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The dual-carbon strategy advocates a green, environmentally friendly, and low-carbon lifestyle. In the field of transportation, electric vehicles (EVs) have been regarded as an effective solution to reduce carbon emissions and to conserve energy. Developing a reasonable charging guidance scheme for users is a feasible way to solve problems, such as the range anxiety of EV users, and has a great application value for the promotion of EVs in the future. In practical situations, how to develop charging induction schemes for users that better meet their needs according to the type of user and their multi-dimensional preferences is the focus of this paper. To this end, this study utilized charging behavioral data to investigate the multi-dimensional charging preference of users based on the collaborative filtering algorithm. Then, a multi-objective optimization model was established based on the preference degree of each charging station and the integrated travel cost. An NSGA-III framework was used to design the algorithm to solve the proposed model. The algorithm was tested using simulation experiments that were designed based on the road network and charging stations in Beijing. The final result is an experimental analysis of the weight matrices for the three different preferences of minimum energy consumption cost, minimum time cost, and minimum fee cost, which yields a difference of about 4.4% between the optimal energy consumption cost and the maximum energy cost, about 2.9% between the optimal time cost and the maximum time cost, and about 10% between the optimal fee cost and the maximum fee cost under these three different preferences, respectively. The proposed multi-objective optimization model is able to provide users with reliable charging station selection by incorporating their personalized charging preference characteristics and charge guidance schemes. [ABSTRACT FROM AUTHOR]

Taking Beijing metro line 5 as the research vehicle model, the influence of different track structure on subway vibration is analyzed. According to the coupling dynamic equations of vehicle rail, the coupling dynamic equations of vehicle body models under integrated rail bed, plate rail bed and floating plate rail structure are established, respectively, and the vibration response of vehicle body models under three kinds of rail structure is calculated. The evaluation indexes of dynamic characteristics of rail coupling are analyzed. The analysis results show that with the increase of subway speed, the vertical displacement and acceleration between the vehicle and the middle point of the track gradually increase, and the vibration response of the fourth wheel to the maximum wheel-rail force also gradually increases. With the increase of the buried depth of subway tunnel, the maximum vertical displacement and ground motion acceleration of the three tracks gradually decrease, which indicates that this method can accurately analyze the vibration response of subway under different track structures. [ABSTRACT FROM AUTHOR]

• Right-turning vehicle-pedestrian conflict assessment at intersection crosswalks. • Various behavior models are integrated to a simulation platform. • The frequency and severity of conflict can be represented by SSMs. • Large dimensions and turning angles result in undesirable safety performance. Frequent vehicle-pedestrian conflicts deserve special attention for safety assessment at intersections. This study helps verify how the simulation as an innovative approach can be utilized for right-turning vehicle-pedestrian conflict assessment at intersection crosswalks prior to implementation. Various behavior models such as vehicle turning path, turning speed, gap acceptance model and pedestrian behavior model, have been established. Through integrating the calibrated models into one simulation platform, the stochastic behavior of vehicles and pedestrians under different geometric layouts and operational conditions can be reproduced. Based on the field data collected by an unmanned aerial vehicle (UAV) at two urban intersections in Beijing, China, it was demonstrated through validation of surrogate safety measures (SSMs), i.e., Post Encroachment Time (PET) and vehicle passing speed at conflict points, that the simulation model can reasonably represent the frequency and severity of conflict occurrence at signalized crosswalks. The sensitivity analysis results indicated that large dimensions and turning angles of intersections tend to result in undesirable safety performance. [ABSTRACT FROM AUTHOR]

Due to the characteristics of electric buses, such as mileage limitations, multiple charging modes, and long charging times, traditional vehicle scheduling and driver scheduling strategies cannot meet the requirements for electric bus line scheduling. To address this issue, we propose a collaborative optimization model for establishing vehicle schedules, charging plans and driver schedules for electric bus lines incorporating three charging modes: fast charging, slow charging and battery swapping. The proposed model is solved by a two-stage solution algorithm based on "Generation and Selection". Case studies are carried out on bus lines in Beijing. The results show that the proposed model can reduce the costs of bus companies and improve the utilization rate of buses and drivers. In addition, the results indicate that bus line length has an important impact on the selection of charging mode. [ABSTRACT FROM AUTHOR]

• The paper integrated the flexible wheelset model calculated by the finite element method into the classical vehicle-track coupling dynamic model, and then imported the bearing substructure model into the vehicle-track coupling dynamic model including flexible wheelset to complete the bearing-vehicle-track coupled dynamic simulation model. • In order to solve the contact relationship between raceway and roller, the slice method is used to describe the contact state of bearing substructure, and the contact between inner ring rib and roller is considered. • To verify the correctness of the established bearing-vehicle-track model, field tests were conducted on the high-speed railway line from Beijing to Tianjin. The field tests verify the effectiveness of the simulation model as well as the correctness of the vehicle model under polygonal wheel wear excitation. • The effects of the different orders and amplitudes of wheel-polygonal wear on dynamic performance of the axle-box system are analyzed and discussed in detail. With the increasing speed of high-speed trains and the deteriorating operation environment of axle-box system, the dynamic performance of axle-box bearing directly affects the stability and safety of operation. In this paper, a bearing-vehicle-track coupling dynamic model is established, and its effectiveness is verified by field tests. The simulation results of the coupling dynamic model including wheel-polygonal wear show that the effect of high order polygonal wheel wear (17th ∼ 21st order) on the axle-box system is greater than that of low order wheel wear (1st ∼ 5th order). The frequency domain of axle-box vertical vibration acceleration excited by high order wheel-polygonal wear is mainly distributed in 400 ∼ 600 Hz. The low order polygonal wheel wear amplitude has little effect on the bearing roller-outer raceway contact load. When the wear amplitude of 20th order polygonal wheel is 0.06 mm, the roller-outer raceway contact load is 27.22% higher than that when the wear amplitude is 0.04 mm. In order to avoid bearing failure caused by excessive bearing roller-raceway contact force, the amplitude of 20th order polygonal wheel wear should reduce to less than 0.04 mm. [ABSTRACT FROM AUTHOR]

• Develop an agent-based model of electric vehicle (EV) and vehicle-to-grid (V2G) adoption. • The EV-V2G model can explicitly simulate social influences on the EV and V2G adoption. • Only 3.3% of survey participants were familiar with V2G. • V2G selling price and advertisement were not very influential to the diffusion of V2G. The potential widespread adoption of Electric Vehicles (EVs) has received considerable attention across the globe. However, as a promising technology for both EVs and smart grid, Vehicle-to-Grid (V2G) tended to receive much less attention. This paper developed an agent-based joint EV and V2G model to simultaneously simulate how EVs and V2G might diffuse across space and over time, with empirical findings from a questionnaire survey in Beijing. In particular, random forest models were developed with the survey data to generate each agent's preferences and attitudes towards EVs and V2G. The joint model also considered three typical levels of social influence, i.e., global influence, neighbor effect, and friendship effect, in the diffusion of EVs and V2G. Finally, the joint model was tested through several "what-if" scenarios, considering different V2G prices, EV/V2G advertisement intensities, and vehicle purchase restrictions. The survey results suggested that 67.7% of the respondents were familiar with EVs, but only 3.3% of them were familiar with V2G. However, over 70% of them would/might try V2G given that they had an EV. The model results suggested that the number of CV applicants was 6.19 times that of BEV applicants in 2030 in the baseline scenario, and only 27.8% of BEV users adopted V2G. Furthermore, V2G selling price, EV/V2G advertisement, and dedicated PHEV purchase permits were not very influential to the diffusion of V2G. The outcomes would be helpful for EV- and V2G-related stakeholders in policy making and technology investment. [ABSTRACT FROM AUTHOR]