The model proposed in this paper uses four psychological instruments for assessing driver behaviour and personality traits aiming to find a relationship between the considered constructs and the occurrence of traffic accidents. A Barratt Impulsiveness Scale (BIS-11) was used for the assessment of impulsivity, Aggressive Driving Behaviour Questionnaire (ADBQ) for assessing the aggressiveness while driving, Manchester Driver Attitude Questionnaire (DAQ) and the Questionnaire for self-assessment of driving ability. Besides these instruments, the participants filled out an extensive demographic survey. Within the statistical analysis, in addition to the descriptive indicators, correlation coefficients were calculated and four hierarchical regression analyses were performed to determine the predictive power of personality traits on the occurrence of traffic accidents. Further, to confirm the results and to obtain additional information about the relationship between the considered variables, the structural equation modelling and binary logistic regression have been implemented. A sample of this research covered 305 drivers, of which there were 100 bus drivers and 102 truck drivers, as well as 103 drivers of privately owned vehicles. The results indicate that BIS-11 and ADBQ questionnaires show the best predictive power which means that impulsivity and aggressiveness as personality traits have the greatest influence on the occurrence of traffic accidents. This research could be useful in many fields, such as the design of selection procedures for professional drivers, development of programs for the prevention of traffic accidents and violations of law, rehabilitation of drivers who have been deprived of the driving license, etc.

According to World Health Organization, each year, over 1.2 million people die on roads, and between 20 and 50 million suffer non-fatal injuries. Based on international reports, Iran has a high death rate caused by road accidents. The objective of this study was to extract implicit knowledge from road accident data sets on roads of Iran through data mining. In this regard, three useful data mining techniques were combined: clustering, classification and rule extraction. Following the preparation stage, data were segmented via three clustering algorithms; Kohonen, K-Means and Twostep. Two-step cluster analysis is a one-pass-through data approach which generates a fairly large number of pre-clusters. Next, the optimized algorithm and cluster were identified, after which, in the classification level and by adding the drivers' demographic features through C5.0, a classification algorithm was employed so as to make the decision tree. Ultimately, the effects of these demographic features were investigated on road accidents. The characteristics such as age, job, driving license duration and gender proved to be more important factors in accident analysis. Certain rules of accidents were then extracted in each season of the year.

Express coach (EC) lost a considerable share of passengers after high-speed rail (HSR) was implemented. This paper proposes a door-to-door operation mode for the EC system and builds a model to design an EC trip-end network in the origin city with the aim of maximizing the EC’s daily operating profit. A case study is undertaken, and the results show that the operating profit of the EC system first increases and then decreases with the growth of the trip-end routes. In the HSR era, door-to-door operation can effectively guarantee the market share and operating profits of the EC.

With adaptive customer-orientation the efficiency of supply chain management is improved substantially. By the introduction of service quality-based decision-making into supply chain management the quality of service (QoS) within supply chains is expected to improve autonomously and continuously up- and downstream. In the paper the main characteristics of quality of service oriented supply chain management are outlined. The quality of service criterion, introduced into the adaptive supply chain model, provides market regulators and managements with the needed information and feedback to their increasingly informed decisions. By an experiment comprising several typical scenarios on our agent-based simulation model it was possible to empirically verify the expected impact of quality of service-
based reasoning on generic adaptive supply chains.

Continuous network design problem (CNDP) is searching for a transportation network configuration to minimize the sum of the total system travel time and the investment cost of link capacity expansions by considering that the travellers follow a traditional Wardrop user equilibrium (UE) to choose their routes. In this paper, the CNDP model can be formulated as mathematical programs with complementarity constraints (MPCC) by describing UE as a non-linear complementarity problem (NCP). To address the difficulty resulting from complementarity constraints in MPCC, they are substituted by the Fischer-Burmeister (FB) function, which can be smoothed by the introduction of the smoothing parameter. Therefore, the MPCC can be transformed into a well-behaved non-linear program (NLP) by replacing the complementarity constraints with a smooth equation. Consequently, the solver such as LINDOGLOBAL in GAMS can be used to solve the smooth approximate NLP to obtain the solution to MPCC for modelling CNDP. The numerical experiments on the example from the literature demonstrate that the proposed algorithm is feasible.

This paper investigates a hybrid management policy of road tolls and tradable credits in mixed road networks with both public and private roads. In the public sub-network, a tradable credit scheme is applied to mitigate traffic congestion. In the private sub-network, tolls are collected by the private company, but the toll levels and toll locations are determined by the government. The purpose of toll charge is two-fold: on the one hand, the government uses it as a tool for mitigating congestion; on the other hand, a threshold of revenue should be guaranteed for the profitability of the private company. A bi-level programming model is formulated to minimize the total travel time in the network by taking into account the user equilibrium travel behaviour and the revenue requirement of private firms. To obtain a  global optimum solution, the bi-level model is transformed into an equivalent single-level mixed integer linear program that can be easily solved with commercial software. Numerical examples are provided to demonstrate the effectiveness of the developed model and the efficiency of the proposed algorithm. It is shown that the mixed management schemes can achieve favourable targets, namely, joint implementation of road tolls and tradable credits can effectively mitigate traffic congestion and meanwhile maintain reasonable revenue for the private company.

Recently, new traffic data sources have emerged raising new challenges and opportunities when applying novel methodologies. The purpose of this research is to analyse car travel time data collected from smartphones by Google Company. Geographic information system (GIS) tools and Python programming language were employed in this study to establish the initial framework as well as to automatically extract, analyse, and visualize data. The analysis resulted in the calculation of travel time fluctuation during the day, calculation of travel time variability and estimation of origin-destination (OD) skim matrices. Furthermore, we accomplished the accessibility analysis and provided recommendations for further research.

According to available data released by the European Aviation Safety Agency (EASA) in the period from 1990 to 2007, more than 94,743 collisions with birds occurred on the territory of US, UK and Canada. In some parts of the world bird population is significantly growing. Also, the number of aircraft operations has increased in recent decades, and more importantly, their increase is expected in the future as well. In these conditions, the number of aircraft collisions with birds is expected to grow. Bird strikes are affecting safety and also generate additional costs in air traffic. This paper will show what type of bird strike costs exist with focus on repair and withdrawal of bird strike costs. Repair and withdrawal costs due to bird strike are specific because they could vary from insignificant amount up to millions of dollars and because of its unpredictability.

Implementation of Air Traffic Management (ATM) Master
Plan-defined projects represents a prerequisite for the
successful implementation of the Single European Sky initiative
defined by the European Commission in 2004. The
implementation of ATM-related projects is currently under the responsibility of the Single European Sky Research Programme Deployment Manager. While the definition of projects is being performed at the European Network level, the
implementation is performed through sub-regional grouping of Air Navigation Service Providers in a form of Functional Airspace Blocks. This paper analyses the level of implementation of ATM-related projects in the Functional Airspace Block Central Europe and their relation to other Functional Airspace Blocks defined in Europe. From this paper it is obvious that even though the planning of Single European Sky projects is based on the collaborative implementation of Functional Airspace Block level, the real implementation is fragmented and based on national levels.