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With the network operation in urban rail transit (URT), accessibility to the URT network increases markedly, leading to a growing transfer demand. As the URT system resource is equivalent to a bottleneck resource, it needs to be fairly allocated to transfer passengers (TP) and direct passengers (DP). Most existing studies focus on single line operation optimization but ignore the transfer demands of TPs. Cross-line operation (CO) has been verified as an efficient way to improve TP travel efficiency. This study focuses on the issue of passenger travel fairness with CO in the URT system. The concept of passenger effective travel time (ET) and ineffective travel time (IET) are proposed first. Based on the concept of α -fairness, the fairness of different classes of passengers was calculated through IET and ET. A mathematical model with decision variables of the turn-back station for CO and train frequency was constructed by analyzing the travel characteristics of passengers in two types of intersecting URT lines ("Y/T"-type and "X"-type) to minimize the passenger IET cost, fairness, and operation cost. Finally, the Changping Line and Line 8 in the Beijing URT system were considered as examples to verify the effectiveness of the proposed approach. The results indicate that from an overall perspective, CO can improve passenger travel fairness without increasing the IET cost for all passengers. Furthermore, considering the fairness of passenger travel may increase the operation costs. Study results contribute to a more fair URT system. • A model for CO with consideration of fairness in URT system is developed to determine the train turn-back stations and train frequencies. • The concept of ET and IET are present to calculate the passenger travel fairness, to reflect the fairness of travel distances and times. • A case study of two intersecting lines of the Beijing Metro is used to verify the model. • A variety of factors are examined for impact on passenger travel fairness. [ABSTRACT FROM AUTHOR]

With its high infection rate, COVID-19 has swept the globe and brought great challenges to social life and economies. As an essential form of public transportation, the Beijing subway plays an important role in transportation systems. In traditional subway organizations, all one-sided doors of a train carriage are employed for passengers' alighting and boarding. A higher risk of COVID-19 infections may be attributed to inevitable bidirectional conflicts at doors with higher passenger volumes. Moreover, quantitative analyses for this problem and corresponding solutions are, limited in recent studies. In this research, conflicts at carriage doors are analyzed using a cellular automaton (CA) based model. Four schemes to separate alighting and passenger boarding into separate doors are investigated. The performances of different schemes with various alighting and boarding passenger ratios are simulated with the software package Legion Studio. Both macroscopic and microscopic parameters to characterize passenger conflicts are obtained for analysis. The separation of alighting and boarding passenger flows yields the desired reduction in bidirectional conflicts, which further limits the probability of infectious disease exposure. This is an important reference to improve current practices and provide specific measurements of passenger organization under abnormal situations. • Alighting and boarding strategy in the subway station is studied. • Cellular automata based simulation model is used to explore parameters' performance. • Alighting and boarding separation strategies reduce conflicts between subway passengers and proximity contact. [ABSTRACT FROM AUTHOR]

An improved cellular automata model based on car–truck combination effect oriented to faithfully reproducing the characteristics of heterogeneous traffic flow is presented in this paper. The model focuses on reflecting complex car-following and lane-changing behavior of cars and trucks by incorporating the difference of physical performance and driving behavior between cars and trucks and the behavioral change caused by car–truck interaction. The update rules of cars and trucks were constructed separately based on the analysis results of NGSIM and SP survey. The impact of the truck in front was introduced into the model, which can affect the lane-changing probability, safety expectation and randomization probability. As revealed by the simulation results, the driving of vehicles in the heterogeneous traffic (i.e. car–truck, truck–car, car–car and truck–truck) is reproduced properly through the model. In addition, the model is capable of reproducing the hysteresis phenomenon and identifying three typical traffic states, namely free flow, synchronized flow and jam. Under certain conditions, trucks can help to eliminate the propagation of congestion waves. Moreover, the percentage of trucks and truck impact have a significant influence on the fundamental diagram, congestion rate, lane-changing rate and traffic stability. The findings of this study can provide a basis for further research on the heterogeneous traffic. • The behavioral characteristics caused by car–truck interaction are considered. • The CA model is improved based on car–truck combination effect. • Trucks can help dissipate some congestion propagation. • The influence of truck impact on the heterogeneous traffic flow are studied. [ABSTRACT FROM AUTHOR]

With cooperative adaptive cruise control vehicles (CACC) development, the heterogeneous traffic flow of human-driven vehicles (HV) and CACC will appear on the same road. Although numerous studies have carefully analyzed the characteristic of the heterogeneous traffic flow, none of them considered the effect of the differences in acceptance of CACC by HV drivers on the heterogeneous traffic flow. In terms of the differences in car-following behaviors of HV drivers with diverse CACC acceptances, this paper deduces the capacity and stability of the heterogeneous traffic flow under different CACC penetration rates. Firstly, the HV driver's car-following behavior model with different CACC acceptability is calibrated through a questionnaire. Then, the analytical framework of the fundamental diagram and stability of the heterogeneous traffic flow is derived, according to the differences of HV drivers' acceptance of CACC. Finally, the paper analyzes the influence factors and effects of the heterogeneous traffic flow capacity and stability. The results indicate under different CACC penetration rates, the improvement of HV drivers' acceptance of CACC increases the capacity and stability of the heterogeneous traffic flow. When CACC penetration rate is lower than 96.35% and HV drivers' acceptance level of CACC is lower than the critical ratio, the popularity of CACC will decrease the stability of traffic flow. When the penetration rate of CACC is less than 34.76%, and HV drivers' acceptance level of CACC is lower than the critical proportion, the popularization of CACC will decrease the capacity of heterogeneous traffic. • Current driver acceptance of CACC and HV drivers' driving behavior in the heterogeneous traffic flow are investigated. • The fundamental diagram and stability analysis framework of the heterogeneous traffic flow considering HV drivers' CACC acceptance are derived. • The influence of HV drivers' CACC acceptance on the heterogeneous traffic flow capacity and stability under different CACC penetration rates are studied. • The critical HV drivers' CACC acceptance and CACC penetration rates to avoid the deterioration of the heterogeneous traffic flow operational due to the prevalence of CACC are extracted. [ABSTRACT FROM AUTHOR]