Increased attention has been given to promoting e-bike usage in recent years. However, the research gap still exists in understanding the effects of spatial interdependence on e-bike choice. This study investigated how spatial interdependence affected the e-bike choice. The Moran’s I statistic test showed that spatial interdependence exists in e-bike choice at aggregated level. Bayesian spatial autoregressive logistic analyses were then used to investigate the spatial interdependence at individual level. Separate models were developed for commuting and non-commuting trips. The factors affecting e-bike choice are different between commuting and non-commuting trips. Spatial interdependence exists at both origin and destination sides of commuting and non-commuting trips. Travellers are more likely to choose e-bikes if their neighbours at the trip origin and destination also travel by e-bikes. And the magnitude of this spatial interdependence is different across various traffic analysis zones. The results suggest that, without considering spatial interdependence, the traditional methods may have biased estimation results and make systematic forecasting errors.

Road freight transport often requires the prediction of volume. Such knowledge is necessary to capture trends in the industry and support decision making by large and small trucking companies. The aim of the presented work is to demonstrate that application of some artificial intelligence methods can improve the accuracy of the forecasts. The first method employed was double exponential smoothing. The modification of this method has been proposed. Not only the parameters but also the initial values were set in order to minimize the mean absolute percentage error (MAPE) using the artificial immune system. This change resulted in a marked improvement in the effects of minimization, and suggests that the variability of the initial value of S2 has an impact on this result. Then, the forecasting Bayesian networks method was applied. The Bayesian network approach is able to take into account not only the historical data concerning the volume of freight, but also the data related to the overall state of the national economy. This significantly improves the quality of forecasting. The application of this approach can also help in predicting the trend changes caused by overall state of economy, which is rather impossible when analysing only the historical data.

Driving comfort is of great significance for rural highways, since the variation characteristics of driving speed are comparatively complex on rural highways. Earlier studies about driving comfort were usually based on the actual geometric road alignments and automobiles, without considering the driver’s visual perception. However, some scholars have shown that there is a discrepancy between actual and perceived geometric alignments, especially on rural highways. Moreover, few studies focus on rural highways. Therefore, in this paper the driver’s visual lane model was established based on the Catmull-Rom spline, in order to describe the driver’s visual perception of rural highways. The real vehicle experiment was conducted on 100 km rural highways in Tibet. The driving rhythm was presented to signify the information during the driving process. Shape parameters of the driver’s visual lane model were chosen as input variables to predict the driving rhythm by BP neural network. Wavelet transform was used to explore which part of the driving rhythm is related to the driving comfort. Then the probabilities of good, fair and bad driving comfort can be calculated by wavelets of the driving rhythm. This work not only provides a new perspective into driving comfort analysis and quantifies the driver’s visual perception, but also pays attention to the unique characteristics of rural highways.

This paper provides a description of driver testing in a simulator. As young drivers are more susceptible to collisions, this was done to determine how young drivers behaved in simulated road situations on a motorway. One of the traffic safety concerns is the failure to keep a proper distance from the vehicle in front, which may result in a rearend collision. The tests simulated car-following situations in which the preceding vehicle performed emergency braking. The experiments were conducted for two scenario variants using different distances from the vehicle in front. The drivers could perform the following emergency manoeuvres: braking with steering away or only braking. The driver response times were compared and analysed statistically. The results were used to determine the emergency manoeuvres performed by the drivers in the simulated road situations. The study reveals that the vehicle surroundings may have a considerable influence on the type of emergency manoeuvres and the driver response time.

Due to the increase of congestion on highways, providing real-time information about the traffic state has become a crucial issue. Hence, it is the aim of this research to build an accurate traffic speed prediction model using symbolic regression to generate significant information for travellers. It is built based on genetic programming using Pareto front technique. With real world data from microwave sensor, the performance of the proposed model is compared with two other widely used models. The results indicate that the symbolic regression is the most accurate among these models. Especially, after an incident occurs, the performance of the proposed model is still the best which means it is robust and suitable to predict traffic state of highway under different conditions.

This paper presents the scheduling models for train
platforming problem (TPP) by using mixed integer linear programming and job shop scheduling theory. First, the operation procedures and scheduled time adjustment costs of different train types specific to busy complex passenger stations are explicitly represented. Second, a multi-criteria scheduling model (MCS) for TPP without earliness and tardiness time window (ETTW) and a time window scheduling model (TWS) with ETTW for TPP are proposed. Third, various dispatching rules were designed by incorporating the dispatcher experiences with modern scheduling theory and a rule-based metaheuristic to solve the above model is presented. With solution improvement strategies analogous to those used in practice by dispatchers, the realistic size problems in acceptable time can be solved.

The purpose was to investigate the interrelation between the age of older city bus users, their travelling habits, their estimated physical (dis)abilities and perceived safety during the trip using the Ljubljana public transportation system. Methods: 101 older bus users agreed to participate in a street survey by answering a questionnaire. Results indicate that the habits of bus users are not age dependent. The frequency of public bus use, the walking distance to the nearest bus stop, the estimated physical abilities and perceived physical limitations of the bus users were not associated to the chronological age. Respondents reported on average 3±1.6 perceived physical limitations and 37% of them perceived their travelling habits to be affected by their physical limitations. While decreased perceived safety during the bus journey was significantly related to the chronological age: significantly more bus users of the oldest-old group reported not having enough time to occupy a seat before the bus drove off, although a significantly higher proportion of older-old adults were offered a seat by their fellow travellers. In conclusion, the perception of physical fitness and health problems are more important contributing factors for the use of public transportation than the chronological age.

There are several possible bus stop locations and configurations. A bus stop can be located before or after the intersection as curb-side stop, bus bay or bus bulb. Determining the proper configuration and location of bus stop represents an important planning decision. While previous research efforts in literature have suggested some advantages and disadvantages regarding bus stop locations and configurations, little effort has been made towards understanding the joint impact of bus stop location and configuration on the transit and other vehicle traffic performance on the intersection. So, this paper analyses the joint impact of bus stop location and configuration on the operational characteristics of traffic flow in terms of average bus trip time and control delay. These operational performance measures for various intersection layouts, volume distributions, movement splits, average bus dwell times and bus departure frequencies have been obtained using calibrated microsimulation traffic software.

The transport system causes extremely harmful consequences for society and the environment. It is manifested through the increased emission of harmful exhaust gases, traffic congestions, traffic accidents, increased level of noise, higher levels of stress and various diseases of all participants of the transport system and society in general. The implementation and modernization of intermodality through the Motorways of the Sea (MoS) as its ecological and socio-economic sustainable subsystem is the efficient way of reducing the above mentioned consequences. Further sustainable development of MoS can be observed according to the ecological and socio-economic criteria and sub-criteria set out in this paper in order to keep it in direct function of protecting the society and preserving the environment.

The paper focuses on analysis of the effect of various surveys and inspections on the psychophysical behaviour of the crew. After analysing the scope and the extent of each regime, the authors identified more than 60% of surveys overlapping each other. Furthermore, the results of the survey conducted among seafarers indicate that the present method of carrying out ship surveys and inspections have a negative effect on the psychophysical condition of the crew. Therefore, a new method of tanker inspections has been proposed in order to reduce the psychophysical strain of the crew. The proposed method would minimise the annual duration of the inspections up to 30% and improve inspection time coordination without compromising quality and safety of the ships.

The growing trend of natural resources consumption has caused irreparable losses to the environment. The scientists believe that if environmental degradation continues at its current pace, the prospect of human life will be shrouded in mystery. One of the most effective ways to deal with the environmental adverse effects is by implementing green supply chains. In this study a multilevel mathematical model including supply, production, distribution and customer levels has been presented for routing–location–inventory
in green supply chain. Vehicle routing between distribution centres and customers has been considered in the model. Establishment place of distribution centres among potential places is determined by the model. The distributors use continuous review policy (r, Q) to control the inventory. The proposed model object is to find an optimal supply chain with minimum costs. To validate the proposed model and measure its compliance with real world problems, GAMS IDE/Cplex has been used. In order to measure the efficiency of the proposed model in large scale problems, a genetic algorithm has been used. The results confirm the efficiency of the proposed model as a practical tool for decision makers to solve location-inventory-routing problems in green supply chain. The proposed GA could reduce the solving time by 85% while reaching on the average 97% of optimal solution compared with exact method.