Autonomous vehicles (AVs) and human-driven vehicles (HDVs) will share the roads for a long time, hence the need to study traffic flows mixing AVs and HDVs, especially during the AV introduction period. This paper aims to investigate the roadway and traffic characteristics that affect the impact of AVs on freeway traffic operations, using an adapted version of the HCM6 truck passenger-car equivalent (PCE) methodology. A large number of scenarios comprising different roadway characteristics, AV types and traffic flow compositions were simulated using Vissim to obtain AV PCEs. The results indicated that, for all scenarios considered, an AV has a 20% lower impact on the quality of service and operation than an HDV. A CART decision tree indicated that the most important factors affecting the AVs’ impact on traffic operations are vehicle-to-vehicle connectivity level and the capability of travelling in platoons. Maximum platoon length did not matter, and the increase in the number of traffic lanes reduced the positive impact of AVs on service quality.

Effectively equilibrating passenger distribution on metro platforms and carriages is important for relieving local congestion. This paper explores the role of incentive mechanisms in encouraging passenger queuing behaviours. To quantitatively analyse passenger compliance with the policy, a questionnaire survey was conducted in Fuzhou, China. According to the preliminary analysis of the survey data, passengers have various moving distance preferences under the incentive scenarios, namely, no movement, smaller distance and greater distance. Additionally, this paper establishes a nested logit model that considers travel purposes and moving distances. The empirical results show that although monetary and point-system incentives can effectively enhance passenger compliance with transfer queue-positioning requirements, when the moving distance is very small, people pay less attention to rewards. Compared to those commuting on weekends, passengers commuting on weekdays comply with policies more strongly, and the effect of implementing incentive policies is better; however, the effect of those policies is reduced among those travelling for leisure. Meanwhile, when travelling for leisure, as the number of companions increases, people’s willingness to follow guidance on where to wait increases. According to the results, the implementation of incentive-based waiting encouragement policies during peak working days can result in good compliance.

At present, interest in the application of unmanned aerial vehicles (UAV) for delivery is growing. A new “multi-type of UAV collaborative delivery” mode has been proposed. Through a combination of large, medium and small UAVs, the delivery capabilities of the UAV logistics system are significantly improved. Sometimes there is high demand, resulting in planned delivery routes that are no longer feasible, and even cause a shortage of distribution centre capacity and drones. This study explores logistics delivery strategies to solve problems caused by high demand. In this study, a multitype and multidistribution UAV model was established with the objective of minimising the total cost of distribution by considering factors such as the UAV energy consumption, load and distribution centre conditions. An improved ant colony algorithm was designed and its effectiveness was verified through the variability of the calculation time and multiple calculation results of different-scale examples. Finally, the classic vehicle routing problem (VRP) case is used in three scenarios to analyse the UAV scheduling optimisation problem. The results indicate that assisted delivery can reduce costs by 3% while ensuring delivery timeliness. The results of this study can provide guidance and benchmarks for the application of UAVs in urban logistics delivery systems.

The main objective of the transport reliability and maintenance analysis is to improve the understanding of accidents through incident investigations. This research focuses on composite pneumatic tyres used in transportation engineering and presents both theoretical and experimental studies. The finite element method used for numerical simulation combined with pre-experimental measurements based on optimisation by material vibration response is presented for tyre material modelling. Piezoelectric vibration test was used for the pre-experimental test of the tyre quarters. The simulation results indicate that the pneumatic tyre with the recommended air pressure inflation shows the least amount of deformation. In comparison, pneumatic tyres with recommended and reduced air pressure inflation of 0.25, 0.5 and 0.75 bar are under research. Additionally, it was established that, when subjected to external forces that exceed the tyre’s maximum weight capacity, as determined by the manufacturer, the tyre exhibits significant stiffening and internal stress. The research suggests that this methodology can be used to obtain a realistic model of vehicle tyre dynamic processes and assess the impact on road traffic safety with different inflation pressures and loads.

The structural deficiencies of the terminal delivery path often make it the main culprit of urban traffic congestion and environmental pollution. Traditional studies of express networks regarded them as an independent entity, ignoring the endogenous role of urban road network morphology and structure. To solve this problem, this paper explored the spatial dependency of terminal delivery routes in Xi'an City based on the idea of a bipartite graph network. A spatial dependency matrix of delivery paths–urban roads was constructed by abstracting delivery paths as node-set A and urban roads as node-set B. In addition, three spatial dependencies indexes, including degree centrality, betweenness centrality and closeness centrality were introduced to analyse the coupling features of these two objects. The results show that these dependency measures can reflect the coupling features of urban terminal delivery paths and urban roads. Firstly, degree centrality demonstrates terminal delivery path coverage and coupling hierarchy and scale-free nature. Secondly, betweenness centrality presents the road utilisation balance of terminal delivery paths. Thirdly, closeness centrality explains how easy it is for delivery paths to connect with others.

Connected and autonomous vehicles (CAVs) are recognised as a technology trend in the transportation engineering arena. As one of the most popular capabilities of CAVs, trajectory planning attracts extensive attention and interest from both academia and the industry. Segmented trajectory planning is gaining popularity for its simplicity and robustness in computation and deployment. Constructive recommendations and guidelines can be provided by exploring the effects of segmented trajectories in different settings of CAVs and intersections. This research proposes a control strategy for segmented trajectory planning in a fixed signal timing environment. To test the effects of this control strategy, this research designs simplified fixed signalised intersection scenarios and implements segmented trajectory planning features of CAVs with different traffic demand scenarios, distances and speed limits. The results show that the proposed control strategy has stable superior performances in different traffic scenarios especially when the traffic volume is near capacity.

Based on two-sided market theory, this paper has studied the pricing problem of ride-hailing platforms with a combination of inter-group network externality and inner-group network externality. Two scenarios of user structure are considered. In scenario 1, both travellers and drivers are single-homing. In scenario 2, travellers are single-homing while drivers are multi-homing. Moreover, time sensitive factors and driver’s commission rate are introduced to reflect the characteristics of transport industry. Finally, the impact of network externality, time sensitivity, driver’s commission rate and entry cost on ride-hailing platform pricing, user scale and profits are analysed. The results show that inter-group network externality and inner-group network externality have a negative effect on platform prices charged to both travellers and drivers. However, when travellers are multi-homing, the price charged to travellers is positive with respect to the inter-group network externality from drivers. In the relationship between travellers’ scale and inter-group network externality, inner-group network externality is positive. Further, in both scenarios, the network externalities from the two sides affect platform profits negatively.

The role of transportation is becoming increasingly important in the world economy, and road transport in particular plays a very important role in all types of transportation. For this reason, it is extremely important to monitor its performance regularly. Very often, this is done using Data Envelopment Analysis (DEA) performance evaluation models, and consequently, there are numerous articles in the literature on DEA evaluation of road transport systems. In this study, we first summarise these articles and classify them according to different characteristics (environmental, safety, economic, energy). Finally, we use them as a basis for developing a novel DEA framework, which is used for the evaluation of the efficiency and ranking of road transport systems that also takes into account undesirable outputs, i.e. environmental and safety outputs. As a case study, we evaluate 28 European countries from technical, safety and environmental aspects. The CCR and SBM models are used to evaluate the efficiency of these countries for the last two years of published data. The results show that Denmark ranks first and Cyprus last for both years. It was also found that safety efficiency is generally rated lower than other criteria. Finally, the results and reasons for the efficiency and inefficiency of specific decision-making units, i.e. countries, are discussed.

Tram signal priority control is a crucial approach for enhancing the reliability of tram operations and has been implemented in various cities. Nevertheless, unpredictable tram operations influenced by tram dwell time during station stops can cause signal priority control failure at intersections. It is challenging to precisely predict tram dwell time at stations that offer multiple lines. To address this issue, the proposed research presents a capped robust optimal control (CRC) technique for tram signal priority. This method entails considering the stochastic number of passengers boarding and alighting at stations with multiple lines. Furthermore, tram delay calculation models at intersections are established and integrated into an objective function. The main objective of this strategy is to enhance tram operation reliability and maximise tram operation efficiency while reducing the adverse impact of tram priority on other vehicles at the intersection. A case study was conducted to evaluate the effectiveness of the CRC method. The results indicate that the CRC technique significantly improves tram operation reliability and efficiency.

This article deals with the highly topical issue of greening air transport chains. It is important to consider the environmental aspect of the current performance of air transport in regions with less intensive air transport chains, such as the Eastern Adriatic. The regional airports of Ljubljana, Zagreb and Belgrade are dependent on European air cargo hubs and at the same time have the task of connecting the national airports in Sarajevo, Podgorica, etc., which complicates the functioning of air transport chains regionally. A comprehensive consideration of air cargo chains is important in terms of price and transport time, but also in terms of the GHG footprint. The results show that an environmental assessment of air transport chains is necessary for a more comprehensive decision on sustainable supply chains. The study enriches the scientific understanding of air transport chains in the Eastern Adriatic region from the point of view of carbon footprint and energy efficiency of transport, and highlights the need to use the already developed IT tools in the assessment and modelling of transport chains when different options are presented to cargo owners. Integrating the above approaches and data into current business models enables the gradual regional decarbonisation of air transport.

With the popularity of electric vehicles, they have become an indispensable part of traffic flow on the road network. This paper presents a reliability-based network equilibrium model to realise the traffic flow pattern prediction on the road network with electric vehicles and gasoline vehicles, which incorporates travel time reliability, electric vehicles’ driving range and recharge requirement. The mathematical expression of reliable path travel time is derived, and the reliability-based network equilibrium model is formulated as a variational inequality problem. Then a multi-criterion labelling algorithm is proposed to solve the reliable shortest path problem, and a column-generation-based method of the successive average algorithm is proposed to solve the reliability-based network equilibrium model. The applicability and efficiency of the proposed model and algorithm are verified on the Nguyen-Dupuis network and the real road network of Sioux Falls City. The proposed model and algorithm can be extended to other road networks and help traffic managers analyse traffic conditions and make sustainable traffic policies.

The article discusses the results of studies of railway line capacity relative to the application of additional block division using virtual blocks in the process of positioning a train reporting its position and train set integrity. The studies were conducted using the authors’ original simulation software enabling extensive parameterisation of infrastructure, including configuration of the train control system and signalling principles, by taking the actual characteristics of train movements into account based on data obtained from real-life measurements.

Non-synchronised timetables of the first hour trains can lead to longer waiting times for passengers wishing to transfer at the transfer station. This study aims to reduce the waiting time of passengers by synchronising the timetables of first hour trains using actual transfer times. The transfer times of the passengers are obtained from the observations and are used in this synchronisation study. The genetic and simulated annealing algorithms are implemented to solve the first train synchronisation model. Finally, a case study is conducted on a section of the Istanbul metro network to test the synchronisation model. The results show that the total waiting time of the first hour trains transfer passengers is reduced by 35% by applying the proposed model. Another result of the study shows that using the actual transfer time instead of the average transfer time of the passengers reduces the average waiting time of the passengers by 19%.