Most of the microscopic traffic simulation programs used today incorporate car-following and lane-change models to simulate driving behaviour across a given area. The main goal of this study has been to develop an automatic calibration process for the parameters of driving behaviour models using metaheuristic algorithms. Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and a combination of GA and PSO (i.e. hybrid GAPSO and hybrid PSOGA) were used during the optimization stage. In order to verify our proposed methodology, a suitable study area with high bus volume on-ramp from the O-1 Highway in Istanbul has been modelled in VISSIM. Traffic data have been gathered through detectors. The calibration procedure has been coded using MATLAB and implemented via the VISSIM-MATLAB COM interface. Using the proposed methodology, the results of the calibrated model showed that hybrid GAPSO and hybrid PSOGA techniques outperformed the GA-only and PSO-only techniques during the calibration process. Thus, both are recommended for use in the calibration of microsimulation traffic models, rather than GA-only and PSO-only techniques.

More than 13.7 million people in Taiwan are scooter users, which signifies the highest density of scooter users in the world. The aim of the present study is to use the user experience (UX) evaluation methods to investigate the factors that influence the users’ satisfaction, recommendation intention, and willingness to accommodate Electric two-wheelers (E2Ws). An online survey design has been used to recruit two-wheeler owners who live in Taiwan. The results of the hierarchical multiple regression analysis, based on a sample of 315 Taiwanese, indicate that the variables of satisfaction, positive emotions, and riding experience predicted whether users intended to recommend a two-wheeler. The results also reveal that external motivation is the core factor that influences a rider’s willingness to purchase an E2W. It highlights the importance of providing opportunities for people to experience the advantages of E2Ws and services. Having good hedonic and pragmatic experiences accumulated during two-wheeler usage may further positively influence the users’ satisfaction and intrinsic motivation. It is recommended that the government and the related industries consider the above issues when formulating related policies or developing E2W or battery technologies.

In order to satisfy the requirements of International Civil Aviation Organization (ICAO) for aircraft taxi route planning in Advanced Surface Movement Guidance and Control System (A-SMGCS), an airport surface operation modelling and simulation approach based on timed and coloured Petri net is presented. According to the layout of the airport surface and the features of surface operation units, a static Petri net model of the airport surface is established. On this basis, in line with the requirements on the aircraft taxiing velocity in ICAO DOC 9830, the dynamic Petri net model of the airport surface operation is established by adding the time attribute to the static model. Additionally, the method of defining the capacity of airport operation unit place is proposed and the constraints of the airport surface operation are incorporated using Petri net elements. Unlike other papers in the field, the airport surface Petri net model established in this paper can simulate conflict-free taxiing using a Petri net simulator without relying on other model-independent algorithms. Based on the CPN Tools software, taking Toulouse Airport as an example, the validity of the model has been verified by comparing the model running data with real flight data.

Providing a satisfying delivery service is an important way to maintain the customers’ loyalty and further expand profits for manufacturers and logistics providers. Considering customers’ preferences for time windows, a bi-objective time window assignment vehicle routing problem has been introduced to maximize the total customers’ satisfaction level for assigned time windows and minimize the expected delivery cost. The paper designs a hybrid multi-objective genetic algorithm for the problem that incorporates modified stochastic nearest neighbour and insertion-based local search. Computational results show the positive effect of the hybridization and satisfactory performance of the metaheuristics. Moreover, the impacts of three characteristics are analysed including customer distribution, the number of preferred time windows per customer and customers’ preference type for time windows. Finally, one of its extended problems, the bi-objective time window assignment vehicle routing problem with time-dependent travel times has been primarily studied.

In order to improve the transfers inside an Urban Rail Transit (URT) station between different rail transit lines, this research newly develops two Ordinal Logistic Regression (OLR) models to explore effective ways for saving the Perceived Transfer Time (PTT) of URT passengers, taking into account the difficulty of improving the transfer infrastructure. It is validated that the new OLR models are able to rationally explain probabilistically the correlations between PTT and its determinants. Moreover, the modelling analyses in this work have found that PTT will be effectively decreased if the severe transfer walking congestion is released to be acceptable. Furthermore, the congestion on the platform should be completely eliminated for the evident reduction of PTT. In addition, decreasing the actual transfer waiting time of the URT passengers to less than 5 minutes will obviously decrease PTT.

As part of an overall traffic signalling system, traffic signs warn the traffic participants, give information about the restrictions, prohibitions and obligations and provide additional information needed for a safe and undisturbed traffic flow. The traffic sign quality is expressed by its retroreflection and it is particularly pronounced in conditions of reduced visibility. The aim of this paper is to analyse how traffic signs quality affects the frequency of traffic accidents in low visibility conditions. For this purpose, traffic accidents and the quality of traffic signs were analysed on 130 state roads in the Republic of Croatia between 2013 and 2015. In the analysis several variables were used: the number of traffic accidents occurred under reduced visibility conditions, length of the road, AADT (Annual Average Daily Traffic) and the number of traffic signs that do not meet the minimum prescribed values of retroreflection. Statistical analysis showed a positive correlation between the accidents and unsatisfactory traffic signs, i.e. that with the increase in the number of traffic sings that do not have a satisfactory level of retroreflection, an increase in the number of accidents in reduced visibility conditions is expected.

Choosing an optimal bunkering port that minimises the increase in the operating costs in a hub and spoke system is a multi-criteria decision-making (MCDM) problem. Furthermore, the criteria are related to the port particularities, the environment, fuel price, and some criteria are quantitative while others are qualitative. It is therefore necessary to create a model that takes such features into consideration. Firstly, in this paper a set of the most used criteria will be defined. Then, a method to choose suitable criteria for a hub and spoke system will be proposed. Secondly, using a Fuzzy AHP, weights will be defined and used in a multi-criteria goal function. The outcome is a bunkering policy MCDM model based on the aggregation of fuel consumption and price to criteria related to port characteristics, local aspects and service particularities. All these factors must be considered by a chief engineer (superintendent) in the process of defining a sustainable bunker policy. A case study based on the North Adriatic port system demonstrates the applicability of the proposed model. In addition, the case study highlights that in hub and spoke systems with short loops, feeder ships can regulate cargo capacity and stay at a port with bunkering policy planning.

The aim of the system with reservations is to reduce the time the user needs to reach the parking space as well as to rationalize the controlling of demands in the central business districts. When applying the system with reservations, it is necessary to know the user’s travel time to the parking space, as well as the time of parking. The sum of these two periods represents the parking space “occupancy”. The purpose of this paper is to suggest a model for determining the total occupancy of a parking space based on 1) the user’s travel time to the parking space; 2) the user’s duration of parking. Considering the fact that we are dealing with values which cannot be exactly estimated, the fuzzy logic system (FLS) is used. A Neural Network (NN) is trained on the basis of data about the estimated values of the input parameters and the real value of output parameters. Thus, a hybrid model of fuzzy logic and neural networks (ANFIS) is obtained. Finally, there is an example based on the real data which shows the application possibilities of this model.

The paper introduces a framework to perform the demand management and route planning tasks of a highly developed transport system managing scheme, assuming an autonomous transport system. Two types of autonomous transport system managing models have been introduced. In case of the first model, the assigned number of trips is assumed to be the modified variable related to the optimization problem. In case of the second model, the decision process is directly influenced by the travel prices defined by the optimization method. These approaches represent different demand management strategies. The first model aims to directly assign the incoming user demands to the system, while the second procedure lets the users make the decision. However, in the second case the system can strongly influence the users’ choices through the values of the travel prices. Accordingly, it seems to be a reasonable assumption that the firstly presented model has significantly higher efficiency in distributing the load on the network. On the other hand, the method of the second model would be much more tolerable and acceptable from a social point of view. Therefore, the aim of the paper is to introduce the developed models and to compare their efficiencies.

The paper presents the methodology for the risk analysis of the road transport of dangerous goods. The risk analysis includes the societal risk for communities living or staying within a radius of six kilometres from all national roads in Poland. The GIS software was employed to make this analysis. The prepared matrix has included the product of the likelihood of a road accident involving explosive dangerous goods and the consequences for communities living in the abovementioned area. The likelihood analysis was developed for explosive and toxic dangerous goods. The consequence analysis was based on the population density, according to which a respective number of people was assigned to each building, depending on the time of day (daytime, nighttime). Each stage of the analysis was presented in the form of a map. In total, two variants of the likelihood analysis, four variants of the consequence analysis and four variants of risk analysis have been developed. All analyses have been developed for the entire country.

Cilj ovog istraživanja je utvrditi koji stavovi o pokazateljima sigurnosne izvedbe utječu na stavove o uspješnosti provođenja ISM Pravilnika među suvremenim pomorcima. Uz navedeno, cilj istraživanja bio je dobiti uvid u stavove pomoraca prema trenutnom stanju ISM implementacije i stanju sigurnosti. Slijedom toga, uzorak od N = 330 pomoraca ispitan je u svojim stavovima prema varijablama sigurnosti i primjeni ISM koda. Korištenjem višestruke regresijske analize zaključeno je da dobro oblikovana i strukturirana sigurnosna pravila i postupci, pozitivna radna okolina i odgovarajuća komunikacija mogu značajno doprinijeti stavovima pomoraca o provedbi ISM-a.

Ključne riječi: sigurnosna izvedba, provedba ISM Pravilnika, višestruka regresijska analiza