Timetable stability depends on the regularity of trains. Any deviation from the planned timetable leads to its instability. Railway network characteristics determine the capacities of the transport service. Depending on the capacity calculation method, time components are added to the minimum headway to ensure timetable stability. The UIC 405 method is simple and can be used on all railways. The disadvantage is that the calculations are based on average data. According to the method, the minimum headway consists of the time of the average headway interval, additional time and the buffer time. The additional time is precisely defined by the number of APB sections, while the buffer time is in the average value. When creating the timetable, the goal is optimal utilisation of the infrastructure. If the headway is too long, the capacity is not used, and if it is too short, timetable instability will ensue. Instead of averaging, this work calculates a buffer time that depends on the ratio of the travel time of the previous and the following trains. In this way, the headway is optimised and the calculation of the UIC 405 method is improved.

Physiological signal index can accurately reflect the degree of fatigue, but the contact detection method will greatly affect the driver's driving. This paper presents a non-contact method for detecting tired driving. It uses cameras and other devices to collect information about the driver's face. By recording facial changes over a period and processing the captured video, pulse waves are extracted. Then the frequency domain index and nonlinear index of heart rate variability were extracted by pulse wave characteristics. Finally, the experiment proves that the method can clearly judge whether the driver is tired. In this study, the Imaging Photoplethysmography (IPPG) technology was used to realise non-contact driver fatigue detection. Compared with the non-contact detection method through identifying drivers' blinking and yawning, the physiological signal adopted in this paper is more convincing. Compared with other methods that detect physiological signals to judge driver fatigue, the method in this paper has the advantages of being non-contact, fast, convenient and available for the cockpit environment.

Urban transport system planning has been moving towards sustainability in recent years, and the concept of urban freight logistics is an integral part of this planning. Urban freight logistics involves many stakeholders that participate in its operation and should be considered in the system planning process. The paper presents one of the approaches to the methodology for the selection of key indicators suitable for the evaluation and monitoring of a sustainable system of urban freight logistics in such a way that it reflects as much as possible the needs of all involved stakeholders. This is done by applying the selected method of multi-criteria analysis with the involvement of various urban freight logistics stakeholders. Based on the proposed methodology, the paper defines significant indicators that can be considered for further evaluation of the level of a sustainable urban freight logistics system. In addition to the possibilities of further development of this methodology, the application of determined significant indicators for calculating the proposed index of sustainable urban freight logistics is discussed. The proposed procedure can be implemented in the preparatory steps in the framework of the creation of sustainable urban logistics plans (SULPs).

For urban extra-long underwater tunnels, the obstacle space formed by the tunnel walls on both sides has an impact on the driver's driving. The aim of this study is to investigate the shy away characteristics of drivers in urban extra-long underwater tunnels. Using trajectory offset and speed data obtained from real vehicle tests, the driving behaviour at different lanes of an urban extra-long underwater tunnel was investigated, and a theory of shy away effects and indicators of sidewall shy away deviation for quantitative analysis were proposed. The results show that the left-hand lane has the largest offset and driving speed from the sidewall compared to the other two lanes. In the centre lane there is a large fluctuation in the amount of deflection per 50 seconds of driving, increasing the risk of two-lane collisions. When the lateral clearances are increased from 0.5 m to 2.19 m on the left and 1.29 m on the right, the safety needs of drivers can be better met. The results of this study have implications for improving traffic safety in urban extra-long underwater tunnels and for the improvement of tunnel traffic safety facilities.

It is generally known that traffic safety is influenced by humans, vehicles, and roads. Nowadays, when new technologies have taken over a large part of the traffic industry, the selection of relevant software, whose competition is great, presents a big problem for the decision-maker. Intelligent systems, such as Motion, SCOOT, and SCATS, are used for the implementation of a control strategy in order to manage signals on the traffic network, with the goal of increasing efficiency and traffic safety. These systems operate on the demand-responsive principle and have logic for traffic optimization which represents their main difference along with the optimization subject and method of the system functioning. The research included consideration of mentioned differences, software, and hardware architecture that have a significant impact on the system’s functionality since the detector’s locations themselves depend on the optimization subject. The implementation benefits are considered through the existing world’s projects. Based on the obtained data, the criteria used for the comparative analysis of these three systems were defined, from the aspect of traffic safety.

Although computer vision-based methods have seen broad utilisation in evaluating traffic situations, there is a lack of research on the assessment and prediction of near misses in traffic. In addition, most object detection algorithms are not very good at detecting small targets. This study proposes a combination of object detection and tracking algorithms, Inverse Perspective Mapping (IPM), and trajectory prediction mechanisms to assess near-miss events. First, an instance segmentation head was proposed to improve the accuracy of the object frame box detection phase. Secondly, IPM was applied to all detection results. The relationship between them is then explored based on their distance to determine whether there is a near-miss event. In this process, the moving speed of the target was considered as a parameter. Finally, the Kalman filter is used to predict the object's trajectory to determine whether there will be a near-miss in the next few seconds. Experiments on Closed-Circuit Television (CCTV) datasets showed results of 0.94 mAP compared to other state-of-the-art methods. In addition to improved detection accuracy, the advantages of instance segmentation fused object detection for small target detection are validated. Therefore, the results will be used to analyse near misses more accurately.

In recent years several projects have been realised in the field of transportation, but there is a lack of systematic analysis of research challenges connected to these projects. Thus, the main aim of this paper is to provide an overview of these challenges through EU funded projects in the field of smart, green and integrated transport. Based on EU strategic documents, reports and roadmaps, 10 topics are identified playing a crucial role in transportation-related research. A systematic analysis of the projects is realised, where the projects collected from an online database in the Horizon 2020 framework programme from 2015 to 2020 are categorised into these topics. The results show that travel behaviour, big data and open data, sustainable mobility planning and smart solutions are covered by several projects which reflect the main research trends. While active and shared modes, multimodal transportation, trip optimisation and Mobility as a Service are also popular topics. Based on the results, the most underrepresented research areas are artificial intelligence and social networks. The analysis of the connections between the research topics could enable the achievement of a long-term paradigm shift in urban mobility, which is beneficial for researchers, professionals and policy makers.

Aiming at the lack of an anti-clogging ability index in the road network traffic evaluation index, an anti-clogging ability index was proposed to measure the anti-clogging ability of urban road traffic network: Κ-anti-clogging coefficient, which is used to measure the shortest path between any pair of starting and ending points on the urban road traffic network. After the current edge of the shortest path is blocked, the shortest path is selected from the current node of the shortest path. If the current edge of the shortest path is blocked again, the selection continues until the shortest path to the ending point is selected. In the case of unrecoverable congestion, the properties of the anti-clogging coefficient vector on any origin-destination pair, a path, and the whole traffic network are analysed, and the algorithm of the anti-clogging coefficient and its complexity are given. Finally, an example analysis is carried out using a local traffic network in a city.

Fatigue detection based on vision is widely employed in vehicles due to its real-time and reliable detection results. With the coronavirus disease (COVID-19) outbreak, many proposed detection systems based on facial characteristics would be unreliable due to the face covering with the mask. In this paper, we propose a robust visual-based fatigue detection system for monitoring drivers, which is robust regarding the coverings of masks, changing illumination and head movement of drivers. Our system has three main modules: face key point alignment, fatigue feature extraction and fatigue measurement based on fused features. The innovative core techniques are described as follows: (1) a robust key point alignment algorithm by fusing global face information and regional eye information, (2) dynamic threshold methods to extract fatigue characteristics and (3) a stable fatigue measurement based on fusing percentage of eyelid closure (PERCLOS) and proportion of long closure duration blink (PLCDB). The excellent performance of our proposed algorithm and methods are verified in experiments. The experimental results show that our key point alignment algorithm is robust to different scenes, and the performance of our proposed fatigue measurement is more reliable due to the fusion of PERCLOS and PLCDB.

Cities located on a path of intercity railroads tend to be in a corridor system to increase commerce and economic profits. Theoretic and practical work concerning train station locations can be used to provide factors that affect the choice of train station sites. In this paper, we find optimal places to locate train stations according to location theories and particular natural and socioeconomic characteristics. The methods we used are focused on maximising users’ economic profits associated with passenger and cargo transportation by finding optimal stations on the route. Furthermore, we created a general algebraic modelling system (GAMS) with linear planning, which is solvable using a C programming language (CPLEX) interactive optimiser. Case studies on 14 stations along the 820 km long Milak-Chabahar corridor helped us to simulate our model and test its feasibility at three alternative times to prove the outcomes. The stations would increase an average profit of 38.6%, 42.94% and 50.85%, but the growth varied in the stations. This research contributes to freight and passenger transportation engineers in railroad design. They benefit from the model to determine the location of a train station to obtain maximum user profits in that station and its surrounding areas.

For organisations to take preventive measures and eliminate potential accidents, the information gained through voluntary reporting is essential. Employees do not, however, report voluntarily for a number of reasons. In this study, we examine why train drivers, who are vital to maintaining rail safety, fail to report hazardous occurrences, leading to employee silence. The measurement tool, which has already been developed specifically for aviation employees, has been applied to 346 train drivers working on Turkish Railways. The scale used for research purposes has proven to be valid and reliable for organisations involved in railways. As a result, it was determined that the drivers did not participate in voluntary reporting due to relational and prosocial, disengaged, quiescence and acquiescence and fear and defensive factors. The highest score for the reasons for non-reporting was observed in the dimension of quiescence and acquiescence. The results of the correlation analysis between dimensions, which are assumed to be the reasons for non-reporting, point to strong positive relationships between each dimension.

Vienna’s geostrategic importance fluctuated through the ages because of the power clashes and subsequent political and socio-economic impacts on the population. This paper assesses its current position in a historical context and then focuses more on the socio-economic dimensions such as interconnectedness and other transport aspects of the geostrategic position. Air and environmentally friendlier modes of passenger transport like high-speed rail are considered and analysed in the European context. This paper also reviews the results and issues dealing with the development of the Vienna Airport and the progress of high-speed railway projects in the Central European Economies (CEEs) after the European Union’s enlargement in 2004. The results suggest that after a restoration period of Vienna’s geostrategic position between 1995–2005, there is currently only a moderate and slowly growing exercise of power, control or influence over the CEEs. The results suggest that there is competition from busier German hub airports as well as the growing importance of CEE airports in transit and growing passenger transport performance figures. The lack of environmentally friendly high-speed infrastructure as a viable option instead of the fastest air travel is preventing Vienna to strengthen its strategic position. Its strategic importance is highly affected by the underdeveloped transport networks in CEEs and the future development of the Vienna Airport as a major transport hub.

To better utilise the service capacity of the limited facilities of a metro station, as well as ensure safety and transport efficiency during peak hours, a large passenger flow control plan is studied through theoretical analysis and numerical simulation. Firstly, by passenger data collection and data analysis, the characteristics of the inbound and outbound passenger flow of a T metro station are analysed. Secondly, AnyLogic evacuation simulation models for the T Station during peak hours, peak hours without/with passenger flow control are established based on real passenger flow data as well as the station structures and layouts by using the AnyLogic software. The results show that there are no obvious congestions in the station hall, and the travel delay is significantly reduced when effective passenger flow control measures are taken. By controlling the speed, direction and movement path of passengers, as well as adjusting the operation of escalators, entrances and automatic ticket-checking machines, passenger flow can become more orderly, transport efficiency can also be improved, and congestion in the station can be well mitigated.

This paper proposes a functional carriage design and an evaluation index system to improve the operational efficiency of high-speed medical trains. Hierarchical task analysis and human-machine-environment analysis were applied to model the transfer task and the functional modules of the medical train. The functional module configuration was obtained by performing a correlation analysis between the task and function. The relationship between carriages was elucidated by analysing material, personnel and information flow, and an optimal grouping diagram was obtained. Based on this design method, an innovative 6-carriage grouping design scheme was proposed. A functional evaluation index system for the carriage design was constructed, and the 6-carriage design was compared with the conventional 8-carriage design to verify the usability of the design method. The results showed that the 6-carriage high-speed trains can be flexibly configured to suit the changing task environment and are generally better than the 8-carriage design. This study provides theoretical and methodological support for constructing efficient and rational functional carriages for high-speed medical trains.

The paper concerns the method of determining the probability of unproductive manipulations during operations, maintenance or repairs on an inland intermodal terminal. The method is mathematically based on the semi-Markov process. The developed method enables revision of unproductive manipulation frequency and duration. It provides an opportunity to analyse and change inland terminal operations so as to increase productivity.

Tourism traffic has a considerable influence on the state of urban traffic in tourist cities. To consider tourism traffic demand in the division of conventional traffic analysis zones (TAZ), a spatial analysis method combining dynamic traffic state features with static land use and road network characteristics is proposed to define tourism traffic analysis zones (TTAZs). Taking Xiamen Island as an example, first, point of interest (POI) data for the tourism elements on Xiamen Island and kernel density estimation (KDE) are applied to determine the core zones impacted by tourism traffic. Second, within the impacted zones, this paper studies the dynamic distribution of the tourism traffic for peak hours during holidays and non-tourism period by employing spatial autocorrelation method based on floating car data (FCD) and determines the area of slow traffic agglomeration of tourism traffic. In view of the distribution of tourism infrastructure, land use, tourism traffic state distribution and road network, this study identified the characteristics of slow traffic agglomeration in the area near Siming Road and divided four TAZs into six TTAZs. By further dividing the urban TTAZs, this paper hopes to provide a reference for urban traffic planning and management, tourism planning and land use planning.

This paper focuses on the potential safety hazards of collision in car-following behaviour generated by deep learning models. Based on an intelligent LSTM model, combined with a Gipps model of safe collision avoidance, a new, Gipps-LSTM model is constructed, which can not only learn the intelligent behaviour of people but also ensure the safety of vehicles. The idea of the Gipps-LSTM model combination is as follows: the concept of a potential collision point (PCP) is introduced, and the LSTM model or Gipps model is controlled and started through a risk judgment algorithm. Dataset 1 and dataset 2 are used to train and simulate the LSTM model and Gipps-LSTM model. The simulation results show that the Gipps-LSTM can solve the problem of partial trajectory collision in the LSTM model simulation. Moreover, the risk level of all trajectories is lower than that of the LSTM model. The safety and stability of the model are verified by multi-vehicle loop simulation and multi-vehicle linear simulation. Compared with the LSTM model, the safety of the Gipps-LSTM model is improved by 42.02%, and the convergence time is reduced by 25 seconds.

The crossing decisions and behaviour of elderly pedestrians are affected by the pedestrian level of service (PLOS). In this paper, an evaluation model was established to analyse the relationship between the traffic environment and the perceived evaluation of elderly pedestrians. Firstly, the characteristic parameters of the selected intersections and the perceived evaluation data of elderly pedestrians at the synchronisation scenery were extracted using manual recording and questionnaire-based truncation methods. The correlation between the perceived evaluation data of elderly pedestrians and the traffic parameters were tested with respect to the dimensions of safety, convenience and efficiency. Then, the significant parameters affecting PLOS were recognised. Based on the traffic characteristic parameters, the PLOS evaluation model from the elderly perspective was established using the fuzzy linear regression method. PLOS classification thresholds were obtained using the fuzzy C-means clustering algorithm. The data from two intersections were used to validate the model. The results show that the difference between the actual and the predicted PLOS values of the two crosswalks were 0.2 and 0.1, respectively. Thus, the proposed PLOS evaluation model in this paper can be used to accurately predict the PLOS from the elderly perspective using the traffic data of signalised intersections.

Connected automated vehicles (CAV) can increase traffic efficiency, which is considered a critical factor in saving energy and reducing emissions in traffic congestion. In this paper, systematic traffic simulations are conducted for three car-following modes, including intelligent driver model (IDM), adaptive cruise control (ACC), and cooperative ACC (CACC), in congestions caused by rear-end collisions. From the perspectives of lane density, vehicle trajectory and vehicle speed, the fuel consumption of vehicles under the three car-following modes are compared and analysed, respectively. Based on the vehicle driving and accident environment parameters, an XGBoost algorithm-based fuel consumption prediction framework is proposed for traffic congestions caused by rear-end collisions. The results show that compared with IDM and ACC modes, the vehicles in CACC car-following mode have the ideal performance in terms of total fuel consumption; besides, the traffic flow in CACC mode is more stable, and the speed fluctuation is relatively tiny in different accident impact regions, which meets the driving desires of drivers.

Cities, even medium-sized and small ones, have become overwhelmed by traffic and congestion. Innovative solutions are required and recent studies have focused on sustainable approaches. This study aims to develop a multimodal transport model consisting of an urban public transportation (UPT) service combined with an e-scooter sharing service. The main purpose of the model is a comparison between two travel alternatives (car and UPT + e-scooter), calculating their associated levels of utility. The methodology is based on a multinomial logit model, implemented in Matlab software, using results from an online mobility survey (socio-economic characteristics of potential users of e-scooters). The additional aim is related to the assessment of the inhabitants’ availability to shift from car to multimodal service or to simple e-scooter service. The developed micromodel was applied in Iași, a mid-sized city located in the northeast of Romania. Several price strategies were analysed in order to find their influence on users’ mobility behaviour. It turned out that the price for the shared e-scooter is too high at this moment to be used for daily travel. Without a price decrease and public authorities’ involvement in facilitating the multimodality, the e-scooter remains only an entertainment activity.

Current analytical free-flow speed models consider all rural two-lane highways as the same road type despite their different functional significance in the network. The aim of this paper is to develop a prediction model for free-flow speed as a function of speed limit and road geometric characteristics for different classes of rural two-lane highways. The research was conducted on 50 representative sections of the two rural classes of two-lane highways equipped with automatic traffic counters in Serbia. In order to develop the appropriate models, it was necessary to determine the threshold values of vehicle time headway in the free-flow for both classes of rural two-lane highways, based on the total number of 191,720 vehicles. The obtained results show that there are differences in the threshold values of free-flow time headway for different road classes. Namely, it was determined that the values of free-flow time headway for Class I amounted to 6.3 s, and for Class II to 8.4 s. The free-flow speed prediction model for different road classes showed that speed limit had the highest impact on free-flow speed for Class I and II highways, followed by horizontal curve radius and shoulder width.

Transport is an industry that generates a significant portion of national income and directly or indirectly employs a large number of workers, while supporting the existence and development of all other sectors of the economy. Despite the long-standing goal of decoupling economic and transport growth in the European Union (EU), freight transport volumes, especially road freight transport, continue to increase. This leads to a deterioration of the quality of life and the environment, but on the other hand also creates business opportunities. The question is which country’s haulers will benefit the most. Using a shift-share analysis, the authors provide an overview of the dynamics of the EU road freight market and select countries for closer examination. They then examine the extent to which the road freight sector contributes to national income in these countries. Using a regression analysis, they estimate transport prices and changes in turnover and gross value added (GVA) for selected countries due to market structure change. The results show that the sector’s turnover increased by 4% due to market changes, sectoral GVA deviated only slightly, and there was a loss of at least 8 billion EUR in GVA due to the shortage of truck drivers.

The expansion of logistics requirements, limited space and strict requirements of generators of logistics requests (GLR) in terms of service quality complicate the supply of the region, resulting in the necessity to improve logistics models (MoL). Proximity to water, the presence of ports and piers along the coast, new eco vehicles and the development of cooperation between land and water transport are elements for improving the existing MoLs in an economically and environmentally acceptable way. Research on the development of an improved multi-echelon logistics network with variable terminals including the coordination and cooperation of a heterogeneous group of transport agencies for the realisation of goods flows represents an innovation in regional logistics (RL). This article presents an integrated MoL development process using dynamic optimisation with a focus on spatial, temporal, transport, economic and environmental components.

When roundabouts face congestion problems, the transition to signalised roundabouts is considered a solution to the problem. The majority of studies have concentrated on how to calculate the optimal cycle length and signal timing to minimise congestion at roundabouts. To date, intelligence algorithms with multi-objectives such as queue length, number of stops, delay time, capacity and so on are widely used for calculating signal timing. Although roundabout congestion can be generated by the weaving zone reducing roundabout capacity, there have been minimal studies which take into account the density in the weaving zone. This study proposed a hybrid gravitational search algorithm – ABFO random forest regression with the following objectives: density, delay time and capacity to find the optimal cycle length and green time in each phase of Changwon city hall roundabout in South Korea as a case study. The optimal cycle length and green time were calculated in MATLAB and microscopic simulation VISSIM sought the effectiveness of a signalised roundabout. The result of the analysis demonstrated that signalised roundabouts with 102 seconds cycle length (phase 1 – 65 seconds of green time and phase 2 – 37 seconds of green time) can reduce density by 46.1%, delays by 32.8% and increase roundabout capacity by 14.8%.

Vehicle exhausts diffuse into roadside crowd breathing zones, thereby jeopardising human health. This study applies dynamic traffic distribution theories to comprehensively consider the impact of vehicle emission diffusion. The results provide a theoretical basis for improving the diffusion of urban traffic pollution to benefit the surrounding environment for roadside crowds. Firstly, a multi-vehicle cellular transport model that is suitable for analysing dynamic traffic distribution is constructed considering the distinct emission factors of various types of vehicles. Secondly, a multi-vehicle emission model is established to consider a range of driving conditions. Then, the concept of roadside crowd exposure risk is introduced, and we describe a method for calculating the total amounts of pollutants emitted by vehicles and inhaled by roadside crowds. The impact of vehicle emission diffusion is comprehensively discussed in terms of vehicle emissions and roadside crowd exposure risk. A generalised impedance function considering the influence of vehicle exhaust emission diffusion is also established based on the weighted average of actual vehicle travel time, multi-model emissions and roadside crowd exposure risk. Finally, this generalised impedance function is integrated into the dynamic optimal user allocation model, and a dynamic traffic allocation model considering the influence of vehicle emission control is developed.

In the post-epidemic era, dynamic monitoring of expressway road freight volume is an important task. To accurately predict the daily freight volume of urban expressway, meteorological and other information are considered. Four commonly used algorithms, a random forest (RF), extreme gradient boosting (XGBoost), long short-term memory (LSTM) and K-nearest neighbour (KNN), are employed to predict freight volume based on expressway toll data sets, and a ridge regression method is used to fuse each algorithm. Nanjing and Suzhou in China are taken as a case study, using the meteorological data and freight volume data of the past week to predict the freight volume of the next day, next two days and three days. The performance of each algorithm is compared in terms of prediction accuracy and training time. The results show that in the forecast of freight volume in Nanjing, the overall prediction accuracies of the RF and XGBoost models are better; in the forecast of freight volume in Suzhou, the LSTM model has higher accuracy. The fusion forecasting method combines the advantages of each forecasting algorithm and presents the best results of forecasting the freight volumes in two cities.

Commuting contributes to high levels of greenhouse gases and air pollution. The recently advocated ‘green commuting’, i.e. active and public modes of transport, will be conducive to low-carbon and environmentally friendly transport. A baseline goal of urban planning is to promote health; however, few studies have explored the health-related impacts of environments at both ends of the commute on residents’ commuting mode choices. To fill the gap, this study proposes to consider the impact of the neighbourhood and working environment on green commuting from a health perspective. Using a sample of 15,886 people from 368 communities in China, three generalised multilevel linear regression models were estimated. Physical and psychological health were combined to further analyse health-related environmental attributes on the commuting choices of residents with different health levels. The results indicate that the working environment exerts more substantial effects on ‘green commuting’ than the neighbourhood environment, especially for workplace satisfaction. Moreover, we found that a good working environment and relationships will significantly encourage the sub-healthy group to choose active commuting. These findings are beneficial for policymakers to consider focusing on reconciling neighbourhood and working environments and meeting the commuting requirements of the less healthy group.

The application of electric vehicles (EVs) in the logistics industry has become more extensive. However, the mileage limitation of electric logistics vehicles (ELVs) and the long-distance distribution of ELVs have become urgent problems. Therefore, this paper proposes a long-distance distribution model for ELVs based on dynamic traffic information considering fleet mileage, distribution time and total distribution cost as the optimisation objectives, thus reasonably planning road selection and charging, and alleviating “mileage anxiety” in the long-distance distribution of ELVs. The model proposed in this paper comprehensively considers the characteristics of the high-speed and low-speed roads, the changes in road traffic flow on weekdays and non-weekdays, the time-of-use electricity price of electric vehicle charging stations (EVCSs) and uses the M/M/s queuing theory model to determine the charging waiting time. Finally, a real traffic network is taken as an example to verify the practicability and effectiveness of this model.

Urban intertunnel weaving (UIW) section is a special type of weaving section, where various lane-changing behaviours occur. To gain insight into the lane-changing behaviour in the UIW section, in this paper we attempt to analyse the decision feature and model the behaviour from the lane-changing point selection perspective. Based on field-collected lane-changing trajectory data, the lane-changing behaviours are divided into four types. Random forest method is applied to analyse the influencing factors of choice of lane-changing point. Moreover, a support vector machine model is adopted to perform decision behaviour modelling. Results reveal that there are significant differences in the influencing factors for different lane-changing types and different positions in the UIW segment. The three most important factor types are object vehicle status, current-lane rear vehicle status and target-lane rear vehicle status. The precision of the choice of lane-changing point models is at least 82%. The proposed method could reveal the detailed features of the lane-changing point selection behaviour in the UIW section and also provide a feasible choice of lane-changing point model.

Safety of rail vehicles is an important feature of sustainable public transport. Proofs of an effort in that area are new recommendations and regulations from the expert commission (WG2 of the Technical Committee CEN / TC 256) regarding trams and light rail vehicles aimed at vulnerable road users. Additional requirements on tram safety can be requested by the vehicle operator and/or city. Pedestrian safety measures can be adopted from the automotive sector utilising the protection principles from Regulation EC No. 78/2009, ECE/UN regulations, and EuroNCAP tests. The purpose of this publication is to introduce a simplified testing method for the tram front end with respect to pedestrian head-on collisions. Testing methods based on segment impactors were generally accepted. The wrap-around distance defines the assessment of vehicle impact areas. A mathematical model was created to compare the results of the full-scale tests and the segment tests done by the standard and simplified aluminium head impactors. The tram front-end design can be tested using this alternate method, based on a simple impactor and easy methodology, providing an efficient tool to inspire both the tram manufacturers and vehicle operators to improve the vulnerable road users’ safety in city traffic.

Based on the GPS trajectory data of a freight enterprise in Dalian, China, this paper studies the identification of loading and unloading points by a clustering algorithm. Firstly, by analysing the characteristics of freight loading and unloading behaviour, combined with the spatial and temporal distribution characteristics of truck GPS trajectory data, three characteristic variables of the number of trucks passing through a certain place, the average speed of trucks and the average stay time of trucks in the place are extracted. Then, the clustering algorithm and visual analysis are used to obtain the target cluster, and the POI language of the geographic information is obtained according to the points in the target cluster. The meaning information is crawled to accurately identify the result of the freight loading point. Finally, two classical clustering algorithms, K-means and GMM, are evaluated and compared. The results show that the identification method designed in this paper finally identifies 2,320 freight loading and unloading points from 11,406,000 trajectory data, which can realise the accurate extraction of freight loading and unloading points.

Transport is an integral part of any company. Nowadays, there is a great emphasis on the use of environmentally friendly modes of transport. In addition to being one of the environmentally friendly modes of transport, rail transport can carry large quantities of various goods over long distances. In order for rail transport in Slovakia to be able to compete with other modes of transport, it is important that Industry 4.0 elements are applied in the technological processes at railway stations. The aim of this article is to draw attention to the impact of the introduction of Industry 4.0 elements into the transport process in rail transport. The premise of the research task is based on the experience with the introduction of intelligent sensors in rail transport in some European Union countries. On the basis of the analysis of the use of information and communication technologies in railway transport, the article carries out a technological evaluation of the design of the wagon control unit in the transport process with regard to the speed of processing a shipment in a border-crossing station.

Numerous studies have shown that city bus drivers suffer from three key categories of health disorders: cardiovascular diseases, gastrointestinal disorders and musculoskeletal system issues, affecting the individual’s ability to work. The aim of this research was to assess the working ability of bus drivers and to determine the connection between the level of physical activity and the work ability in professional bus drivers. The study protocol included an assessment of participants’ work ability using the Work Ability Index (WAI) Questionnaire on a sample of 115 bus drivers. A statistical analysis was performed using the SAS System software package (SAS Institute Inc., North Carolina, USA). The questionnaire for determining the work ability index indicated good or excellent work ability in 78 (67.8%) of bus drivers. Moderate work ability that needed to be improved was recorded in 27 (23.5%) of drivers, and poor work ability that needed to be restored in 10 (8.7%). The results of the regression analysis show that increasing the average number of steps per day by a 1,000 increases the WAI score by 0.8. The obtained data should serve as an important argument for the design of future public health and kinesiology interventions to improve the work ability in professional bus drivers.

The emerging seaport-inland port dyad shows a great contribution to the hinterlands of seaports. However, little literature looked at its influence. This paper used an improved radiation model to study the effects of the seaport-inland port dyad on the seaport container hinterland delimitation in a Chinese multi-port system (system including 7 seaports, 2 inland ports, and 31 provinces, and formed 14 dyads). The radiation of each seaport on provinces was estimated to track changes in seaport superior hinterlands and hinterland ratings. The results showed that: i) After forming seaport-inland port dyad, the superior hinterlands scope of Shanghai Port and Shenzhen Port were expanded. ii) Both Shenzhen Port and Xiamen Port increased their radiation and then further expanded the scope of their strong and stronger level of radiation hinterlands. The provinces close to inland ports and far from seaports were significantly affected. These conclusions demonstrated that the seaport can expand its hinterland scope by establishing a seaport-inland port dyad and then compete with other seaports for market share in long-distance provinces. Various seaports may have different effects from the same inland port. As a result, seaports should choose suitable dyad to achieve their hinterland targets.

With the rapid development of urban rail transit (URT) in China, the contradiction between high cost and low passenger demand becomes prominent. To fully analyse the impacts of passenger demand on the profitability of URT can be difficult, 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 URT with different types, in consideration of the spatial and temporal characteristics of demand. Based on the data of the 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 also a good alternative while metro with higher capacity. Utilizing the URT with high capacity under insufficient demand can aggravate the burden of the 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.

As an important part of the container terminal operating system, the container terminal handling system affects the manufacturing operation efficiency of the container terminal. With the development of containerized transport industry, the container terminal handling system is becoming more and more important to the container terminal. It is aimed to seek a method to improve the efficiency of loading and unloading, and the container terminal handling system is taken as the research subject. Petri net and ExtendSim software are combined to simulate and optimize the container terminal handling system based on the relevant research results and the current situation at home and abroad. Describe the loading and unloading operation process of the container terminal system logically by Petri net according to the composition of the container terminal. Next eigenvalues of the correlation matrix are calculated to analyze the effectiveness of the Petri net system. Then simulate the whole container terminal handling system using ExtendSim based on the Petri net system, and statistical data of the ship entry module can be obtained. By analyzing the simulation results, find the factors that affect the efficiency of container terminals. The simulation is optimized by adjusting the running speed of container trucks, the quantity ratio of inner and outer tracks, and the running mode of the container trucks.

The urban expressway confluence area is selected as the research object. Through video aerial photography, image processing and artificial auxiliary technology to obtain high precision trajectory data. Based on the measured data, the driver response mode is divided into multiple sub-models from the macro and micro levels. Based on the measurement of driver type, asymmetric characteristic index and driver response mode, the type and distribution of traffic delay and the influence of asymmetric behavior on the traffic capacity of confluence area are further revealed. The results show that the radical, conservative and ordinary drivers mainly adopt non-decreasing mode, concave mode 4-1 and convex mode 2-1 respectively in the process of oscillation disturbance.The traffic delay caused by the driver ' s asymmetric behavior in the confluence area of the expressway is generally positive, and the average reaction time of the driver is larger than that of the equilibrium state. And asymmetric behavior leads to the average decrease of bottleneck outflow rate by about 7 %, which leads to the increase of delay and the decrease of traffic capacity.

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.

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.

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.

The emerging seaport-inland port dyad shows a great contribution to the hinterlands of seaports. However, little literature looked at its influence. This paper used an improved radiation model to study the effects of the seaport-inland port dyad on the seaport container hinterland delimitation in a Chinese multi-port system (system including 7 seaports, 2 inland ports, and 31 provinces, and formed 14 dyads). The radiation of each seaport on provinces was estimated to track changes in seaport superior hinterlands and hinterland ratings. The results showed that: i) After forming seaport-inland port dyad, the superior hinterlands scope of Shanghai Port and Shenzhen Port were expanded. ii) Both Shenzhen Port and Xiamen Port increased their radiation and then further expanded the scope of their strong and stronger level of radiation hinterlands. The provinces close to inland ports and far from seaports were significantly affected. These conclusions demonstrated that the seaport can expand its hinterland scope by establishing a seaport-inland port dyad and then compete with other seaports for market share in long-distance provinces. Various seaports may have different effects from the same inland port. As a result, seaports should choose suitable dyad to achieve their hinterland targets.

With the rapid development of urban rail transit (URT) in China, the contradiction between high cost and low passenger demand becomes prominent. To fully analyse the impacts of passenger demand on the profitability of URT can be difficult, 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 URT with different types, in consideration of the spatial and temporal characteristics of demand. Based on the data of the 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 also a good alternative while metro with higher capacity. Utilizing the URT with high capacity under insufficient demand can aggravate the burden of the 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.

As an important part of the container terminal operating system, the container terminal handling system affects the manufacturing operation efficiency of the container terminal. With the development of containerized transport industry, the container terminal handling system is becoming more and more important to the container terminal. It is aimed to seek a method to improve the efficiency of loading and unloading, and the container terminal handling system is taken as the research subject. Petri net and ExtendSim software are combined to simulate and optimize the container terminal handling system based on the relevant research results and the current situation at home and abroad. Describe the loading and unloading operation process of the container terminal system logically by Petri net according to the composition of the container terminal. Next eigenvalues of the correlation matrix are calculated to analyze the effectiveness of the Petri net system. Then simulate the whole container terminal handling system using ExtendSim based on the Petri net system, and statistical data of the ship entry module can be obtained. By analyzing the simulation results, find the factors that affect the efficiency of container terminals. The simulation is optimized by adjusting the running speed of container trucks, the quantity ratio of inner and outer tracks, and the running mode of the container trucks.

The urban expressway confluence area is selected as the research object. Through video aerial photography, image processing and artificial auxiliary technology to obtain high precision trajectory data. Based on the measured data, the driver response mode is divided into multiple sub-models from the macro and micro levels. Based on the measurement of driver type, asymmetric characteristic index and driver response mode, the type and distribution of traffic delay and the influence of asymmetric behavior on the traffic capacity of confluence area are further revealed. The results show that the radical, conservative and ordinary drivers mainly adopt non-decreasing mode, concave mode 4-1 and convex mode 2-1 respectively in the process of oscillation disturbance.The traffic delay caused by the driver ' s asymmetric behavior in the confluence area of the expressway is generally positive, and the average reaction time of the driver is larger than that of the equilibrium state. And asymmetric behavior leads to the average decrease of bottleneck outflow rate by about 7 %, which leads to the increase of delay and the decrease of traffic capacity.

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.

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.

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.

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.