely to use traffic reports for their route changes if they perceived traffic reports to be accurate and timely, and frequently listened to traffic reports. Respondents were more likely to change their departure times if they perceived traffic reports to be accurate and relevant, and frequently listened to traffic reports. The implication for Advanced Traveler Information Systems are that they may be designed to support both enroute and pre-trip decisions. ATIS performance, measured in terms of accuracy, relevance and timeliness would be critical in the success of such systems. Further, near-term prediction of traffic conditions on congested and unreliable routes (where conditions change rapidly) and incident durations is desirable.     

The changing economic impacts of the port of New York

This paper investigates the economic effects of maritime trade through the Port of New York on the New York metropolitan region. It decomposes the impacts associated with the trans-shipment of waterborne exports and imports in 1977 and 1987 into those arising from the changing tonnage of trade and those attributable to the changing commodity mix. Input-output analysis is used to calculate the numbers of jobs, personal and business incomes, and output which arise from each effect. Finally, it examines the impacts on specfic industries and occupations in the region.     

Direct analysis of the perceived importance of attributes of reliability of travel modes in urban travel

Reliability of travel modes was found to be the most important characteristic of transportation systems in several attitudinal investigations of individual travel behavior. This paper represents the first part of a research effort aimed at gaining a better understanding of the characteristics of reliability of transportation modes in urban travel. In this research, reliability characteristics are identified; their importance relative to each other is assessed, and an insight into possible structure of an objective reliability index is discussed. The research is based on perceived values of reliability, which were identified through a large attitudinal survey conducted in the Chicago metropolitan area.     

Direct to your destination: the size,scope and competitive status of express coach carriers in the United States

The advent of express coach bus lines offering guaranteed seating and emphasizing curbside pickup and drop-off is contributing to a revival in intercity bus travel in the United States. Relatively little is known, however, about the scale and geographic scope of these carriers or the competitive landscape in which they operate. To fill this void, this study evaluates the service networks operated by the two largest express coach operators in the country, BoltBus and Megabus, and evaluates a data set of 4775 fares sold on megabus.com. The results show that these carriers cumulatively serve 127 intercity segments and operate about 52.9 million bus miles per year. Together, these carriers have grown to about one third of the size of Amtrak, with Megabus and BoltBus providing 3.3 billion and .69 billion seat miles of service, respectively, compared to Amtrak’s 12.8 billion. With respect to the types of routes it serves and the competition it faces, Megabus has evolved into a carrier quite different than Boltbus; more than one third of Megabus’ bus miles are operated on segments without Amtrak service, while virtually all of BoltBus’ miles face this competition. The analysis of Megabus’ pricing shows that fares rise modestly within 2 weeks of departure, while the per-mile costs are much less ($.08/mile) for 300–399 mile trips than for those 50–99 miles ($.22/mile). Nevertheless, the dispersion of fares tends to fall as the departure date nears, regardless of distance. Together, these prominent bus lines serve 66 of the 100 most heavily traveled U.S. city pairs that have characteristics suitable for intercity bus service—which is more than Amtrak. With further growth on the horizon, planners, federal regulators, and researchers should collaborate on establishing reporting requirements for this expanding sector.

     

Development of a neighborhood commute mode share model using nationally-available data

Transportation - Practitioners often use demand models to predict how neighborhood-level land use, infrastructure, demographic, and other changes may impact transportation systems. Few of the...     

Where do cyclists ride? A route choice model developed with revealed preference GPS data

To better understand bicyclists’ preferences for facility types, GPS units were used to observe the behavior of 164 cyclists in Portland, Oregon, USA for several days each. Trip purpose and several other trip-level variables recorded by the cyclists, and the resulting trips were coded to a highly detailed bicycle network. The authors used the 1449 non-exercise, utilitarian trips to estimate a bicycle route choice model. The model used a choice set generation algorithm based on multiple permutations of path attributes and was formulated to account for overlapping route alternatives. The findings suggest that cyclists are sensitive to the effects of distance, turn frequency, slope, intersection control (e.g. presence or absence of traffic signals), and traffic volumes. In addition, cyclists appear to place relatively high value on off-street bike paths, enhanced neighborhood bikeways with traffic calming features (aka “bicycle boulevards”), and bridge facilities. Bike lanes more or less exactly offset the negative effects of adjacent traffic, but were no more or less attractive than a basic low traffic volume street. Finally, route preferences differ between commute and other utilitarian trips; cyclists were more sensitive to distance and less sensitive to other infrastructure characteristics for commute trips.