This paper compares two fuzzy clustering algorithms – fuzzy subtractive clustering and fuzzy C-means clustering – to a multi-layer perceptron neural network for their ability to predict the severity of crash injuries and to estimate the response time on the traffic crash data. Four clustering algorithms – hierarchical, K-means, subtractive clustering, and fuzzy C-means clustering – were used to obtain the optimum number of clusters based on the mean silhouette coefficient and R-value before applying the fuzzy clustering algorithms. The best-fit algorithms were selected according to two criteria: precision (root mean square, R-value, mean absolute errors, and sum of square error) and response time (t). The highest R-value was obtained for the multi-layer perceptron (0.89), demonstrating that the multi-layer perceptron had a high precision in traffic crash prediction among the prediction models, and that it was stable even in the presence of outliers and overlapping data. Meanwhile, in comparison with other prediction models, fuzzy subtractive clustering provided the lowest value for response time (0.284 second), 9.28 times faster than the time of multi-layer perceptron, meaning that it could lead to developing an on-line system for processing data from detectors and/or a real-time traffic database. The model can be extended through improvements based on additional data through induction procedure.

The exact calculation of logistics costs has become a real challenge in logistics and supply chain management. It is essential to gain reliable and accurate costing information to attain efficient resource allocation within the logistics service provider companies. Traditional costing approaches, however, may not be sufficient to reach this aim in case of complex and heterogeneous logistics service structures. So this paper intends to explore the ways of improving the cost calculation regimes of logistics service providers and show how to adopt the multi-level full cost allocation technique in logistics practice. After determining the methodological framework, a sample cost calculation scheme is developed and tested by using estimated input data. Based on the theoretical findings and the experiences of the pilot project it can be concluded that the improved costing model contributes to making logistics costing more accurate and transparent. Moreover, the relations between costs and performances also become more visible, which enhances the effectiveness of logistics planning and controlling significantly

The paper deals with the traffic control and job optimization in the marine canal system. The moving of vessels can be described as a set of discrete events and states. Some of these states can be undesirable such as conflicts and deadlocks. It is necessary to apply adequate control policy to avoid deadlocks and blocks the vessels’ moving only in the case of dangerous situation. This paper addresses the use of Petri net as modelling and scheduling tool in this context. To find better solutions the authors propose the integration of Petri net with a genetic algorithm. Also, a matrix based formal method is proposed for analyzing discrete event dynamic system (DEDS). The algorithm is developed to deal with multi-project, multi-constrained scheduling problem with shared resources. It is verified by a computer simulation using MATLAB environment.

This paper is concerned with the development of a resource allocation model for road networks under supply uncertainty caused by natural disasters. An optimization model is proposed to determine which links should be invested for the system to perform better while encountering natural disasters such as earthquake. The connectivity reliability and travel time reliability of origin-destinations (ODs) are selected as performance measures to do so. The Monte-Carlo simulation method is used to estimate the reliability measures and the model is solved by the genetic algorithm. The proposed model is implemented on a test network to demonstrate the results.

Log-linear modelling is advanced as a procedure to identify factors that underlie the relative frequency of occurrence of various characteristics. The purpose of this study is to present a modelling effort using log-linear models to estimate the relationships between driver’s fault and carelessness and the traffic variables such as gender, accident severity, and accident time. The study was conducted in four different districts in Ankara, the capital of Turkey. There were 1,325 people selected for the study; and they were asked whether they had been in an accident. Four hundred and forty-eight of them answered that they had been involved in an accident. As drivers, 276 out of 448 people, namely 61.6%, had traffic accidents. The data on the variables, namely gender, driver’s fault and carelessness, accident severity and accident time, were collected through a questionnaire survey. Detailed information has been created based on this information. The analysis showed that the best-fit model regarding these variables was the log-linear model. Furthermore, the odds ratio between these variables, the associations of the factors with the accident severity and the contributions of various factors, and the multiple interactions between these variables were assessed. The obtained results provide valuable information in regard to preventing undesired consequences of traffic accidents.

Railway transport has a very important role in economy of every country. The efficiency of railway transport depends both on the quality of transport organization and on the technical reliability of the railway rolling stock. During operation of the railway freight wagons in the last years, a large number of breaks of suspension system elements have been noticed. This feature is especially reported at four-axle double wagon for coal transport (designated Fbd) and three-axle wagon for transport of cars (designated DDam). Frequent breaks of suspension system elements reduce the efficiency of transport and in some cases cause derailment of wagons and lead to large economic losses. In this paper, the causes of breakage of suspension on both wagons (Fbd and DDam) have been analyzed, but also the possibilities of how to resolve these problems, i.e. how to reduce them to a minimum or avoid them completely.

The paper is based on the question whether the existing (legislation determined) method for determining the visibility length on passive protected level railroad crossings insures the relevant level of traffic safety. It has been recognised that using of such method does not provide stopping of road driver vehicles in front of railroad crossing in all conditions. Based on such conclusion a new approach to determining visibility length on passive protected level railroad crossing is proposed. The new approach is based on the assumption that it is necessary, primarily on level railroad crossings with local roads to recognize the worst possible and expected road and weather conditions. The testing of the proposed method in the real environment has shown that at lower speeds of road vehicles there is almost no difference, and that important benefits are recognised for the speeds of 30 and 50km/h where longer stopping distances of road vehicles have been detected (road vehicle can stop safely in front of a rail crossing) with almost the same visibility lengths. The use of the proposed method could have important impact on the increase of traffic safety on passive protected level railroad crossings.

Historically, very few logistic trends have caught the attention of academics and practitioners to the same extent as outsourcing. A comprehensive literature review reveals two reasons for this continual topicality. The problem complexity and the business environment dynamics – including an interaction with other main trends in logistics and modern supply chains – both led to a permanent literature gap, indicating the need to explore some new aspects of logistics outsourcing (LO). In this paper, a new LO research perspective has been explored by identifying some weaknesses in the main LO research streams and related common viewpoints which led to six ‘logistics outsourcing research paradoxes’. Each of these paradoxes is briefly described and their links with research streams and common views on LO discussed. Finally, the nature of some known opportunities for further research is better explained and some overlooked research opportunities are highlighted.

The emergency evacuation test method of rail transit station not only affects the operation safety of the station, but it also has significant influence on the scale and cost of the station. A reasonable test method should guarantee both the safety of evacuation and that the investment is neither excessive nor too conservative. The paper compares and analyzes the differences of the existing emergency evacuation test methods of rail stations in China and other regions on the evacuation load, evacuation time calculation and the capacity of egress components, etc. Based on the field survey analysis, the desired velocity distribution of pedestrians in various station facilities and the capacity of egress components have been obtained, and then the parameters of pedestrian simulation tool were calibrated. By selecting a station for the case study, an evacuation simulation model has been established, where five evacuation scenarios have been set according to different specifications and the simulation results have been carefully analyzed. Through analyzing the simulation results, some modification proposals of the current emergency evacuation test method in the design manual have been considered, including taking into account the section passenger volume, walking time on escalators and stairs of the platform, and the condition in which the escalator most critical to evacuation should be considered as out of service.