Young drivers represent the most vulnerable age group at risk of participating in traffic accidents. In order to reduce the occurrence of traffic accidents involving young drivers, various models for assessing the risk of accidents have been studied. Inexperience, lack of driving skills and risky behaviour in traffic are the main characteristics of traffic accidents involving young adult drivers. On the contrary, traffic accidents involving older adult drivers are characterised by reduced visual and cognitive stimuli and reduced mobility. Based on the data about traffic accidents from the available databases relevant for road traffic safety in the Republic of Kosovo over a four-year period, the road characteristics that caused the majority of traffic accidents involving young adult drivers and the subjective  and objective factors that affected the occurrence of traffic accidents the most have been defined. To conclude the research, a correlation has been defined between objective and subjective factors that increase the risk of traffic accidents, as well as the  frequency of single safety factors (human, vehicle, road and environment) in traffic accidents involving young adult drivers.

Energy conservation and emission reduction from the transportation sector are of great significance in coping with the global energy and environmental crisis. As the bottleneck of urban road traffic, intersection burdens the urban environment greatly. When the volume of left-turn traffic is large, the continuous flow intersection (CFI) can effectively improve intersection operation efficiency. This paper first put forward the definition and application conditions of CFI. Then its mechanism for energy saving and emission reduction was analysed. CFI transformation was designed taking a typical intersection in Xi’an as an example. Operating efficiency, energy consumption and emissions of the intersection before and after CFI transformation were evaluated using the VISSIM model. The  results show that energy consumption and emissions in the intersection are greatly reduced after CFI transformation. Queue length is reduced by more than 41%. Energy consumption and pollutant emission are reduced by about 8%. Through the simulation analysis, the emission reduction benefits most when the volume of left-turn traffic is 80%–85% of the design capacity, and the ratio of leftturn
traffic over through traffic is maintained between 50% and 100%. This study suggests that CFI is suitable for large-scale promotion with careful examination.

Deviations in driving time (DT), or significant variations, occur frequently on urban public transport (PT) lines, except in subsystems with separate routes. DT variability is the main reason for disturbances in operation, leading to unstable and unreliable transport service. Moreover, it also causes variability in total user travel time, which is one of the main parameters of transport service quality. Identifying and quantifying factors that influence PT vehicle DT characteristics is significant for designing advanced prediction and  passenger information systems and prioritising investments to reduce bus travel time and improve the scheduling process, and thus the level of transport service quality. An analysis of the elements of the route and other static elements of the line that influence DT was carried out in this paper. A model for determining and quantifying influential factors and methodologies for collecting all necessary data was created. The multiple regression model, developed as a result of the conducted multivariate statistical analysis using the specialised SPSS software, was applied to the selected representative set of lines in a real urban PT system. The created regression model explains between 18.2% and 97.4% of the variance of average, minimum and maximum DT and its deviation in the peak and off-peak periods.

In order to promote the modernisation process of rural roads and improve road capacity, the problem of bottleneck sections of rural roads needs to be solved urgently. The phenomenon of wide-road-and-narrow-bridge sections is particularly prominent in rural roads. Based on this, this paper analyses the degree of influence of roadway one-way lane width, bridge deck oneway lane width, motorised vehicles to non-motorised vehicles ratio, and road-bridge connection dimension on the capacity of the wide-road-and-narrow-bridge section based on the combination of VISSIM simulation and random forest algorithm. The result of the coefficient of determination (R2) of the random forest-based capacity prediction model shows that the random forest fits the data very well; the degree of influence on the capacity is in descending order of the bridge deck one-way lane width, motorised vehicles to non-motorised vehicles ratio, roadway one-way lane width and the road-bridge connection dimension. The model can, on the one hand, provide a reference for  improving the capacity of bottleneck sections of rural roads; on the other hand, it can provide decision value for the order of measures to be taken when rural roads are rebuilt and expanded, according to the order of importance.

The purpose of this research is to investigate the effect of land use, built environment and public transportation facilities’ locations on destinations of bike-sharing trips in an urban setting. Several methods have been applied to determine the relationship between predicting variables and trip destinations, such as ordinary least squares regression, spatial regression and geographically weighted regression. Additionally, a comparison between the proposed models, count models and random forest has been conducted. The data were collected in Budapest, Hungary. It has been found that touristic points of interest, and healthcare and educational points have a positive impact on bike-sharing destinations. Public transportation stops for buses, trains and trams attract bike-sharing users, which has a potential for the bike-and-ride system. Land use has different effects on bike-sharing trip destinations; mostly as a circular shape variation within the urban structure of the city, such as residential, industrial, commercial and educational zones. Other variables, such as road length and water areas, form as constraints to bike-sharing trip destinations. Geographically weighted and spatial regression performs better than count models and random forest. This study helps decision-makers in predicting the origin-destination matrix of bike-sharing trips based on the transportation network and land use.

Drivers show different characteristics in traffic oscillations. These differences reflect the driver’s driving style, which is an important part of traffic uncertainty. This paper deeply explores the driving characteristics in asymmetric driving behaviour and its influence on traffic flow characteristics. The aim is to improve the understanding of safe driving. Continuous vehicle trajectories under various traffic flow conditions in an expressway merging area are obtained by aerial photography. Image processing technology is used to extract the basic parameters of traffic flow and vehicle operating characteristic data. Based on the measured data, the driver’s response mode is subdivided into multiple sub-modes. On the basis of this study, the types and distribution of traffic hysteresis and the impact of asymmetric behaviour on merging area capacity are further revealed. The results show that the response coefficient will increase for 58.72 % drivers during the process of experiencing oscillation disturbance to rebalance. The traffic hysteresis caused by driver’s asymmetric following behaviour in an expressway merging area is generally positive. This reduces the bottleneck outflow rate of the merging area by about 7 % on average. This study has important practical significance in analysing the formation mechanism of traffic congestion and adopting effective protective measures.

The emerging seaport-inland port dyad contributes greatly to the development of seaport hinterlands. However, little research has examined its influence on container hinterland delimitation. This paper used an improved radiation model to study the effects of seaport-inland port dyads on the container seaport hinterland delimitation in the context of a Chinese multi-port system. The radiation of each seaport was estimated to track changes in the seaport superior hinterlands and hinterland ratings and discover the patterns of the effects. The results show that the formation of dyads expands the scope of superior hinterlands and improves the hinterland ratings of seaports. The provinces close to inland ports and far from seaports were significantly affected and the same inland port influenced seaports differently. These results demonstrate that establishing a seaport-inland port dyad is a good way to compete with other seaports for larger market shares. These different effects can serve as a guideline for seaport authorities to choose suitable dyads to achieve their hinterland targets.

With the rapid development of urban rail transit (URT) in China, a contradiction between high costs and low passenger demand becomes prominent. Complete analysis of the impacts of passenger demand on the profitability of URT can be difficult to conduct, due to the multifaceted impact of passenger demand with multidimensional characteristics. To this end, we propose a strategy that helps to analyse the profitability of different types of URT, taking into account the spatial and temporal characteristics of demand. Based on data of the Shunde (SD) district in China, the profitability of metro, light rail transit (LRT), monorail and tram was evaluated. Results show the profitability under different demand levels. Tram might be the best choice at low demand levels. At medium demand levels, LRT and monorail are competitive. At high demand levels, LRT with medium to high capacity and low cost is a good alternative to metro, though the capacity of metro is higher. Utilizing the URT with high capacity under insufficient demand can aggravate the burden of depreciation, and make it hard to achieve profit. The spatial characteristics of the demand described in this paper reflect the problem of insufficient demand in marginal areas due to the diversified construction of URT.

The container terminal handling system plays an important role in marine transportation, and improving its efficiency has become a big challenge. Therefore, this paper proposes an analytical method that combines a Petri net with simulation tools. Firstly, the container terminal handling system is abstracted into a Petri net system according to the internal logic of the handling process. Next, eigenvalues of the correlation matrix are calculated to analyse the effectiveness of the Petri net system. Then, the Petri net system is simulated using the Extend-Sim software. The result suggests that, after optimising, the handling capacity of the berth is clearly improved. Using the Petri net and simulation tools together to analyse the container terminal system is the innovation and the most important aspect of this paper. Because the combination of a Petri net and simulation can not only ensure the reliability of the model but also optimise the container terminal handling system more intuitively.