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The road network maintaining stability is critical for guaranteeing urban traffic function. Therefore, the vulnerable links need to be identified accurately. Previous vulnerability research under static condition compared the operating states of the old equilibrium before the event and the new equilibrium after the event to assess vulnerability ignoring the dynamic variation process. Does road network vulnerability change over time? This paper combines the vulnerability assessment with the traffic flow evolution process, exploring the road network vulnerability evaluation from the perspective of time dimension. More accurate identification and evaluation of vulnerable nodes and links can help to strengthen the ability of road network resisting disturbances. A modified dynamic traffic assignment (DTA) model is established for dynamic path selection (reselect the shortest path at the end of each link) based on the dynamic user optimal (DUO) principle. A modified cell transmission model is established to simulate the traffic flow evolution processes. The cumulative and time-varying index of vulnerability assessment is established from the viewpoint of traveler's time loss. Then the road network vulnerability assessment combined the traffic flow model with the vulnerability index. The road network vulnerability assessment of Bao'an Central District of Shenzhen, China, reveals that road network vulnerability does contain a dynamic process, and vulnerable links in each phase can be exactly identified by the model. Results showed that the road network would have a large vulnerability during the disordered phase when the main road fails. Therefore, prioritizing the smooth flow of main roads can weaken the impact of road network vulnerability exposure., Author(s): Yu Sun [1]; Binglei Xie (corresponding author) [1]; Shan Wang [1]; Dazhuang Wu [1] 1. Introduction Road traffic network is the material basis for the existence and effectiveness of [...]

The section deformation distribution of reinforced concrete components is nonlinear due to the size effect. Existing analysis models such as the plastic hinge and the truss element are based on the plane cross-section assumption. The nonlinear deformation distribution of the section cannot be accurately simulated. Therefore, in this paper, non-planar strain distribution functions of sections are established. The law of the influence of geometrical characteristics and load characteristics on the nonlinear deformation distributions of the sections of the beam ends is analyzed. The quantitative method is established between the section size, position, and shear span ratio, and the nonlinear deformation distributions of sections. The finite element simulation and test results show that the non-planar strain distribution shape functions of sections given in this paper can accurately describe the axial strain distributions of different sections along the height and width of the sections. The non-planar deformation behaviors and mechanical properties of the components can be simulated. The interface connection accuracy is improved in the structural multiscale simulation. [ABSTRACT FROM AUTHOR]

Since the outbreak of COVID-19, there have been hundreds of millions of confirmed cases in the world, and people can strongly perceive the risk of infection with the virus in their daily lives, which has seriously affected people's life and travel, thus hindering the development of all sectors of society, especially the transportation sector. Taking China as an example, since the outbreak of the pandemic, China's overall public transportation passenger volume has decreased by about 37%, seriously affecting the normal running of the public transit. Therefore, the ways of ensuring the normal running of the public transport system during the pandemic has become the focus of this paper. In order to solve this problem, this paper constructed a SEM model based on pandemic risk perception, analyzed the impact of public transit pandemic prevention strategies (TPS) on risk perception (RP) and travel mode use according to the personal trip survey data in Harbin, China during the pandemic. The results showed that people's risk perception had a significant negative impact on car usage and transit usage. In other words, people's risk perception of virus infection had a great impact on travel, especially on the use of public transit. The transit pandemic prevention strategy had a significant negative impact on risk perception, and had a significant positive impact on people's use of transit. This showed that in the current pandemic outbreak period, the transit pandemic prevention strategy proposed by the Harbin authorities cannot effectively reduce transit usage, and can provide proven and effective transit pandemic prevention strategies. This provided an important support for ensuring the normal running of the public transit system and guiding the sustainable development of public transit during the outbreak of the pandemic. [ABSTRACT FROM AUTHOR]

Bus bunching is a common phenomenon caused by irregular bus headway, which increases the passenger waiting time, makes the passenger capacity uneven, and severely reduces the reliability of bus service. This paper clarified the process of bus bunching formation, analyzed the variation characteristics of bus bunching in a single day, in different types of periods, and at different bus stops, then concluded twelve potential factors. A hybrid model integrating a genetic algorithm with elitist preservation strategy (eGA) and decision tree (DT) was proposed. The eGA part constructs the model framework and transforms the factor identification into a problem of selecting the fittest individual from the population, while the DT part evaluates the fitness. Model verification and comparison were conducted based on real automatic vehicle location (AVL) data in Shenzhen, China. The results showed that the proposed eGA–DT model outperformed other frequently used single DT and extra tree (ET) models with at least a 20% reduction in MAE under different bus routes, periods, and bus stops. Six factors, including the sequence of the bus stop, the headway and dwell time at the previous bus stop, the travel time between bus stops, etc., were identified to have a significant effect on bus bunching, which is of great value for feature selection to improve the accuracy and efficiency of bus bunching prediction and real-time bus dispatching. [ABSTRACT FROM AUTHOR]

In contrast to private cars, rail transit systems are a more effective way to deal with the emerging challenges in cities with high population densities, such as congestion, air pollution, and traffic emissions. Rail transit systems, however, are commonly costly, due to substantial investments in construction and maintenance. It is thus necessary to design the candidate rail transit systems carefully to ensure public transport accessibility and sustainability, with consideration of the space-time correlation of population densities. In this paper, the space-time correlations of population densities are incorporated into the design of a candidate rail transit line over years. A closed-formed mathematical programming model is proposed, with an optimisation objective of social welfare budget maximisation. The social welfare budget is defined as the summation of the expected social welfare and social welfare margins. The model decision variables include rail line length, rail station number, and project start time of the candidate rail transit line. The analytical solutions for the proposed rail design model are given explicitly for different scenarios with various constraints. [ABSTRACT FROM AUTHOR]

This study is devoted to handle disturbances occurring in a subway network during the off-peak period. By dissecting the relationship of transfer connections between connected lines, transfer passengers and non-transfer passengers as well as operating agencies are taken into consideration, respectively, and a trade-off method for timetable rescheduling is proposed to minimize the waiting time of all transfer passengers as well as the deviation from the planned timetable. We adopt the 𝜀 -constraint method to convert the bi-objective model to an integer linear programing model with single objective, which can be solved by CPLEX within seconds. The method is validated by some numerical experiments based on a real-world case derived from the Beijing Subway network. Results show that the proposed method is able to generate approximate Pareto optimal solutions and to provide decision support for dispatchers. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the implementation flexibility of multiperiod rail line design in a linear monocentric city. Three alternatives (fast-tracking, deferring, and do-nothing-alternative (DNA) of a candidate rail line project) are examined, based on an in-depth uncertainties analysis of the demand side for this candidate rail line project. Conditions for the three alternatives of fast-tracking, deferring, and DNA are analytically explored and an illustrative example is given to demonstrate the application of the proposed models. Insightful findings are reported on the interrelationship between the rail line length and spatial and temporal correlation of population distribution as well as the implication of the correlation in practice. Sensitivity analyses are carried out in several scenarios in another numerical example to show the proposed conditions of three alternatives. [ABSTRACT FROM AUTHOR]

Aiming at the dense urban road network vulnerability without structural negative consequences, this paper proposes a novel non-structural road network vulnerability analysis framework. Three aspects of the framework are mainly described: (i) the rationality of non-structural road network vulnerability, (ii) the metrics for negative consequences accounting for variant road conditions, and (iii) the introduction of a new vulnerability index based on user exposure. Based on the proposed methodology, a case study in the Sioux Falls network which was usually threatened by regular heavy snow during wintertime is detailedly discussed. The vulnerability ranking of links of Sioux Falls network with respect to heavy snow scenario is identified. As a result of non-structural consequences accompanied by conceivable degeneration of network, there are significant increases in generalized travel time costs which are measurements for “emotionally hurt” of topological road network. [ABSTRACT FROM AUTHOR]

As China's urbanization process continues to accelerate, the demand for intercity residents' transportation has increased dramatically. Holiday travel has different demand characteristics, causing serious shortage during peak periods. However, current research barely focuses on the passenger flow prediction along with travel characteristics of intercity shuttles. Accurately predicting passenger flow during the holidays helps to improve operational organization efficiency and residents' satisfaction, and provides a basis for reasonable resource allocation by the management department. This paper analyzes the spatiotemporal characteristics of intercity shuttles passenger flow in the Pearl River Delta. Separate passenger flow prediction models on non-holiday and holiday are established using an improved genetic algorithm optimized back propagation neural network (IGA-BPNN) based on the characteristics of passenger flow, and the prediction models are validated based on panel data. The results of weekly flow show obvious holiday characteristics, and the hourly traffic flow of holidays is much larger than that of weekends and weekdays. There is a significant difference in the hourly flow between different holidays. The IGA-BPNN model used in this paper achieves lower prediction error relative to the benchmark BPNN approach (leads a two thirds reduction in MAPE, and an over 85% reduction in MSPE). [ABSTRACT FROM AUTHOR]

Urban rail transit passenger flow forecasting is an important basis for station design, passenger flow organization, and train operation plan optimization. In this work, we combined the artificial fish swarm and improved particle swarm optimization (AFSA-PSO) algorithms. Taking the Window of the World station of the Shenzhen Metro Line 1 as an example, subway passenger flow prediction research was carried out. The AFSA-PSO algorithm successfully preserved the fast convergence and strong traceability of the original algorithm through particle self-adjustment and dynamic weights, and it effectively overcame its shortcomings, such as the tendency to fall into local optimum and lower convergence speed. In addition to accurately predicting normal passenger flow, the algorithm can also effectively identify and predict the large-scale tourist attractions passenger flow as it has strong applicability and robustness. Compared with single PSO or AFSA algorithms, the new algorithm has better prediction effects, such as faster convergence, lower average absolute percentage error, and a higher correlation coefficient with real values. [ABSTRACT FROM AUTHOR]

With growing traffic congestion and environmental issues, the interactions between travel behaviour and the built environment have drawn attention from researchers and policymakers to take effective measures to encourage more sustainable travel modes and to curb car trips, especially in urbanising areas where travel demand is very complicated. This paper presents how built environmental factors affect public transit choice behaviour in urban villages in China, where a large population of low-income workers are accommodated. This location had a high demand for public transit and special built environmental characteristics. Multinomial logistic regression was employed to examine both the determinants and magnitude of their influence. The results indicate that the impacts of built environments apply particularly in urban villages compared to those in formal residences. In particular, mixed land use generates an adverse effect on public transit choice, a surprising outcome which is contrary to previous common conclusions. This study contributes by addressing a special type of neighbourhood in order to narrow down the research gap in this domain. The findings help to suggest effective measures to satisfy public transit demand efficiently and also provide a new perspective for urban regeneration. [ABSTRACT FROM AUTHOR]

In this paper, we propose a face recognition algorithm by incorporating a neighbor matrix into the objective function of sparse coding. We first calculate the neighbor matrix between the test sample and each training sample by using the revised reconstruction error of each class. Specifically, the revised reconstruction error ( RRE ) of each class is the division of the l 2 -norm of reconstruction error to the l 2 -norm of reconstruction coefficients, which can be used to increase the discrimination information for classification. Then we use the neighbor matrix and all the training samples to linearly represent the test sample. Thus, our algorithm can preserve locality and similarity information of sparse coding. The experimental results show that our algorithm achieves better performance than four previous algorithms on three face databases. [ABSTRACT FROM AUTHOR]

The cost-efficiency of public transport systems is a helpful measure for regulators to establish an effective subsidy mechanism. This study presents a cost-efficiency measurement model of bus routes based on stochastic frontier analysis, taking into account not only heterogeneous outputs but also operating environment factors. In addition, four new operating environment factors that can affect the efficiency of bus routes are introduced. An empirical analysis, based on 39 routes operating in Jiangyin City, China, is presented. It was found that vehicle kilometres have a bigger impact on total operating costs than other parameters such as fixed inputs and fuel price. Operating environment factors such as average bus stop density and the percentage of bus lanes have significant influences on cost-inefficiency differentials. Furthermore, the measurement of cost-efficiency enables identification of the difference between actual total operating costs and efficient total operating costs at a bus route level. The proposed approach could support regulators in setting reasonable cost benchmarks based on efficient total operating costs. [ABSTRACT FROM AUTHOR]

Vehicle drivers usually perceive a higher risk when driving on snow covered roads. The city cleaning efficiency would directly influence the risk and mitigation of wintertime events, especially for snow covered roads. Under the risk-informed approach background, more attention is paid to the capacitated arc routing problem (CARP) of urban snow plowing operations. Current algorithms mainly relies on the topology of road network without considering snow covered pavement's negative effect on road capacity and traffic flow. This paper proposes a vulnerability-based parallel heuristic algorithms applied for the CARP by implementing risk-informed approach. First, a method is proposed to set service priorities based on the vulnerability evaluation by considering the added cost of travel demands. Second, a sub-process path-scanning approach is developed to avoid redundant path scans. Then verification and comparison between this newly proposed constructive heuristic and existing algorithms of whole-process path-scanning and sequential processing are conducted. Results show that the sub-process path-scanning approach obviously costs less service completion time than the existing algorithms for solving the CARP. However, this improved algorithm would also cause an increase of deadhead time upon dispatch. The balance between service completion time and deadhead time for more routing problems would be discussed in the near future.