Energy savings in transport

A decade of increasing Federal attention to urban transportation needs has culminated in the 1970 Urban Mass Transportation Assistance Act. This Act is intended to provide 10 thousand million dollars over the next 12 years in Federal assistance money to urban public transportation systems. This paper examines the needs of selected U.S. cities as a basis for (1) understanding the vast, various and complex transportation needs of urban areas throughout the country, and (2) assessing the sufficiency of these funds. The sample cities have been placed into three broad categories based on the state of development of their transportation systems. In Category I cities, the essential need is to ensure the survival of bus systems for the use of non‐drivers, or to provide some other viable alternative to the automobile; in Category II cities, the primary needs are to relieve auto congestion and to improve public transportation components, while in Category III cities, the primary need is massive investment to improve and to extend public transportation facilities. It is concluded that the presently intended Federal funding level for transportation will not meet the financial requirements of the Category III cities.     

A multiobjective model for maximizing fleet availability under the presence of flight and maintenance requirements

Every aircraft, military or civilian, must be grounded for maintenance after it has completed a certain number of flight hours since its last maintenance check. In this paper, we address the problem of deciding which available aircraft should fly and for how long, and which grounded aircraft should perform maintenance operations, in a group of aircraft that comprise a combat unit. The objective is to achieve maximum availability of the unit over the planning horizon. We develop a multiobjective optimization model for this problem, and we illustrate its application and solution on a real life instance drawn from the Hellenic Air Force. We also propose two heuristic approaches for solving large scale instances of the problem. We conclude with a discussion that gives insight into the behavior of the model and of the heuristics, based on the analysis of the results obtained.     

Computing 4D near-optimal trajectories for dynamic air traffic flow management with column generation and branch-and-price

Abstract

The current air traffic system faces recurrent saturation problems. Numerous studies are dedicated to this issue, including the present research on a new dynamic regulation filter holding frequent trajectory optimisations in a real-time sliding horizon loop process. We consider a trajectory optimisation problem arising in this context, where a feasible four-dimensional (4D) trajectory is to be built and assigned to each regulated flight to suppress sector overloads while minimising the cost of the chosen policy. We model this problem with a mixed integer linear programme and solve it with a branch-and-price approach. The pricing sub-problem looks for feasible trajectories in a dynamic three-dimensional (3D) network and is solved with a specific algorithm based on shortest path labelling algorithms and on dynamic programming. Each algorithm is tested on real-world data corresponding to a complete traffic day in the European air traffic system; experimental results, including computing times measurement, validate the solution process.     

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.     

A fuzzy-stochastic optimization model for the intermodal fleet management problem of an international transportation company

ABSTRACT

In this paper, a fuzzy-stochastic optimization model is developed for an intermodal fleet management system of a large international transportation company. The proposed model integrates various strategic, tactical and operational level decisions simultaneously. Since real-life fleet planning problems may involve different types of uncertainty jointly such as randomness and fuzziness, a hybrid chance-constrained programming and fuzzy interactive resolution-based approach is employed. Therefore, stochastic import/export freight demand and fuzzy transit times, truck/trailer availabilities, the transport capacity of Ro-Ro vessels, bounds on block train services, etc. can also be taken into account concurrently. In addition to minimize overall transportation costs, optimization of total transit times and CO₂ emission values are also incorporated in order to provide sustainable fleet plans by maximizing customer satisfaction and environmental considerations. Computational results show that effective and efficient fleet plans can be produced by making use of the proposed optimization model.     

Transport Demand Management in Turkey: A Genetic Algorithm Approach

Abstract

This article proposes new models for estimating transport demand using a genetic algorithm (GA) approach. Based on population, gross national product and number of vehicles, four forms of the genetic algorithm transport planning (GATP) model are developed – one exponential and the others taking quadratic forms – and applied to Turkey. The best fit models in terms of minimum total average relative errors in the test period are selected for future estimation. Demand management strategies are proposed based on three scenarios: restricting private car use, restricting truck use and the simultaneous management of private car use and goods movement. Results show that the GATP model may be used to estimate transport demand in terms of passenger-kilometers traveled (pass-km), vehicle-kilometers traveled (veh-km) and ton-kilometers completed (ton-km). Results also show that the third scenario – simultaneous restrictions on private car use and goods movement – could reduce total veh-km by about 35% by 2025 in this study of Turkish rural roads.     

The analysis of travel and emission impacts of travel demand management strategies using activity-based models

This paper demonstrates, tests and shows the value of activity-based travel demand models and household sample enumeration forecasting techniques in evaluating the transportation and air quality impacts of travel demand management strategies. Using data from the Portland, Oregon metropolitan area, three transportation policies were evaluated both individually and in combination: transit improvements, pricing, and telecommunications. The activity-based models used in this testing represents a significant improvement to today's "four-step" sequential model systems by providing a deeper insight into the individual decision making process in response to transportation policies. A wider range of impacts is predicted, and indirect effects as well as synergistic effects of such policies are taken into consideration. These models are capable of providing the information needed to improve the linkage of transportation models with emissions and air quality analysis methodologies by improving the prediction of variables that are important to accurately estimating emissions and air quality impacts of transportation actions.     

What does a one-month free bus ticket do to habitual drivers? An experimental analysis of habit and attitude change

The aim of this study was to investigate whether a temporary structural change would induce a lasting increase in drivers' public transport use. An experiment targeting 43 drivers was carried out, in which a one-month free bus ticket was given to 23 drivers in an experimental group but not to 20 drivers in a control group. Attitudes toward, habits of, and frequency of using automobile and bus were measured immediately before, immediately after, and one month after the one-month long intervention. The results showed that attitudes toward bus were more positive and that the frequency of bus use increased, whereas the habits of using automobile decreased from before the intervention, even one month after the intervention period. Furthermore, the increase in habitual bus use had the largest effect on the increase in the frequency of bus use. The results suggest that a temporary structural change, such as offering auto drivers a temporary free bus ticket, may be an important travel demand management tool for converting automotive travel demand to public-transport travel demand.     

A distributed origin–destination demand estimation approach for real-time traffic network management

Abstract

This paper describes a distributed recursive heuristic approach for the origin–destination demand estimation problem for real-time traffic network management applications. The distributed nature of the heuristic enables its parallelization and hence reduces significantly its processing time. Furthermore, the heuristic reduces dependency on historical data that are typically used to map the observed link flows to their corresponding origin–destination pairs. In addition, the heuristic allows the incorporation of any available partial information on the demand distribution in the study area to improve the overall estimation accuracy. The heuristic is implemented following a hierarchal multi-threading mechanism. Dividing the study area into a set of subareas, the demand of every two adjacent subareas is merged in a separate thread. The merging operations continue until the demand for the entire study area is estimated. Experiments are conducted to examine the performance of the heuristic using hypothetical and real networks. The obtained results illustrate that the heuristic can achieve reasonable demand estimation accuracy while maintaining superiority in terms of processing time.     

Dealing with congestion from a regional perspective The case of Massachusetts

Traffic congestion has received considerable public and media attention over the past several years. However, many of the transportation and land use actions offered to deal with the congestion phenomenon focus only on a specific site or at most a subregion of the metropolitan area. This paper argues that congestion in many cases is an areawide phenomenon requiring consideration from a regional and programmatic viewpoint. A ten-point congestion-relief program developed for eastern Massachusetts is described. Actions in this program included those aimed to mitigate current congestion and avoid future congestion through land use management. Four policy areas are emphasized - providing transportation system improvements, managing transportation demand, managing land use, and managing the institutional and funding framework. The paper concludes that because of the political nature of the congestion problem, the congestion-relief program's importance lies more in the message it sends to the public that programmatic action is being taken. The paper also concludes that a regional approach is necessary thus requiring close examination of existing institutions, that demand management is an important component of the strategy, that the private sector has an important role to play, and that the long-term effectiveness of the program relates to the success of attempts to institutionalize efforts into zoning and permit procedures.