The goal of the study was to investigate if the drivers behave in the same way when they are driving a motorcycle or a car. For this purpose, the Motorcycle Rider Behaviour Questionnaire and Driver Behaviour Questionnaire were conducted among the same drivers population. Items of questionnaires were used to develop a structural equation model with two factors, one for the motorcyclist’s behaviour, and the other for the car driver’s behaviour. Exploratory and confirmatory factor analyses were also applied in this study. Results revealed a certain difference in driving behaviour. The principal reason lies probably in mental consciousness that the risk-taking driving of a motorbike can result in much more catastrophic consequences than when driving a car. The drivers also pointed out this kind of thinking and the developed model has statistically confirmed the behavioural differences. The implications of these findings are also argued in relation to the validation of the appropriateness of the existing traffic regulations.

The paper is focused on the Fourier transform application in urban traffic analysis and the use of said transform in traffic decomposition. The traffic function is defined as traffic flow generated by different categories of traffic participants. A Fourier analysis was elaborated in terms of identifying the main traffic function components, called traffic sub-functions. This paper presents the results of the method being applied in a real case situation, that is, an intersection in the city of Bucharest where the effect of a bus line was analysed. The analysis was done using different time scales, while three different traffic functions were defined to demonstrate the theoretical effect of the proposed method of analysis. An extension of the method is proposed to be applied in urban areas, especially in the areas covered by predictive traffic control.

A commuter’s mode choice decision in response to provided traveller information is directly dependent on the temporal and spatial interactions between the available travel modes, the network performance and control schemes, and the supplied traveller information. A self-developed simulation model – Intelligent Network Simulation Model (INSIM) – was employed to simulate travel scenarios in a multimodal transportation network. A set of experiments was designed to analyse and evaluate the influence of traffic information on commuter’s mode choice, using a medium-sized area in Singapore. Simulation results showed that the private-to-public mode switch propensity bears a strong and direct relation with amount of disseminated integrated multimodal traveller information (IMTI) as well as timeliness of information update. Other influential factors include degrees of accessibility and compliance to IMTI, and congestion-related events such as accidents.

Travel time forecasting is an interesting topic for many ITS services. Increased availability of data collection sensors increases the availability of the predictor variables but also highlights the high processing issues related to this big data availability. In this paper we aimed to analyse the potential of big data and supervised machine learning techniques in effectively forecasting travel times. For this purpose we used fused data from three data sources (Global Positioning System vehicles tracks, road network infrastructure data and meteorological data) and four machine learning techniques (k-nearest neighbours, support vector machines, boosting trees and random forest).

To evaluate the forecasting results we compared them in-between different road classes in the context of absolute values, measured in minutes, and the mean squared percentage error. For the road classes with the high average speed and long road segments, machine learning techniques forecasted travel times with small relative error, while for the road classes with the small average speeds and segment lengths this was a more demanding task. All three data sources were proven itself to have a high impact on the travel time forecast accuracy and the best results (taking into account all road classes) were achieved for the k-nearest neighbours and random forest techniques.

The left-turn of vehicles at intersections has significant impacts on urban traffic congestions and accidents, which have negative effect on vehicle emissions causing air pollution. Many urban traffic networks prohibit direct left-turns for transport planning to keep traffic moving efficiently on major roads. As such, this paper proposes a bi-level mathematical model for left-turn prohibition planning considering both travel times and traffic emissions. The lower-level and upper-level are respectively solved by using the Frank-Wolfe algorithm and an improved genetic algorithm. By numerical examples, this paper shows that the improved algorithm can effectively enhance the speed and accuracy of the calculation, and the traffic congestions and emissions can be alleviated by implementing the left-turn prohibition at some carefully selected intersections.

A bi-objective programming model (BP) with spatial equity constraints is proposed to site park-and-ride (P&R) facilities in traffic networks. Both the number and locations of P&R facilities are determined. The maximal coverage and minimal resource utilization criteria, which are generally conflicting, are simultaneously considered to reveal the trade-off between the quality and cost of coverage. Furthermore, the concept of passenger flow volume per cost is defined and several properties of the model solutions are analyzed. Finally, this model is applied to site P&R facilities in Anaheim, California. Application results show the trade-offs associated with passenger flow volume, cost and passenger flow volume per cost, and the effects of spatial equity constraints on the spatial deployment of P&R facilities.

Previous research has shown that mobile phone use while driving increases the risk of being involved in an accident. This paper investigates the reported frequency of taxi drivers' mobile phone use and its effects on traffic safety. A representative sample of taxi drivers was included in an interview-based survey by trained interviewers. It was found that 81% of the taxi drivers reported talking by using hand-held phone while driving. There is a relationship between the phoning while driving and drivers' self-reported involvement in a dangerous situation. It is clear that the use of mobile phone while driving is an important traffic safety issue.

This study presents an accident prediction model of Erzurum’s Highways in Turkey using artificial neural network (ANN) approaches. There are many ANN models for predicting the number of accidents on highways that were developed using 8 years with 7,780 complete accident reports of historical data (2005-2012). The best ANN model was chosen for this task and the model parameters included years, highway sections, section length (km), annual average daily traffic (AADT), the degree of horizontal curvature, the degree of vertical curvature, traffic accidents with heavy vehicles (percentage), and traffic accidents that occurred in summer (percentage). In the ANN model development, the sigmoid activation function was employed with Levenberg-Marquardt algorithm. The performance of the developed ANN model was evaluated by mean square error (MSE), the root mean square error (RMSE), and the coefficient of determination (R2). The model results indicate that the degree of vertical curvature is the most important parameter that affects the number of accidents on highways.

The paper presents Vehicular Ad Hoc Network (VANET) system based on an analysis of the movement of a motorcade in an emergency situation. This analysis seeks to answer the question: when and under what conditions Emergency Message (EM) sent by Vehicle-to-Vehicle (V2V) system reaches the final target to help in preventing of serious accidents, such as multi-vehicle collisions. The model of calculation based on the key principles of vehicle braking enables finding the time to possible collision and the residual velocity of the vehicle. In the calculations, the average values of the driver’s reaction time are accepted; in addition, a sent emergency message is considered to be free of interference. Upon choosing different road and driving conditions, it is found what vehicle of the motorcade stops before the possible obstacle on emergency braking. The performance of vehicles with and without VANET system is compared.

Large amounts of energy drinks and caffeine, which is the main ingredient of energy drinks, produce a negative effect on the drivers, and therefore affect traffic safety.
In order to determine the attitudes of drivers toward the impact of energy drinks and caffeine, a research was conducted using a questionnaire form and the targeted group of the survey were drivers. The research was conducted in the City of Belgrade in December 2012. There were 420 survey papers distributed to drivers of different age groups of which 412 were returned. The survey was completely anonymous and consisted of two parts. The first part was related to basic demographic information about the respondents and it had 8 closed type questions. These questions were responded by circling one of the offered answers. The second part of the survey referred to determining the driver’s attitudes about energy drinks and caffeine. The second part consisted of 26 questions and respondents were to use a five-level scale in order to show to what extent they agree or disagree with any of the listed statements.
The results show that energy drinks are consumed mostly by young people, less than 25 years old. The effect of caffeine on gender is statistically significant. Headache is the reason why caffeine (25%) is consumed more than energy drinks (8%).
Major impact of energy drinks and caffeine on road safety indicates a required activity in this area such as education.

It is commonly accepted that the majority of maritime causalities are caused by human factors/errors. The role of human factor in maritime accident and the possible reasons of this argument can be quantitatively evaluated based on expert knowledge and multiple criteria decision-making (MCDM) methodology. To investigate what makes the first “human factor” in ship accidents, a hybrid approach was applied in this study. Two methods, the decision-making trial and evaluation laboratory (DEMATEL) and the analytical network process (ANP) were proposed to evaluate the importance level of the human factors in maritime casualties. Quantitative evaluations of the human errors in maritime operations can greatly improve the decision-making process and reduce potential risks. As a result of this study, the top three priorities in the evaluation systems were found as: ‘ability, skills, knowledge’ (8.94%), ‘physical condition’ (8.77%), ‘weather - sea conditions’ (8.21%) and the least important criterion was ‘cargo characteristics’ (2.21%).

An urban passenger transportation problem is studied. Municipal authorities and passengers are regarded as participants in the passenger transportation system. The municipal authorities have to optimise road width and public transport frequency. The road consists of a dedicated bus lane and lanes for passenger cars. The car travel time depends on the number of road lanes and passengers’ choice of travel mode. The passengers’ goal is to minimize total travel costs, including time value. The passengers try to find the optimal ratio between public transport and cars. The conflict between municipal authorities and the passengers is described as a game theoretic model. The existence of Nash equilibrium in the model is proved. The numerical example shows the influence of the value of time and intensity of passenger flow on the equilibrium road width and public transport frequency.

This paper provides a preview of the former stages through which the market of express postal services had gone and the possibilities of further development, both on the global and local level. The aim of this paper is to complete an estimation of the need for this type of express services using the competitive Lotka–Volterra model in Serbia. In order to reduce the complexity of the process, the division of competition was conducted in two segments: the public operator and the private segment (comprised of all private operators). The given model provides a description of a dynamic competition relationship by indicating the existence of the equilibrium point between the public and the private sectors, and the conditions of its stability. The obtained values indicate that the private sector affects the public operator. The existing predator-prey relationship gives preference to the private sector and can be described by the Lotka-Volterra model.

For economic evaluation of a highway development project, multiple criteria must be considered on a timeframe longer than the project implementation interval and a geographical area larger than the project zone. In this study, a framework is proposed based on the Network-Level Life Cycle Cost Analysis (NL-LCCA) to assess the effect of highway development projects on mobility, safety, economy, environment and other monetizable criteria. In this approach, project impacts are estimated within physical boundaries of highway network over the network life cycle. This framework can be used as a decision-making support for evaluation and ranking of pre-defined development projects, proposing new cost-effective development projects, assessment of cost efficiency of existing highway network and budget allocation optimization.

The aim of this paper is to determine, based on conducted marketing research, the level of passenger satisfaction with public transport services for the purpose of making better marketing decisions in the example of the City of Belgrade. The main task is to test the hypothesis on the existence of significant influence of factors, such as quality service, attitude and behaviour of employees (e.g. driver), adequate informing, quality of vehicles, line routes and timetable, on passenger satisfaction. Correlation coefficient and regression analysis were used for interpreting the obtained results and examining the formulated hypothesis. Empirical research has shown that there is a significant correlation between the aforementioned factors and passenger satisfaction with public transport services. The obtained results provided recommendations and guidelines for improving and increasing the quality of public transport services. The research results also provide the basis for future research that could examine the relationship between passenger satisfaction with services and sub-groups within the analyzed factors.

A typical trait of public transport is a spatially scattered demand. A route net that is operated by a carrier (or several carriers) has to be adapted to the demand. Public transport vehicles that are not used during a period of a day are usually parked in defined parking lots that have a given capacity. When the vehicle goes from the place where its schedule ends (usually a terminus of the last connection served by the vehicle) to the place where the vehicle should be parked, a non-productive journey occurs. The same occurs at the beginning of the vehicle schedule as well. The main goal of the paper is to present a mathematical model that enables minimization of the total length of all the non-productive journeys. Functionality of the proposed mathematical model was tested in the conditions of a real bus public transport network.

The paper discusses theoretically and examines empirically the influence of the relationship commitment on collaborative behaviour in supply chains. In today’s unstable business environment companies should collaborate to achieve mutual goals and competitive advantage. Defining relationship commitment and collaboration in supply chains (from social exchange theory point of view) is the basis of the research of this paper. Our aim is to examine the influence of relationship commitment on collaboration in supply chains in Slovenian economy. The qualitative research part discusses if the relationship commitment between partners in supply chain influences the collaborative behaviour between partners and which are the antecedents of relationship commitment. The research is based on a quantitative analysis of the online questionnaire survey made on the Slovenian economy. The research results show strong influence of trust and relationship commitment on collaboration between partners in supply chains.

The braking rate and train arresting operation is important in the train braking performance. It is difficult to obtain the states of the train on time because of the measurement noise and a long calculation time. A type of Group Stochastic M-algorithm (GSMA) based on Rao-Blackwellization Particle Filter (RBPF) algorithm and Stochastic M-algorithm (SMA) is proposed in this paper. Compared with RBPF, GSMA based estimation precisions for the train braking rate and the control accelerations were improved by 78% and 62%, respectively. The calculation time of the GSMA was decreased by 70% compared with SMA.

Throughout the history, the transportation of goods and related logistics have played an important role in human development and existence. This pertains to numerous interlinked processes, whose management is often linked to social system, international linkages, development of industry, market and market specifics. In modern times, the management of these processes is increasingly bound to globalization of production and market, moving of production to countries with cheaper labour force, environmental protection. The present Slovenian economy depends to a large extent on economies and corporate relations of the European Union and the world. Such inter-connectedness demands frequent transportation of semi-finished and finished goods. By providing timely delivery of goods, transportation consequently enables inter-organizational linkages and individual production, economic, market and other processes. Organizational and inter-organizational management of transport logistics demands profound understanding of transport flows, freight forwarding expertise and knowledge of transport, tax, environmental and other related regulations. Adequate knowledge and mastering of cultural, linguistic, national and other differences is important as well. The presented analysis and evaluation form the basis of the construction of inter-organizational model of logistics management in Slovenia.