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In order to enhance passenger willingness to choose buses for commuting and to reduce the operating costs and tailpipe emissions of bus companies, a bus scheduling model is established. The model aims to minimize the sum of the operating costs of the bus company, the costs associated with the loss of passengers' interest, and the cost of tailpipe emissions. It considers constraints such as maintaining an average load factor of the buses above 60%, ensuring a departure interval of greater than 5 min during non-peak hours and less than 30 min during peak hours, and limiting the maximum number of buses allocated to a route. The passenger flow is divided into peak hours and nonpeak hours according to the survey of passenger flow during each period of a bus operation on a route in Nanjing City, China. A genetic algorithm is employed to solve the proposed bus scheduling model and determine the total costs during peak and non-peak hours. After designing the parameters of the genetic algorithm, optimal departure intervals and bus numbers for a day's operation cycle on a given route are calculated using a weighting method. [ABSTRACT FROM AUTHOR]

The urban slow traffic system refers to the traffic system in the city that can allow people to walk, ride, travel by bus and other slow travel. Through 4,728 papers on slow moving system in China from 2000 to 2020 included in CNKI, analysis and summary of literature publishing trend, research strength, research focus and development trend are conducted based on CiteSpace software. It is expected to provide reference for future research in this field. [ABSTRACT FROM AUTHOR]

The aim of this study was to understand passengers' continuance use intention with respect to autonomous buses (ABs) based on actual riding experience. Therefore, an extended technology acceptance model taking characteristics of both autonomous driving and buses into account was proposed, and 576 passengers with ABs riding experience in China responded to the survey. Several findings were revealed. First, characteristics of buses (including perceived in-vehicle safety, service quality and general attitudes toward buses) had positive effects on continuance use intention. Second, perceived road safety was not directly associated with continuance intention but had positive effects on perceived usefulness. Third, two significant moderating variables were revealed, namely, past bus riding habits and driver reliance (i.e., the degree to which passengers considered it important for ABs to have a driver). These observations suggest practical implications for policymakers and automakers. • •This paper explored the continuous use intention of autonomous buses in China. •; •A model considering the autonomous buses' riding experience was proposed. •; •Two moderator variables (past bus riding habits and driver reliance) were verified. •; •Perceived road safety and in-vehicle safety had different effects. •; •Perceived enjoyment had effects on continuance intention to use autonomous buses. [ABSTRACT FROM AUTHOR]

• There are significant satisfaction differences in bus traveling before and after COVID-19. • COVID-19 has severely affected satisfaction with bus traveling of low-income individuals. • Low-income individuals' satisfaction with bus traveling is determined by socioeconomic attributes rather than traveling attributes after COVID-19. • Risk concern has a significant positive impact on risk perception, but risk concern and risk perception have only a minor impact on satisfaction before and after COVID-19. • There is a significant relationship between satisfaction levels and modes of traveling alone and traveling with companions by bus. Although all cities in China have promulgated public transportation control measures to choke off the spread of COVID-19, it also has brought severe changes to low-income individuals' bus traveling. However, the study focusing on satisfaction differences in bus traveling before and after COVID-19 is far under-researched, this paper therefore explored satisfaction differences among low-income individuals under socioeconomic attributes, traveling attributes, and psychological attributes by using the data consist of interviews addressed to 930 individuals in Taiyuan, China. Furthermore, the relationship between satisfaction levels and modes of traveling alone and traveling with companions by bus has also been deeply analyzed to reduce single-person driving problem. As a result, many exciting phenomena were discovered: the significant factors affecting low-income individuals' satisfaction occur "shift" on a large scale after COVID-19; risk concern has a significant positive impact on risk perception, but risk concern and risk perception have only a minor impact on satisfaction before and after COVID-19; it was found that there is a significant relationship between satisfaction levels and modes of traveling alone and traveling with companions by bus. Understanding them can be a reference for improving the travel environment between low-income individuals. [ABSTRACT FROM AUTHOR]

This study presents a multi-objective optimization model for the urban electric transit network problem with the aim of simultaneously designing the layout of bus routes, the frequency and the location and size of charging stations by making a tradeoff between two inconsistent objectives from the perspectives of passengers and operators. A Pareto artificial fish swarm algorithm (PAFSA) embedded with the genetic algorithm (GA) is developed to solve the proposed model. The PAFSA is designed to iteratively search for the proper network configuration satisfying two conflicting objectives. During which, the demand assignment with real-time transit information is performed to update the frequency of each newly designed route. The GA embedded into the PAFSA iteratively decides the locations of charging stations and the number of chargers to be installed in each charging station. A case study of the transit network in an urban region of a city in China is implemented, revealing that the proposed approach is able to rationally design a relatively large-scaled transit network with searching for the best fits between two inconsistent objectives. [ABSTRACT FROM AUTHOR]

The spatial distribution of bus garages determines the total vehicular dead mileage of the transit system because buses must travel between bus garages and terminals at the start or conclusion of a day. By contrast, the size of the garages determines the queuing status when buses enter or leave the garages. Thus, a bus garage system with reasonable distribution and size is required to address these problems. In this article, a queuing–location–allocation model for optimizing a bus garage system is developed. Since a nonlinear objective function is involved, a linearization technique is introduced to convert the proposed model into an equivalent linear form. Next, a Lagrangian relaxation algorithm is designed to solve the linear form model. To validate the proposed algorithm, two groups of randomly generated test instances and a real-life case, the Dalian transit system in China, are applied. The results show that the proposed Lagrangian heuristic is efficient and stable. [ABSTRACT FROM AUTHOR]

Exclusive bus lanes have been widely regarded as an effective way to promote bus priority and improve the service quality, while they have not attracted more passengers to travel by bus in China. Also, more attention is usually paid to the infrastructure and facilities of exclusive bus lanes, but not much attention is paid to the passenger satisfaction of public transit with them. Therefore, this paper studies how to improve the service quality of public transit with exclusive bus lanes from a perspective of passenger satisfaction. A Structural Equation Model (SEM) was developed to investigate the mechanism of relationships between passenger satisfaction and the factors influencing the service quality of public transit with exclusive bus lanes. A total of 2087 respondents from Shanghai, China, participated in this study. Also, a comparison model of different groups using public transit including captive riders, choice riders, and captive by choice riders was established. Results show that passengers were dissatisfied with the current service of public transit with bus lanes, while they would prefer to take buses in the near future. In addition, travel environment, facilities, and convenience, rather than operational efficiency, had significant effects on passenger satisfaction. Through the comparison model, it was found that choice and captive by choice users might prefer public transit with bus lanes and captive users might be unable to bear the financial burden of private motorized travel. "Crowdedness in the buses on bus lanes during peak hours" especially for choice riders and "driving stability" especially for captive riders were the improvement direction for attracting more passengers to travel by bus. The results and the proposed policies of this study can benefit for the planning and operations of exclusive bus lanes in Shanghai and other similar cities around the world. [ABSTRACT FROM AUTHOR]

This paper envisions and assesses the performance of an autonomous bus-on-demand (ABoD) system. We take Fuyang, Zhejiang, China, as the study area to investigate the spatiotemporal distribution of bus travel demand during workdays, and we propose replacing inefficient bus routes with the ABoD system. Agent-based models with various bus dispatching and operation control strategies are constructed to evaluate the performance of the ABoD system. The behaviors and interactions of the agents, passengers, autonomous buses, and a control center are designed. After the verification of the simulated bus travel demand with real-world demand, a series of scenarios with various ABoD operation strategies are simulated. The simulation results show that, in comparison with both current fixed-schedule bus services and the optimized bus dispatching strategies, the ABoD system occupies fewer road resources and utilizes bus vehicles more efficiently. Besides, the system is adaptive to the sudden surge in bus travel demand and is economically sustainable. [ABSTRACT FROM AUTHOR]

This paper aims to explore the factors influencing passengers' satisfaction toward bus transit and develop the improvement strategy for the small-medium city. Data including individual attributes, travel activity attributes, and perceived service attributes were collected in the city of Weinan, China. The ordered logit (OL) model and ordered Probit (OP) model were employed to explore the significant factors associated with passengers' satisfaction toward bus transit. The odds ratio (OR) was applied to quantitatively measure the effects of the significant factors. Improving strategies of bus transit service were proposed based on the model results using the three-factor theory. Results show that the OL model outperforms the OP model. The age, daily average waiting time, perceived waiting time, transferring convenience, the attitude of the driver, intelligent travel information service, hygienic environment inside the bus, ticket price, bus route setting, and bus stop setting significantly affect the passengers' satisfaction. Among them, the ticket price, perceived waiting time, bus stop setting, intelligent travel information service, transferring convenience, and bus route setting were identified as exciting factors. It is recommended that optimization of bus route and bus stop setting, building bus dedicated lanes, optimizing dynamic charging system, and providing intelligent travel information service could be effective strategies to improve passengers' satisfaction toward bus transit in Chinese small-medium cities. [ABSTRACT FROM AUTHOR]

To prevent bus bunching, a dynamic headway control method in the V2I (vehicle to infrastructure) environment for a high‐frequency route with bus lane is developed. Bus operating speed guidance on the mid‐blocks and intersection signal adjustment are two main strategies in the proposed method. A forecasting model of bus travel time under the dynamic control method is developed. The objective function is set up by taking into account differences between actual bus headways and dispatching headways, and the scaling ratios of intersection cycle lengths. The optimization model is solved using genetic algorithm. The proposed method is applied to a real bus route in Meihekou city, China, and compared with the current control plan as well as holding strategy. Results show that the proposed method can reduce bus headway deviations in all investigating periods; negative impacts on cars can be limited by setting reasonable values for the parameters. [ABSTRACT FROM AUTHOR]

An important aspect of Intelligent Public Transportation Systems (IPTS) is providing accurate travel time information. Knowing arrival times of public vehicles in advance can reduce waiting times of passengers and attract more people to take public transport. Existing approaches have two main limitations in the field of bus travel time prediction. First, influenced by increasingly complex real-time traffic factors and sparsity of real-time data, bus travel times can be difficult to predict accurately in modern cities. Second, bus dwelling and transit times are predominantly affected by different factors and hence have different patterns, but little research focuses on how to divide dwelling and transit areas and to build independent models for them. Consequently, we propose a novel segment-based approach to predict bus travel times using a combination of real-time taxi and bus datasets, that can automatically divide bus routes into dwelling and transit segments. Two models are built to predict them separately by incorporating different impact traffic factors. We evaluate our approach using real-world trajectory datasets, collected in Xi'an, China during June 2017. Compared to existing methods, the experimental results reveal that our approach improves the accuracy of bus travel time prediction, especially under abnormal traffic conditions. [ABSTRACT FROM AUTHOR]

Highlights • Jointly optimize stops, routes, timetables and passengers' mode choices for CB. • A heuristic solution to efficiently discover CB customers and generate bus lines. • A numerical experiment to verify the optimality gap of the heuristic solution. • Case study using a real-world city-scale taxi trajectory data set. Abstract A customized bus (CB) system is an emerging public transportation that aims to provide direct and efficient transit services for groups of commuters with similar travel demands. Existing CB systems aggregate similar travel demands and plan bus lines manually, which is inefficient and costly. In this paper, we propose a CB line planning framework called CB-Planner, which is applicable to multiple travel data sources. A mathematical programming formulation is proposed to simultaneously optimize bus stop locations, bus routes, timetables and passengers' probabilities of choosing CB. We then developed a heuristic solution framework that includes a grid-density based clustering method for discovering potential travel demands efficiently, a bus stop deployment algorithm to minimize the number of stops and walking distance, and dynamic programming based routing and timetabling algorithms for maximizing estimated profit. We conduct an experiment on a small-scale network to verify the performance gap between the optimal solution and our proposed heuristic solution. A case study is then conducted on one-month taxi trajectory data in Nanjing, China. The study demonstrates that CB lines generated by our CB-Planner can achieve higher profit compared with baseline methods, and they also provide efficient transit services with short walk distances and small departure time adjustments. The moderate increase in travel time is paid off by the significant savings in travel fare. [ABSTRACT FROM AUTHOR]

With the development of social economy and health care technology, people are expected to live longer, and the world's population tends to be ageing. As one of the services for elderly people, the concessionary bus travel programme provides a kind of social welfare for elderly people, while peak-hour traffic pressures (e.g., traffic congestion, traffic injuries, and travel discomfort) faced by elderly people have been ignored. This paper attempts to help society create a better travel environment for elderly people by analysing their travel behaviours. Specifically, using household survey data from Beijing, the statistical analysis is used to paint a more detailed picture of daily travel experience of elderly people with regard to departure times, travel purposes, travel mode choices, etc. Then, a nested logit model is employed to interpret travel patterns of elderly people. The results show that the bus plays the most important role in motorized travel of elderly people. Furthermore, the free bus programme has induced only 4.85% of bus travel among elderly people, indicating that the programme has little effect on elderly people's bus choices. Based on the results of the analysis, several options are proposed in this paper to help society adapt to the changing demographics. [ABSTRACT FROM AUTHOR]

Highlights • A new model is proposed to optimize transit routes for the least total travel time. • Transfer time composition is considered in the transit network optimization. • A genetic algorithm is newly presented to solve the proposed model. • Optimal solution to the transit network design can be provided rationally. Abstract In order to minimize the total time cost of all the trips, a new transit network optimization model is developed in consideration of reducing not only time-consuming transfers but also trips which have to make relatively more transfers by optimizing the layout of the transit routes. In contrast to commonly taking the time cost of a transfer in a trip roughly as a constant in a public transit network design work, this research attaches much importance to the effect of the transfer time composition on the total time expense of a transit trip. A genetic algorithm is proposed to solve the newly developed optimization model. The bus route network in an urban region of a city in China is studied for example in this research. It is confirmed that the new optimization model solved by the proposed genetic algorithm is able to more rationally provide the optimal solution to the design of a relatively large-scaled transit network for its efficient operation. In future research, more experiments are necessary to further validate and improve the effectiveness and efficiency of applying the new model solved by the proposed genetic algorithm. [ABSTRACT FROM AUTHOR]

In China, overlapped routes from multiple bus lines are widespread. Some buses are overcrowded while others have few passengers. The goal of this study is to reduce onboard passenger crowding without wasting bus capacity. This paper examines an extended multiple-depot vehicle scheduling problem (VSP) with multiple vehicle types. First, a bi-objective integer programming model was created. The trade-off between operating cost and passenger travel cost was established and the crowding cost due to different vehicle sizes was especially considered. Then, the capacity restraint incremental assignment algorithm and a vehicle scheduling method with multiple vehicle types were developed to find Pareto-optimal solutions that considered vehicle capacity constraints. Finally, the proposed methodology was validated using a real-world transit network in Beijing, China. The optimization results from about 1.18 million bus card swiping records show that our model and solution algorithm can effectively reduce the passenger crowding cost and avoid the waste of transport capacity. [ABSTRACT FROM AUTHOR]

Accidents, bad weathers, traffic congestions, etc. led to the uncertainties of travel times in real-life road networks, which greatly affected the quality of individual’s life and the reliability of transportation system. This paper addressed the school bus routing problem in such a stochastic and time-dependent road environment. Firstly, the problem was set based on a single-school configuration, and the students were picked up at their homes, which was in line with the current situation of school bus systems in China. Thus, it could be regarded as an independent problem of school bus route generation in random dynamic networks, which could be solved as a variant of extended Vehicle Routing Problem. However, due to the fluctuation and uncertainty of link travel times, the arrival time at each stop including the destination was varying. Therefore, the selection of optimal path connecting the current service node with the next one was treated as a sub-problem in this study, where the reliability of travel times in the stochastic and time-varying network was highly concerned by such time-rigid commuters. To this end, a Robust Optimal Schedule Times model with a hard time windows constraint was built to generate a most cost-reliable route for school buses. By the use of Robust Optimization method, it was intended to minimize the worst-case total cost which combined the cost of earlier schedule delays with the disutility of travel times. It was also proved that the proposed model could be converted into solving a conventional problem in deterministic dynamic networks for a reduction of computation complexity, which provided the potential of applying to the practical problems. Finally, the validity of the proposed model and its performance evaluation was analyzed through a small-scale computational instance, where all the link travel times in the simulated network were attributed to both time-varying and stochastic. Then, a mathematical programming solver was used to find the exact optimal solution. The results indicated that the model was valid, and the necessity of considering the stochastic and time-dependent nature of transportation networks was also confirmed in the case study. [ABSTRACT FROM AUTHOR]

This study develops an independent efficiency measurement model framework of bus routes, so as to treat preferably the heterogeneous outputs in a data envelopment analysis (DEA)-based efficiency measurement. It then introduces four new exogenous operating environment factors at the microscopic level of bus routes, and applies the three-stage DEA approach to incorporate operating environment effects and statistical noise into the efficiency measurement framework. The main purpose is to measure impartially the managerial efficiency of bus routes, purged of operating environment effects and statistical noise, and additionally to investigate the operating environment effects on efficiency. An empirical analysis, based on 39 routes operated in Jiangyin City, China, is presented. The principal finding is that the adoption of the independent efficiency measurement model framework is reasonable and has many virtues. Moreover, the proposed approach could substantially provide decision support both for regulators and for producers of bus services. In addition, the operating environment does indeed significantly affect operating efficiency and quality efficiency, especially the latter. [ABSTRACT FROM PUBLISHER]

• Bus bunching occurs much fewer in observations than in conventional models. • Counteraction between link and stop headway deviations can resist bus bunching. • Superposition between link and stop headway deviations destroys headway regularity. • Counteraction is more prominent than superposition with buses moving forward. • The counteraction effect owes to drivers' reactions to bus travel time deviations. Bus headway deviations are the major causes of bus bunching, which is detrimental to bus service reliability and leads to excessive waiting time for passengers. Generally, it is believed that bus bunching is an inevitable result once a service disturbance occurs, as long as the route is long enough. However, in this study, it goes as low as 5% of all trips from the empirical data, contradicting the expectation in theory. This study explores the underlying reasons for this contradiction based on empirical data from two representative bus routes in China. The results show that headway deviations on links and at stops mostly counteract with each other, constraining the occurrence of bus bunching. Under this counteraction effect, the path headway deviations remain within a stable range, normally bounded by the planned headway. It indicates that the bus system has a self-repair ability to resist headway disruptions, which explains why bus bunching happens at a considerably lower frequency in practice than in theory. We further discuss how the counteraction effect works. The insights gained from this study can shed light on preventing bus bunching and generating new ways to recover bus service regularity after a headway disruption. If we can adequately adjust the control methods to make the link and stop headway deviations counteract with each other, the bus system can automatically mitigate the headway deviations. [ABSTRACT FROM AUTHOR]

Customized bus (CB) provides convenient door-to-door transportation services to passengers through a subscription-based model. To ease the problem of insufficient taxis and private hire services at large transport terminals, we propose and evaluate a customized CB service for railway stations and airports in China. The proposed CB problem considers a routing problem with time-dependent travel time and late-customers. A periodic optimization approach is adopted to periodically collect passenger demands, optimize customized bus routes for the period, and re-optimize the routes to cater to late-coming customers. The static problem for each period is modeled as a time-dependent customized bus routing problem with time windows and release date (TDCBRPTW-R), which is solved with a hybrid meta-heuristic algorithm combining adaptive large neighborhood search (ALNS) with variable neighborhood descent (VND). An acceleration method is developed for insertion feasibility check for the TDCBRPTW-R. The stability and accuracy of the proposed algorithm is evaluated in the numerical experiments derived from Solomon's data set. For the periodic re-optimization procedure, four methods are proposed to handle late customers according to different application scenarios. The re-optimization procedure is tested on the road network in Chengdu with passenger data provided by Didi Chuxing. The experiments demonstrate that a loose time window allows the service to serve more passengers and reduces operational costs. Lastly, the experiments also show the effectiveness of the proposed methods in handling late customers. • A periodic customized bus service for large transport terminals in China. • A static MIP model for the static problem with time-dependent travel time. • A hybrid meta-heuristic algorithm with an accelerated feasibility check method. • Dynamic optimization approaches to handle late customers. • Comprehensive experiments on both the static problem and the dynamic problem. [ABSTRACT FROM AUTHOR]

Rises in the number of transit buses, bus routes, and overall traffic volume in China’s cities, coupled with interference from other transport modes, such as taxis loading and unloading passengers nearby, have led to increasing traffic delays at bus stops, which is considered one of the factors degrading service levels and traffic operations on urban roadways. This paper studies traffic characteristics at bus stops, investigates variations in delay from different types or designs of bus stops, and analyzes the impact of it on traffic capacity, the purpose of which is to propose a solution to predicting the feasibility of an integrated design of bus stops and taxi stands with the help of mathematical models and based on the objectives of optimal traffic operations and passenger transfer. [ABSTRACT FROM AUTHOR]

Visitors on sight-seeing tours in contemporary globalizing Shanghai observe the futuristic ambitions, exponential development and chaotic polyrhythmicity of New Shanghai. The nostalgia industry simultaneously 'teleports' the tourists on tours back to a time when Shanghai was a legendary world metropolis; the Golden Age of the inter-war era. Inspired by Henri Lefebvre's critical rhythmanalysis, and by Jonathan Sterne's conceptualization of communication as organized movement and action, this paper explores bus tours by commission of the municipal government. Shanghai is the place where the movements of the buses, as well as the tourists on board, become part of communicating the place identity and multiple rhythms of the city. The buses are conceived as means of communication, in a twofold sense, and as both underscoring and binding together the many incommensurabilities of place: old and new, Western and Chinese, industrialism and post-industrialism, nationalism and globalism. The author argues that mobility, media modernity and a confounding mixture (reflexively manifested on the tour ' Confused and Mixed Shanghai') constitute a collective memory of the city, and that the buses in all their seeming banality, communicate Shanghai's particular rhythms of retromodernity. [ABSTRACT FROM AUTHOR]

Abstract: The time control point strategy is often adopted by bus operators in China and Singapore to provide more reliable transit service. It is thus important to design a schedule, in which bus drivers should devote their efforts to catch up a scheduled arrival time at a predetermined time control point on a bus route because passengers can definitely benefit from a reliable bus route schedule. This paper first proposes a novel reliable bus route schedule design problem by taking into account the bus travel time uncertainty and the bus drivers’ schedule recovery efforts. It proceeds to develop a robust optimization model for the proposed problem, which aims to minimize the sum of the expected value of the random schedule deviation and its variability multiplied by a weighting value. A Monte Carlo simulation based solution method is subsequently designed to solve the robust optimization model. Finally, a numerical example based on a real bus route in Suzhou city of China is carried out to demonstrate the strength of the robust optimization model. We find that the optimal scheduled travel time (or slack time) depends on bus drivers’ schedule recovery behavior and on decision makers’ scheduling philosophies. [Copyright &y& Elsevier]

Bus cabin air quality has not been incessantly monitored in Hong Kong. This study investigates the in-cabin exposure levels of CO, CO2 and PM10 for running buses in Hong Kong that are equipped with Euro II, III and IV engines. A representative urban—suburban bus route was chosen and there were no significantly different in-cabin CO levels reported among engine types and between rush and non-rush hours. However, in-cabin CO level was found significantly associated with ambient/roadside CO level; the former was altogether higher than the latter due to the bus’ own exhaust. Regarding in-cabin PM10 concentration, the engine type played a major role. The outcome demonstrates that new buses (i.e. Euro IV) generally provide a better in-cabin environment for commuters. Therefore, implementation of an air filtration upgrade, together with a routine filter cleaning schedule, is an effective measure to ameliorate bus cabin air quality. This study also provides useful information for further investigation into the causal relationship between health risks and long-term air pollution exposure in local bus cabins. [ABSTRACT FROM PUBLISHER]

Bus travel-time prediction has attracted a lot of research interest in recent years. In the present study a support vector machine was applied to the bus travel-time prediction problem in an attempt to suggest a new model with better explanatory power and stability. Bus travel times forecast by the model were assessed using the data of transit route number 23 in Dalian, China. The results show that the support vector machine models outperformed the historic mean prediction model, the autoregressive integrated moving average and the artificial neural network model. [ABSTRACT FROM AUTHOR]

The setting of timetables and bus routing/scheduling are essential to an inter-city bus carrier''s profitability, its level of service and its competitive capability in the market. In the past, carriers in Taiwan usually set their timetables and bus routes/schedules manually, which was inefficient. In this research we thus attempt to develop a model that will help Taiwan inter-city bus carriers in timetable setting and bus routing/scheduling. The model employs multiple time–space networks that can formulate bus movements and passenger flows and manage the interrelationships between passenger trip demands and bus trip supplies to produce the best timetables and bus routes/schedules. Mathematically, the model is formulated as a mixed integer multiple commodity network flow problem. An algorithm, based on Lagrangian relaxation, a sub-gradient method, the network simplex method, a Lagrangian heuristic and a flow decomposition algorithm, is developed to efficiently solve the problem. The results of a case study, regarding a major Taiwan inter-city bus operation, illustrate the model performance. [Copyright &y& Elsevier]

With the popularity and development of mobile Internet, new transportation network services such as customized buses are expected to become a new way of popular transportation in crowded metropolises. In this paper, we propose a real-time customized bus routes design model. We divide the proposed model into two-stage problem to solve. The first stage problem is the vehicle route problem with time window (VRPTW), and the second stage problem is bilateral matching problem. For the first stage, the column generation algorithm is used to solve the problem. For the second stage, we solve it by the improved H-R bilateral matching algorithm. Finally, data on customized bus in Tianjin city of China are used to verify the accuracy of the real-time customized bus routes design model. The optimized results show that the average attendance rate has reached 70.8%, and the service rate of passenger has reached 88.5%. The results have proved that the real-time customized bus routes design model has a practical applicability in operation. [ABSTRACT FROM AUTHOR]

As urban roads are becoming more congested, bus travel is becoming increasingly popular in China. Numerous studies have shown that bus stop always has great effect on traffic flow near the bus stop. In this paper, the influence of bus bay on traffic flow in adjacent lane is studied. Based on the well-known KKSW (Kerner–Klenov–Schreckeneberg–Wolf) CA (cellular automaton) model, a new KKSW-BB (Bus Bay) CA model is proposed to simulate heterogeneous traffic flow composed of passenger cars and buses near a bus bay. Through numerical simulation, the traffic flow characteristics in adjacent lane are studied in the framework of Kerner's three-phase traffic theory. The frequency and severity of rear-end collisions are analyzed to research the influence of bus bay on traffic safety in adjacent lane. The results show that both the traffic efficiency and safety in adjacent lane can be negatively affected by the buses entering and leaving the bus bay. [ABSTRACT FROM AUTHOR]

Plug-in electric buses have great potential to enhance the profits of operators in multiple-microgrid systems via the use of vehicle-to-grid technology. In contrast to stationary energy storage units, a plug-in electric bus can move among different microgrids to provide not only passenger transportation service but also energy transportation service. In this paper, a single-leader and multiple-follower model based on the Stackelberg game method is proposed for the look-ahead dispatch of bus routes and power allocation in microgrids. First, a time-space trip model for a fleet of plug-in electric buses was established, and the total costs of the plug-in electric bus operator were optimized as a leader-level problem. Then a rolling energy management strategy was formulated as a follower-level problem to optimize the total costs of each microgrid operator and to deal with the prediction error of the distributed energy resources and loads. Next, the proposed bi-level optimization problem was transformed into a single-level mixed-integer linear programming problem. Finally, case studies were carried out on three real microgrids in China and on BYD-K9 plug-in electric buses. The simulation results indicated that the costs for a plug-in electric bus operator would decrease by 33.35% in the proposed bi-level model compared with the fixed charging model, and the costs for an isolated MG would decrease by 24.16% compared with the model regardless of the plug-in electric buses. • A time-space trip model was proposed to arrange the route of plug-in electric bus. • A rolling energy management strategy was introduced for the microgrid operators. • A single-leader and multiple-follower model was built to solve the proposed problem. [ABSTRACT FROM AUTHOR]

This paper presents a direct modelling approach to evaluate household travel energy consumption and CO 2 emissions based on the spatial form of neighborhoods and streets. It integrates one multinomial logit model and four double hurdle models to predict travel outcomes: vehicle ownership portfolio choice, car travel distance, bus travel distance, motorcycle travel distance and ebike travel distance. The energy consumption and CO 2 emissions are then estimated using these travel outcomes. A full application of the modelling approach is demonstrated through a pilot project in Jinan, China. A holdout validation is also performed to address the over-fitting problem of models calibrated from the training set data. Results show that the proposed approach is operational and appropriate for sketch planning applications to promote clean energy and low carbon city planning in urbanizing China. • A direct modelling approach to evaluate household travel energy consumption and CO 2 emissions is presented. • The approach assesses the impact of the spatial form of neighborhoods and streets. • A holdout validation is performed to address the over-fitting problem of calibrated models. [ABSTRACT FROM AUTHOR]