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To address the symmetry-related resilience issues of stations and lines in urban rail transit networks, we propose a two-stage robust optimization-based approach for urban rail transit network planning. In this context, resilience is conceptualized as the ability of the network to maintain its operational symmetry under normal and disruptive conditions. Firstly, we used passenger flow distributions as decision variables to construct a two-stage symmetry-based urban rail transit network planning model, aiming to simultaneously minimize the total cost and total operating time of the network while preserving its functional symmetry. Secondly, we designed a hybrid evolutionary algorithm with chromosomes having a two-layer encoding structure, where the Niched Pareto Genetic Algorithm served as the main algorithmic framework, and a Large Neighborhood Search mechanism was designed to optimize the connectivity gene layer of individuals, ensuring the symmetry of network connectivity. Finally, we conducted computational verification on randomly generated instances to confirm the effectiveness of the model and algorithm. The experimental results demonstrated that our method could find two sets of Pareto optimal solutions for cost preference and time preference, thereby preserving the operational symmetry of the network under normal and damaged conditions, as well as reducing the total operating time. This effectively improved the overall efficiency and resilience of the network. Our designed hybrid evolutionary algorithm converged to satisfactory objective values in the early iterations, exhibiting strong search and optimization performance and effectively solving the two-stage symmetry-based urban rail transit network planning model. [ABSTRACT FROM AUTHOR]

As an important part of modern comprehensive transportation system, high-speed railway (HSR), whether it is a transregional trunk line or an intercity line, always shapes the industrial layout and changes the living environment at different levels. Based on the analysis of the railway network topology and organization process of passenger train, this paper clarifies the connotation of passenger train operation scheme of HSR considering network survivability, and further explains the connotation of railway network system and its relationship with passenger train operation scheme. In this paper, a comprehensive quantitative index of the importance of key nodes and key edges is established, and an evaluation index of the survivability of railway service network based on the operating mileage of passenger trains is constructed, which is applied to the real local HSR network in China. With the aim of improving the survivability of HSR system, an alternative operation route of passenger trains between some OD stations is given according to the specific railway interruption situation., Author(s): Yong Xian [1]; Yinzhen Li (corresponding author) [1]; Haijun Li [1]; Changxi Ma [1]; Tianxiang Zhang [2]; Yongpeng Zhao [1] 1. Introduction Railway plays an important role in economic [...]

This study aims to elucidate the implications of carbon peak and carbon neutrality targets on corridor logistics, with a focus on the burgeoning high-speed rail express sector. Acknowledging carbon emissions taxation as an integral component of transportation costs, it examines the competitive dynamics among four cargo transport modes: high-speed rail (HSR), conventional rail, aviation, and road transport. Within a strategic game framework, carriers are analyzed based on freight rates, speed, safety, reliability, and convenience to assess their utility. A dynamic game model and a solution approach are developed, aiming to optimize freight-related variables, maximize carriers' generalized profits, and enhance shippers' utility. Empirical validation is provided through case studies in Xi'an and Lanzhou, northwest China, affirming the model's efficacy. The findings reveal the strong competitive edge of the high-speed rail express in the corridor, offering valuable insights for carrier pricing strategies, emission tax rate setting, and macro-policy adjustments in the transport sector. [ABSTRACT FROM AUTHOR]

Predicting rail transit passenger flow is crucial for modifying the metro schedule. To increase prediction accuracy, a model is proposed that combines long short-term memory (LSTM) with single spectrum analysis (SSA). Firstly, a stepwise decomposition sampling (SDS) strategy based on SSA progressive decomposition is proposed as a solution to the data leaking issue in traditional sequence decomposition. Then, based on this strategy, the passenger flow time series with complex features is decomposed into a relatively single trend and fluctuation component. Finally, the LSTM network is employed to perform short-term predictions on each component separately. The predicted value of each component is accumulated to obtain the original passenger flow' predicted result. The example shows that, compared with the single LSTM and other hybrid models, the proposed method offers a greater overall prediction accuracy in the experimental days, and the method has specific applicability., Author(s): Haijun Li (corresponding author) [1]; Yongpeng Zhao [1]; Changxi Ma [1]; Ke Wang [1]; Xiaoting Huang [1]; Wentao Zhang [2] 1. Introduction Subway system has the advantages of large [...]

Tourist-dedicated train is the product of the combination of railway transportation and tourism, and its tour line selection includes the selection of nodes and lines. Based on the principle of decision-making, taking technical factors, tourism factors, regional economic factors, and passenger flow factors as criteria, this paper analyzes the decision-making indices affecting the tour line and establishes the decision-making index system. Subsequently, the prospect theory considering the bounded rationality and psychological factors of decision makers is combined with vague set fuzzy decision theory, and a comprehensive decision method based on vague set and prospect theory is proposed. Finally, the feasibility of the proposed decision method is verified by an example. The research shows that the established decision-making index system is representative, and the proposed decision-making method is scientific and effective for the decision making of tourist lines of tourist-dedicated train. The decision-making results can be used as a reference for the formulation of tour lines and line plans of tourist-dedicated train., Author(s): Yuanding Cui (corresponding author) [1]; Changxi Ma [1] 1. Introduction Tourist-dedicated train is a new tourism product developed by railway transport enterprises for the tourism market. It is the [...]

A new macroscopic traffic flow lattice model is established which considered the taillight effect and velocity deviation. By combining the concept of critical density, the critical condition of taillight triggering is established. The situation of taillight appearing is fully considered, and the influence of taillight effect is analyzed. Through the stability analysis of the model, the stability conditions of the model are obtained. By nonlinear analysis, the mKdV equation is derived which can describe the evolution mechanism of the density wave. From the phase diagram, we can find that the two factors have a positive impact on the stability of traffic flow. Finally, spatiotemporal evolution of the density wave and cross-section view of the density wave are obtained by numerical simulation to verify the theoretical derivation of this paper. The simulation results show that the stability of traffic flow can be improved by considering taillight effect and speed deviation. In addition, by comparing the time-space evolution maps of different parameter values, it can be found that the stability of traffic flow considering the taillight effect and speed deviation is better than that considering one factor alone. However, the stability of traffic flow will be negatively affected by low speed estimate and high critical density., Author(s): Zhicheng Li [1]; Changxi Ma (corresponding author) [2] 1. Introduction With the development of urbanization and modern science and technology, traffic problems have become the most serious social problem [...]

Real-time, accurate and efficiency short term traffic flow prediction is one of the key technologies to realize traffic flow guidance and traffic control, which has been widely concerned in the domain of ITS (Intelligent Transport System) during recent years. Through the study of the existing traffic flow prediction model, road traffic flow control model with the slope of the change rate is proposed. The model can find out abnormal point from the traffic flow time series by the use of the slope change rate, and it can analyse this trend of traffic flow changes for control purposes of traffic flow. The achieved results indicate that the algorithm is suitable for road traffic flow peak control problem and could be effective for road traffic flow control.

Parking demand forecasting is an important part of urban parking planning and is also an important basis for the development of parking facilities. The primary objective of this study was to explore multiple factors that affect the curb parking price (CPP) and the changing rules of the curb parking price (CPP) with these factors and to predict the CPP in terms of urban mobility. The data were collected through a statistical survey that was administered in 81 cities in China. The cities were divided into three categories: rich cities (RCs), poor cities (PCs), and tourist cities (TCs). Both the time series method (TSM) and regression analysis method (RAM) were developed to simultaneously examine the factors associated with the CPP among parking users. The results showed that TSM and RAM can account for common urban curb parking prices. The prediction results showed that the CPP is affected by the number of urban dwellers (UD), the prevalence of car ownership (CO), and the per capita disposable income (PCDI) of urban residents; the CPP can be predicted by a model built on the basis of the above three influencing factors. The results can enhance our understanding of the factors that affect CPP. Based on the results, some suggestions regarding the use of the CPP range in parking policy planning were discussed., 1. Introduction Curb parking is a public resource [1]. At present, the average ratio of cars to parking spaces in the entire urban district of large cities in China is [...]

This study aimed to reveal the potential relationship between personal characteristics of e-bike riders and illegal occupation of motor vehicle lane. To this end, a questionnaire survey was conducted and 350 valid copies of responses were retrieved from the e-bike riders. Depending on the number of motor vehicle lanes occupied, the risky behavior of illegal occupation was divided into four intervals: intervals A, B, C, and D. The disaggregate theory has high adaptability to the analysis of individual traffic behavior. In this study, the multinomial logit model was used, and eight personal characteristics of e-bike riders were selected. The aforementioned four intervals were the four selection limbs, and a measurement model calculating the influence of personal characteristics on the behavior of illegal occupation was built. The theory of elasticity was employed to analyze the sensitivity degree of each influence factor. The results showed that the absolute values of elasticity of all tested influence factors, including age, educational level, and eye vision, were less than 1.000. However, on the four intervals, the elasticity of riders' temperament was 1.203, 1.656, 1.554, and 1.355, respectively, and elasticity of riding proficiency was 2.782, 3.883, 3.453, and 2.932, respectively., 1. Introduction e-bike is defined as the mass of the whole vehicle shall not exceed 55 kg, the speed shall not exceed 25 km/h, and the motor power shall be [...]

In recent years, there are more and more applications of traffic violation monitoring in some countries. The present work aims to analyze the vehicle speeds nearby road traffic violation monitoring area on urban main roads and find out the impact of road traffic violation monitoring on the vehicle speeds. A representative urban main road section was selected and the traffic flow was recorded by camera method. The vehicle speeds before, within, and after the road traffic violation monitoring area were obtained by the calculation method. The speed data was classified and processed by SPSS software and mathematical method to establish the vehicle speed probability density models before, within, and after the road traffic violation monitoring area. The results show that the average speed and maximum speed within the traffic violation monitoring area are significantly slower than those before and after the traffic violation monitoring area. 70.1% of the vehicles before the road traffic violation monitoring area were speeding, and 80.2% of the vehicles after the road traffic violation monitoring area were speeding, while within the road traffic violation monitoring area, the speeding vehicles were reduced to 15.9%. When vehicles pass through the road traffic violation monitoring area, the vehicle speeds tend to first decrease and subsequently increase. In its active area, road traffic violation monitoring can effectively regulate driving behaviors and reduce speeding, but this effect is limited to the vicinity of the traffic violation monitoring. The distribution of vehicle speeds can be calculated from vehicle speed probability density models., 1. Introduction In many countries, with the development of the social economy, the number of automobiles has increased yearly, and a series of problems such as road congestion mess in [...]

To comprehensively understand the research progress of the fleet scheduling for hazardous materials, the study has summarized the corresponding research results from three aspects (a) hazardous materials transportation risk, (b) route optimization, and (c) fleet scheduling, and then pointed out potential problems from six aspects: (a) the coupling risk of the transport fleet; (b) the screening of time and space for the transport of hazardous materials; (c) the scheduling optimization for transport fleets; (d) taking insufficient account of transport risks fairness; (e) insufficient robustness of scheduling schemes; and (f) lacking of research results on fleet scheduling of transport in the context of antiterrorism. After that, by considering the existing shortcomings of the current research, five research directions are presented that should be further explored in the future. Subsequently, both rough set and association rule theory is applied to explore the cause chain of transportation accidents for hazardous materials, and analyze the mechanism of transport accident for hazardous materials. Next, the Bayesian network is presented to predict the accident rate of hazardous materials transportation under different temporal and spatial conditions, and the dynamic rolling scheduling method of hazardous materials transport fleet is constructed under normal and antiterrorism background., 1. Introduction Hazardous materials are referred to those substances and articles with explosive, inflammable, toxic, infectious, corrosive, and other dangerous characteristics that are liable to cause human casualties, property damage, [...]

To understand the status quo of urban recurrent traffic congestion, the current results of recurrent traffic congestion, and gating control are reviewed from three aspects: traffic congestion identification, evolution trend prediction, and urban road network gating control. Three aspects of current research are highlighted: (a) The majority of current studies are based on statistical analyses of historical data, while congestion identification is performed by acquiring small-scale traffic parameters. Thus, congestion studies on the urban global roadway network are lacking. Situation identification and the failure to effectively warn or even avoid traffic congestion before congestion forms are not addressed; (b) correlation studies on urban roadway network congestion are inadequate, especially regarding deep learning, and considering the space-time correlation for congestion evolution trend prediction; and (c) quantitative research methods, dynamic determination of gating control areas, and effective countermeasures to eliminate traffic congestion are lacking. Regarding the shortcomings of current studies, six research directions that can be further explored in the future are presented., 1. Introduction In recent years, with the rapid development of the social economy, the contradiction between the limited carrying capacity of urban roadway networks, and the rapidly growing traffic demand [...]

This paper builds a multiobjective optimization model for solving the taxi carpooling with detour problem and designs a genetic algorithm to determine a fair pricing scheme for riders and drivers. The researches show that it is feasible to share a taxi with detour. It is the key to determine appropriate carpooling payment ratio and detour carpooling payment ratio. The ratio of detour distance to travel distance has an important influence on detour carpooling. It should be limited to less than certain values. Payment ratios and the maximum value of the ratio of detour distance to travel distance are determined by the method proposed in this paper. The method can ensure benefits of passengers and drivers, which makes detour carpooling a reality. These conclusions and the method have a certain guiding significance for formulating taxi policy., 1. Introduction Taxi carpooling mode has become a common travelling mode. The mode permits several passengers to share the same taxi. Taxi carpooling can effectively solve the problem of having [...]

The effect of aggressive driving behavior on driver's injury severity is analyzed by considering a comprehensive set of variables at highway-rail grade crossings in the US. In doing so, we are able to use a mixed logit modelling approach; the study explores the determinants of driver-injury severity with and without aggressive driving behaviors at highway-rail grade crossings. Significant differences exist between drivers' injury severity with and without aggressive driving behaviors at highway-rail grade crossings. The level of injury for younger male drivers increases a lot if they are with aggressive driving behavior. In addition, driving during peak-hour is found to be a statistically significant predictor of high level injury severity with aggressive driving behavior. Moreover, environmental factors are also found to be statistically significant. The increased level of injury severity accidents happened for drivers with aggressive driving behavior in the morning peak (6-9 am), and the probability of fatality increases in both snow and fog condition. Driving in open space area is also found to be a significant factor of high level injury severity with aggressive driving behaviors. Bad weather conditions are found to increase the probability of drivers' high level injury severity for drivers with aggressive driving behaviors., 1. Introduction Traffic accidents are a very important safety issue in the United States. For example, six million accidents were reported to the police in 2016 which involved 37461 fatalities [...]

An extended car-following model is proposed on the basis of experimental analysis to improve the performance of the traditional car-following model and simulate a microscopic car-following behaviour at signalised intersections. The new car-following model considers vehicle gather and dissipation. Firstly, the parameters of optimal velocity, generalised force and full velocity difference models are calibrated by measured data, and the problems and causes of the three models are analysed with a realistic trajectory simulation as an evaluation criterion. Secondly, an extended car-following model based on the full optimal velocity model is proposed by considering the vehicle gather and dissipation. The parameters of the new car-following model are calibrated by the measured data, and the model is compared with comparative models on the basis of isolated point data and the entire car-following process. Simulation results show that the optimal velocity, generalised force, and full velocity difference models cannot effectively simulate a microscopic car-following behaviour at signalised intersections, whereas the new car-following model can avoid a collision and has a high fit degree for simulating the measured data of the car-following behaviour at signalised intersections., 1. Introduction A car-following model is a mathematical description of the movement of a car in the same lane given the change in the moving state of the front car [...]

For the problem of taxi carpooling detour, this paper studies driver strategy choice with carpooling detour. The model of taxi driver strategy evolution with carpooling detour is built based on prospect theory and evolution game theory. Driver stable strategies are analyzed under the conditions of complaint mechanism and absence of mechanism, respectively. The results show that passenger's complaint mechanism can effectively decrease the phenomenon of driver refusing passengers with carpooling detour. When probability of passenger complaint reaches a certain level, the stable strategy of driver is to take carpooling detour passengers. Meanwhile, limiting detour distance and easing traffic congestion can decrease the possibility of refusing passengers. These conclusions have a certain guiding significance to formulating taxi policy., 1. Introduction Taxi carpooling mode has the characteristics of improving the transportation efficiency, easing the traffic pressure, and reducing environmental pollution [1,2]. In recent years many cities in China have [...]

Countdown signal control is a relatively new control mode that can inform a driver in advance about the remaining time to pass through intersections or the time needed to wait for other drivers and pedestrians. At present, few countries apply vehicular countdown signals. However, in China, some cities have applied vehicular countdown signals for years, though it is unclear how and how much such signals influence driving psychologies and behaviors compared with non-countdown signal controls. The present work aims to clarify the impact of vehicular countdown signals on driving psychologies and behaviors on the cognitive level. A questionnaire survey with 32 questions about driving psychologies and behaviors was designed, and an online survey was conducted. A total of 1051 valid questionnaires were received. The survey data were analyzed, and the main results indicate that most of the surveyed drivers prefer countdown signal controls and think that such controls can improve not only traffic safety but also traffic operational efficiency. The surveyed drivers also think that countdown signal controls have an impact on driving psychologies and behaviors and the survey results have demonstrated that the driving behaviors of female drivers surveyed are not conservative under the clear conditions of green countdown signal control. Further studies and methods concerning the effects of countdown signals on driving psychologies and behaviors are discussed., 1. Introduction While intersections are part of the road system, they are far more complex than the segments connecting them [1, 2]. Driving psychologies and behaviors at road intersections are [...]