TRIP DISTRIBUTION MODELLING USING FUZZY LOGIC AND A GENETIC ALGORITHM

This article examines possibilities for the application of soft computing techniques for the prediction of travel demand. The model, based on fuzzy logic and a genetic algorithm, successfully solves the trip distribution problem. The possibilities of using the proposed model in solving trip generation, modal split and route choice problems have also been indicated. The model has been tested on a real numerical example. Exceptionally good correspondences between estimated and real values of passenger flows have been obtained.     

Improvement of external transport cost evaluation in the context of Lithuania’s integration into the European Union

This paper starts by reviewing the main components of social marginal costs and environmental costs in the context of transport, and it draws on the experience in Europe concerning the means by which these costs can be valued. That experience is then translated to the situation in Lithuania, where many of the same issues are now being debated. A multicriteria method is proposed to internalize these costs, both from the perspective of the state and of the carriers. Costs need to be raised substantially if the social and environmental factors are to be paid for by the transport users, and such action would bring Lithuania closer to the best practice currently in operation in the European Union.     

Locating inspection facilities in traffic networks: an artificial intelligence approach

Abstract

In order for traffic authorities to attempt to prevent drink driving, check truck weight limits, driver hours and service regulations, hazardous leaks from trucks, and vehicle equipment safety, we need to find answers to the following questions: (a) What should be the total number of inspection stations in the traffic network? and (b) Where should these facilities be located? This paper develops a model to determine the locations of uncapacitated inspection stations in a traffic network. We analyze two different model formulations: a single-objective optimization problem and a multi-objective optimization problem. The problems are solved by the Bee Colony Optimization (BCO) method. The BCO algorithm belongs to the class of stochastic swarm optimization methods, inspired by the foraging habits of bees in the natural environment. The BCO algorithm is able to obtain the optimal value of objective functions in all test problems. The CPU times required to find the best solutions by the BCO are found to be acceptable.     

Hazard perception test development for Lithuanian drivers

Hazard perception tests may not be transferable between different countries, due to differences in traffic culture and infrastructure. Therefore, different instruments might be necessary for assessing hazard perception in various countries. The aim of the current study was to develop the Lithuanian hazard perception test based on static traffic images and test its psychometric properties. Thirty-four experienced drivers participated in a pilot study, and 125 drivers with diverse driving experience took part in the main study. The final test contained 27 static traffic scenes and the participants were asked to respond if they saw a hazard or not. Results demonstrated that the test has satisfactory internal consistency and test-retest reliability. It differentiated between inexperienced and experienced drivers, and between those experienced drivers who had less than three or more than three crashes in their driving history. The test has sufficient psychometric properties for research; still further development is needed in order to apply it for individual testing and decisions about licence provision.     

Identifying critical road segments and measuring system-wide robustness in transportation networks with isolating links: A link-based capacity-reduction approach

A wide range of relatively short-term disruptive events such as partial flooding, visibility reductions, traction hazards due to weather, and pavement deterioration occur on transportation networks on a daily basis. Despite being relatively minor when compared to catastrophes, these events still have profound impacts on traffic flow. To date there has been very little distinction drawn between different types of network-disruption studies and how the methodological approaches used in those studies differ depending on the specific research objectives and on the disruption scenarios being modeled.In this paper, we advance a methodological approach that employs different link-based capacity-disruption values for identifying and ranking the most critical links and quantifying network robustness in a transportation network. We demonstrate how an ideal capacity-disruption range can be objectively determined for a particular network and introduce a scalable system-wide performance measure, called the Network Trip Robustness (NTR) that can be used to directly compare networks of different sizes, topologies, and connectivity levels.Our approach yields results that are independent of the degree of connectivity and can be used to evaluate robustness on networks with isolating links. We show that system-wide travel-times and the rank-ordering of the most critical links in a network can vary dramatically based on both the capacity-disruption level and on the overall connectivity of the network. We further show that the relationships between network robustness, the capacity-disruption level used for modeling, and network connectivity are non-linear and not necessarily intuitive. We discuss our findings with respect to Braess’ Paradox.     

A proposed simulation-based operational policy for cruise ships in the port of Kotor

This paper investigates the simulation modelling of cruise ship traffic in the Boka Kotorska Bay (BKB), which has become a very attractive cruise destination due to its geographic location, port features and attractiveness for tourism. The purpose of this paper is to examine the development of new port infrastructure, because of the increased cruise ship arrivals in recent years. The paper describes in detail the layout of the port of Kotor and the possibilities for quay extensions. The solution to minimize the number of ships at anchorage instead of being at berth is given, because the passengers of the latter ships have a more convenient approach towards the port. The simulation model is verified and the simulation results are validated against the real data prior to an investigation of the possible scenario for quay extension. The proposed solution confirms the preliminary survey results that initiated the investigation of possibilities to improve the port infrastructure. Moreover, simulation results point towards a significant improvement of cruise ships throughput in the BKB. The proposed operational policies and statistical analysis, as well as a comprehensive model analysis of the BKB provided here, are a good foundation for future investigations.     

Solving the logistic problems with optimal resource assignment using fuzzy logic methods

Fuzzy approach of optimal resource assignment regarding the given demands in the scope of transportation will be presented in the article. The basis of the research is the crisp solution which is also presented in the article. The basic solution was upgraded in order to be able to handle vaguely (i.e. fuzzily) defined requirements and resource properties. The optimal resource configuration is calculated with the aid of Hungarian algorithm which uses the data calculated with the fuzzy methods for its inputs. The approach described is presented on the example of a military convoy formation. Copyright © 2011 John Wiley & Sons, Ltd.