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Huijun Sun
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport (Beijing Jiaotong University) Ministry of Transport, Beijing, 100044, China

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Journal article
Published: 01 August 2021 in Fundamental Research
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The emergence of ridesplitting as a form of ridesourcing reduces the use of vehicles on the road. When connecting multiple ridesplitting orders and single orders to the sharing path, it can achieve higher sharing efficiency. This paper aims to further improve the vehicle sharing rate, and explore the impact of multi-mode sharing using the order data of Haikou, China provided by DiDi Chuxing. A shareability network combining the ridesplitting network and connection network is built based on the order data. We propose the on-demand matching algorithm with four matching objectives to obtain the dispatching strategy. The results show that the percentage of shared trips can reach 99%, the vehicle saving rate can reach 83%, and the average number of shared trips served by shared vehicles can reach about 6 with the time interval 20 min and maximum delay 300 s. When the maximum delay is 300 s, the percentage of orders that can be shared by multiple modes is about 30%. The average delay, idling time and waiting time of shared orders are slightly higher than the corresponding maximum delay, and increase with the increase of the maximum delay, while the change of saving time is the opposite. The proposed algorithm considers the impact of the maximum delay, which, compared with the maximum matching algorithm, has a significant improvement.

ACS Style

Yafei Li; Huijun Sun; Ying Lv. Collaborative matching of ridesplitting and connection in the ridesourcing market. Fundamental Research 2021, 1 .

AMA Style

Yafei Li, Huijun Sun, Ying Lv. Collaborative matching of ridesplitting and connection in the ridesourcing market. Fundamental Research. 2021; ():1.

Chicago/Turabian Style

Yafei Li; Huijun Sun; Ying Lv. 2021. "Collaborative matching of ridesplitting and connection in the ridesourcing market." Fundamental Research , no. : 1.

Journal article
Published: 03 June 2021 in Transportation Research Part B: Methodological
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Subway system is the main mode of transportation for city dwellers and is a quite significant backbone to a city's operations. One of the challenges of subway network operation is the scheduling of the first trains each morning and its impact on transfers. To deal with this challenge, some cities (e.g. Beijing) use bus ‘bridging’ services, temporarily substituting segments of the subway network. The present paper optimally identifies when to start each train and bus bridging service in an intermodal transit network. Starting from a mixed integer nonlinear programming model for the first train timetabling problem, we linearize and reformulate the model using the auxiliary binary variables. Following that, the bus bridging model is developed to cooperate with the first train operation for reducing long transfer waiting times. After realizing the low computational efficiency of solving the integrated model, a tailored algorithm is designed to optimally solve the first train timetabling and bus service bridging problems. The exact models and algorithms are applied to the Beijing subway network to test their effectiveness and computational efficiency. Numerical results show that our approaches decrease the total passenger waiting time by 53.4% by a combined effect of adjusting the first train departure times and operating 27 bridging buses on 7 routes.

ACS Style

Liujiang Kang; Hao Li; Huijun Sun; Jianjun Wu; Zhiguang Cao; Nsabimana Buhigiro. First train timetabling and bus service bridging in intermodal bus-and-train transit networks. Transportation Research Part B: Methodological 2021, 149, 443 -462.

AMA Style

Liujiang Kang, Hao Li, Huijun Sun, Jianjun Wu, Zhiguang Cao, Nsabimana Buhigiro. First train timetabling and bus service bridging in intermodal bus-and-train transit networks. Transportation Research Part B: Methodological. 2021; 149 ():443-462.

Chicago/Turabian Style

Liujiang Kang; Hao Li; Huijun Sun; Jianjun Wu; Zhiguang Cao; Nsabimana Buhigiro. 2021. "First train timetabling and bus service bridging in intermodal bus-and-train transit networks." Transportation Research Part B: Methodological 149, no. : 443-462.

Journal article
Published: 15 May 2021 in Decision Support Systems
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Travel restriction measures have been widely implemented to curb the continued spread of COVID-19 during the Chinese Lunar New Year celebrations. Many operation lines and train schedules of China's railway were either heavily adjusted or canceled. In this study, a mixed-integer linear programming model and a two-step solution algorithm were developed to handle such large-scale adjustments. The formulation considers a flexible time window for each operation line and locomotive traction operations, and minimizes the number of locomotives utilized with their total idle time for train rescheduling and locomotive assignment, respectively. The solution algorithm determines the minimum locomotive fleet size based on the optimal train rescheduling results; it then reduces the traction idle time of locomotives. In response to the uncertainty of COVID-19, two tailored approaches were also designed to recover and remove operation lines, which can insert and cut operation lines based on the results of locomotive assignment. Finally, we conducted a case study of the Beijing-Tianjin intercity railway from the start of the COVID-19 outbreak to the recovery of operations.

ACS Style

Liujiang Kang; Yue Xiao; Huijun Sun; Jianjun Wu; Sida Luo; Nsabimana Buhigiro. Decisions on train rescheduling and locomotive assignment during the COVID-19 outbreak: A case of the Beijing-Tianjin intercity railway. Decision Support Systems 2021, 113600 .

AMA Style

Liujiang Kang, Yue Xiao, Huijun Sun, Jianjun Wu, Sida Luo, Nsabimana Buhigiro. Decisions on train rescheduling and locomotive assignment during the COVID-19 outbreak: A case of the Beijing-Tianjin intercity railway. Decision Support Systems. 2021; ():113600.

Chicago/Turabian Style

Liujiang Kang; Yue Xiao; Huijun Sun; Jianjun Wu; Sida Luo; Nsabimana Buhigiro. 2021. "Decisions on train rescheduling and locomotive assignment during the COVID-19 outbreak: A case of the Beijing-Tianjin intercity railway." Decision Support Systems , no. : 113600.

Journal article
Published: 11 May 2021 in Accident Analysis & Prevention
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This paper designs a systemic framework to quantify speed reduction induced by traffic incidents using a causal inference framework. The results can provide a reference to traffic managers for evaluating incident severities, thus take proper control measures after the incident in order not to underestimate or overestimate the negative impact. A two-phase scheme is proposed, including impacted region determination and speed reduction quantification. We first propose a Frame Region (FR) method, based on the shockwave propagation, to determine the spatiotemporal impacted region (SIR) using speed map. It is worth-noting that we design a statistical experiment to prove the rationality of congestion threshold selection. Secondly, we introduce a causal inference method for identifying the matched freeway segments. The traffic condition of finally matched freeway segments can be served as non-incident traffic condition of the incident occurred location, which contributes to quantifying the incident impact on speed reduction. We further demonstrate the proposed method in a case study by taking advantage of an incident record and related real freeway speed data in China. An interesting observation is that, along with the freeway segments away from the incident location, the congestion duration time of different freeway segments firstly rises and then decreases. The case study also illustrates the impact of incident on speed lasts almost 3 h and the congestion caused by the incident spreads 11 km, while the average causal effect of incident on all the impacted freeway segments is 42.3 km/h.

ACS Style

Danni Cao; Jianjun Wu; Xianlei Dong; Huijun Sun; Xiaobo Qu; Zhenzhen Yang. Quantification of the impact of traffic incidents on speed reduction: A causal inference based approach. Accident Analysis & Prevention 2021, 157, 106163 .

AMA Style

Danni Cao, Jianjun Wu, Xianlei Dong, Huijun Sun, Xiaobo Qu, Zhenzhen Yang. Quantification of the impact of traffic incidents on speed reduction: A causal inference based approach. Accident Analysis & Prevention. 2021; 157 ():106163.

Chicago/Turabian Style

Danni Cao; Jianjun Wu; Xianlei Dong; Huijun Sun; Xiaobo Qu; Zhenzhen Yang. 2021. "Quantification of the impact of traffic incidents on speed reduction: A causal inference based approach." Accident Analysis & Prevention 157, no. : 106163.

Journal article
Published: 13 March 2021 in Transportation Research Part C: Emerging Technologies
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One-way car-sharing systems, an increasingly prominent transportation means, are facing the vehicle imbalance issue with their emergence. To overcome the problem, operators have adopted a common strategy to relocate vehicles among stations by dispatchers. However, along with this approach come imbalanced dispatchers, demanding double-balanced optimization for relocation operations in vehicle relocation and dispatcher scheduling. In this paper, we propose an integrated model to determine the optimal requests served, relocation tasks, and dispatchers’ routes in order to minimize the generalized daily operational cost. The model adopts two different time granularities to obtain all the possible relocation tasks and the refined scheduling of dispatchers. Due to the dynamic nature and the scale of this double-balanced relocation problem, a hybrid solution algorithm is designed combining a rolling horizon algorithm with a customized decomposition algorithm. The planning horizon consists of several stages, each of which contains a sub-problem for the double-balanced relocation, and a customized decomposition is embedded to optimize it efficiently. Some computational experiments and a case study in Lanzhou, China are conducted to identify critical parameters and illustrate the performance of the proposed method.

ACS Style

Shuang Yang; Jianjun Wu; Huijun Sun; Yunchao Qu; Tongfei Li. Double-balanced relocation optimization of one-way car-sharing system with real-time requests. Transportation Research Part C: Emerging Technologies 2021, 125, 103071 .

AMA Style

Shuang Yang, Jianjun Wu, Huijun Sun, Yunchao Qu, Tongfei Li. Double-balanced relocation optimization of one-way car-sharing system with real-time requests. Transportation Research Part C: Emerging Technologies. 2021; 125 ():103071.

Chicago/Turabian Style

Shuang Yang; Jianjun Wu; Huijun Sun; Yunchao Qu; Tongfei Li. 2021. "Double-balanced relocation optimization of one-way car-sharing system with real-time requests." Transportation Research Part C: Emerging Technologies 125, no. : 103071.

Review article
Published: 05 March 2021 in Frontiers of Engineering Management
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Safety is one of the most critical themes in any large-scale railway construction project. Recognizing the importance of safety in railway engineering, practitioners and researchers have proposed various standards and procedures to ensure safety in construction activities. In this study, we first review four critical research areas of risk warning technologies and emergency response mechanisms in railway construction, namely, (i) risk identification methods of large-scale railway construction projects, (ii) risk management of large-scale railway construction, (iii) emergency response planning and management, and (iv) emergency response and rescue mechanisms. After reviewing the existing studies, we present four corresponding research areas and recommendations on the Sichuan-Tibet Railway construction. This study aims to inject new significant theoretical elements into the decision-making process and construction of this railway project in China.

ACS Style

Liujiang Kang; Hao Li; Cong Li; Na Xiao; Huijun Sun; Nsabimana Buhigiro. Risk warning technologies and emergency response mechanisms in Sichuan—Tibet Railway construction. Frontiers of Engineering Management 2021, 1 -13.

AMA Style

Liujiang Kang, Hao Li, Cong Li, Na Xiao, Huijun Sun, Nsabimana Buhigiro. Risk warning technologies and emergency response mechanisms in Sichuan—Tibet Railway construction. Frontiers of Engineering Management. 2021; ():1-13.

Chicago/Turabian Style

Liujiang Kang; Hao Li; Cong Li; Na Xiao; Huijun Sun; Nsabimana Buhigiro. 2021. "Risk warning technologies and emergency response mechanisms in Sichuan—Tibet Railway construction." Frontiers of Engineering Management , no. : 1-13.

Journal article
Published: 25 February 2021 in Transportation Research Part E: Logistics and Transportation Review
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With the growing urban population and its rapid growth of mobility needs, metro systems often suffer from congestion in peak hours in many mega-cities over the world. This incurs severe travel delays for commuters and safety risks for metro operators. Hence, passenger flow management and control becomes an essential way to reduce station congestion during high-peak hours. This paper investigates the passenger flow control problem with the objective of increasing the number of boarding passengers. Considering the scenario that the destination of each passenger entering the station is unknown, a flow control problem with dynamic and station-based constraints is proposed to dynamically determine the number of passengers boarding each train at each station. Compared with existing flow control strategies, this model can improve the equity for boarding passengers of different OD pairs. The station-based flow control problem is formulated as a complicated nonlinear nonconvex quadratic programming model. To solve the intractable nonlinear programming model, we reformulate it into the dynamic programming formation and develop two efficient heuristic algorithms to solve it. We carry out two sets of numerical experiments, including the small-scale case with synthetic data and the real-world case with the operation data of Beijing metro system, to evaluate the performance of our model and algorithms. Several performance indicators, e.g. average waiting time and Gini coefficient, are presented to verify the efficiency and fairness of proposed model. The numerical results applied to Beijing urban subway network indicate that our approach can reduce the passengers’ waiting time and the line-level Gini coefficient by 5.21% and 23.52% compared with the benchmark flow control strategy with maximum loading and station-based constraints.

ACS Style

Ping Zhang; Huijun Sun; Yunchao Qu; Haodong Yin; Jian Gang Jin; Jianjun Wu. Model and algorithm of coordinated flow controlling with station-based constraints in a metro system. Transportation Research Part E: Logistics and Transportation Review 2021, 148, 102274 .

AMA Style

Ping Zhang, Huijun Sun, Yunchao Qu, Haodong Yin, Jian Gang Jin, Jianjun Wu. Model and algorithm of coordinated flow controlling with station-based constraints in a metro system. Transportation Research Part E: Logistics and Transportation Review. 2021; 148 ():102274.

Chicago/Turabian Style

Ping Zhang; Huijun Sun; Yunchao Qu; Haodong Yin; Jian Gang Jin; Jianjun Wu. 2021. "Model and algorithm of coordinated flow controlling with station-based constraints in a metro system." Transportation Research Part E: Logistics and Transportation Review 148, no. : 102274.

Journal article
Published: 03 February 2021 in Computers & Industrial Engineering
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In station-based one-way carsharing system, the asymmetric demand-supply issue represents a toughing challenge. This problem affects the carsharing system’s level of service as well as the financial viability, and requires the engagement of a large amount of resources in redistributing the sharing cars to meet travelers’ need. Firstly, this paper proposes an approach involves the day-to-day dynamics of traveler’s ’learning behavior’ together with an adaptive incentivization scheme of the carsharing operator. Secondly, on each day, carsharing travelers make the route choice decisions according to their perceived travel costs, which can be affected by the past experience and the incentivization scheme of the carsharing operator. More specifically, the adaptive scheme does not require specific information about travelers’ behavior traits, is adopted by the operator so as to motivate travelers to rent their car from an over supplied station and/or return it to an under supplied station, thereby reducing the expected cost of relocating the cars using dedicated staff. What is more, travelers tend to discount the value of the incentive, making it less effective in relocations. Then, the equilibrium state and stability of the evolution model is examined. Finally, numerical experiments are conducted to illustrate the application of the approach.

ACS Style

Si Zhang; Huijun Sun; Ying Lv; Jianjun Wu. Day-to-day dynamics of traveler learning behavior and the incentivization scheme of the operator for one-way carsharing services. Computers & Industrial Engineering 2021, 155, 107170 .

AMA Style

Si Zhang, Huijun Sun, Ying Lv, Jianjun Wu. Day-to-day dynamics of traveler learning behavior and the incentivization scheme of the operator for one-way carsharing services. Computers & Industrial Engineering. 2021; 155 ():107170.

Chicago/Turabian Style

Si Zhang; Huijun Sun; Ying Lv; Jianjun Wu. 2021. "Day-to-day dynamics of traveler learning behavior and the incentivization scheme of the operator for one-way carsharing services." Computers & Industrial Engineering 155, no. : 107170.

Journal article
Published: 12 January 2021 in Transportation Research Part D: Transport and Environment
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Freight transportation contributes to increasing carbon emissions in the transportation sector. The CO2 emissions inherently caused by the intercity freight transportation between cities should be emphasized. This study first introduces the concepts of CO2 emission intensity (EI) based on the extraction of freight transportation information in the form of GPS trajectory data. A gravity theory-based intercity CO2 EI model is proposed, so that the driving forces of emission generation can be revealed. Then, we analyze the CO2 EI in terms of mobility characteristics, spatial autocorrelation, and influencing factors. Finally, the proposed method is applied to a typical case study of the Beijing-Tianjin-Hebei urban agglomeration for evaluation of an emission control policy. The findings provide a theoretical reference for analyzing the intercity connections within a regional urban agglomeration in terms of emissions, and support the implementation of feasible emission reduction strategies.

ACS Style

Guangtong Xu; Ying Lv; Huijun Sun; Jianjun Wu; Zhenzhen Yang. Mobility and evaluation of intercity freight CO2 emissions in an urban agglomeration. Transportation Research Part D: Transport and Environment 2021, 91, 102674 .

AMA Style

Guangtong Xu, Ying Lv, Huijun Sun, Jianjun Wu, Zhenzhen Yang. Mobility and evaluation of intercity freight CO2 emissions in an urban agglomeration. Transportation Research Part D: Transport and Environment. 2021; 91 ():102674.

Chicago/Turabian Style

Guangtong Xu; Ying Lv; Huijun Sun; Jianjun Wu; Zhenzhen Yang. 2021. "Mobility and evaluation of intercity freight CO2 emissions in an urban agglomeration." Transportation Research Part D: Transport and Environment 91, no. : 102674.

Journal article
Published: 31 December 2020 in International Journal of Environmental Research and Public Health
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With the rapid development of urbanization, the blind expansion of urban space has led to a series of social problems. In this process, the degree of urban function mixing affects the urbanization development level, making it particularly important to study the degree of coupling coordination between the two aspects. In this paper, taking Beijing as an example, we use urban point of interest (POI) data and taxi GPS trajectory data to calculate the urban POIs’ spatial entropy and taxis’ temporal entropy, based on the information entropy. We use the POIs’ spatial entropy and taxis’ temporal entropy to measure the urban function mixing degree. Also, the model of coupling coordination degree is used to measure the degree of coupling coordination between the urban function mixing degree and the urbanization development level. The results indicate the following: First, the POIs’ spatial entropy and taxis’ temporal entropy have significant regional imbalances. On the whole, both show a declining pattern when moving from the central urban area to the outer suburbs. The urban function mixing degree and urbanization development level are also higher in the central urban area than in the outer suburbs. Second, the coupling coordination among the urbanization development level, POIs’ spatial entropy, and taxis’ temporal entropy is distributed unevenly across various regions, which means that the three types of coupling coordination are in balanced development in the central urban area, but in unbalanced development in the outer suburbs. Third, from the perspective of spatial correlation characteristics, the higher is the degree of spatial agglomeration, the higher are the urban function mixing degree and urbanization development level, and the higher is the coupling coordination degree among the urbanization development level, POIs’ spatial entropy, and taxis’ temporal entropy. Therefore, relevant departments should plan the construction of urban functional areas reasonably, according to the degree of coupling coordination between the urban function mixing degree and the urbanization development level in different regions, so as to realize the healthy and sustainable development of a city.

ACS Style

Xuanxuan Xia; Kexin Lin; Yang Ding; Xianlei Dong; Huijun Sun; Beibei Hu. Research on the Coupling Coordination Relationships between Urban Function Mixing Degree and Urbanization Development Level Based on Information Entropy. International Journal of Environmental Research and Public Health 2020, 18, 242 .

AMA Style

Xuanxuan Xia, Kexin Lin, Yang Ding, Xianlei Dong, Huijun Sun, Beibei Hu. Research on the Coupling Coordination Relationships between Urban Function Mixing Degree and Urbanization Development Level Based on Information Entropy. International Journal of Environmental Research and Public Health. 2020; 18 (1):242.

Chicago/Turabian Style

Xuanxuan Xia; Kexin Lin; Yang Ding; Xianlei Dong; Huijun Sun; Beibei Hu. 2020. "Research on the Coupling Coordination Relationships between Urban Function Mixing Degree and Urbanization Development Level Based on Information Entropy." International Journal of Environmental Research and Public Health 18, no. 1: 242.

Journal article
Published: 16 December 2020 in International Journal of Environmental Research and Public Health
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The emergence and development of car-sharing has not only satisfied people’s diverse travel needs, but also brought new solutions for improving urban traffic conditions and achieving low-carbon and green sustainable development. In recent years, car-sharing has had competition with other ways of getting around, as the acceptance of car-sharing has grown, notably taxis. Therefore, it is particularly important to explore car-sharing travel costs advantages from the perspective of consumers and discover the competitive and complementary spaces between car-sharing and other modes. Therefore, taking Beijing as an example, this paper uses GPS trajectory data based on car-sharing orders to design a travel cost framework of car-sharing and taxis. We calculate and compare the travel cost difference between these two modes under different travel characteristics. The results indicate that car-sharing is a more economical way for consumers to travel for short or medium lengths of time, while people are more inclined to take taxis for distances of long duration. Compared with on workdays, at the weekend, the cost advantage of car-sharing is greater for long-distance trips. Moreover, the cost advantage of car-sharing increases gradually with the increase in travel distance. In addition, the travel costs of car-sharing and taxis are also affected by peak and off-peak traffic periods. Compared with off-peak periods, it is more cost-effective for travelers to take taxis during peak traffic periods for various travel distances. From the perspective of the travel cost, it is of great theoretical significance to discuss the substitution (market competition) and complementary relationship (market cooperation) between car-sharing and taxis in a detailed and systematic way. It provides methods and ideas for the comparative cost calculation of car-sharing and other travel modes. This paper also provides enlightenment and guidance for the development of car-sharing. Enterprises should implement differentiated pricing, designing different charging methods for different traffic periods, travel miles, and rental times, and set up additional stations in the surrounding areas of the city. Relevant government departments should also strictly manage the market access of car-sharing, and add or open car-sharing parking lots in centralized areas and for specific periods.

ACS Style

Beibei Hu; Yue Sun; Huijun Sun; Xianlei Dong. A Contrastive Study on Travel Costs of Car-Sharing and Taxis Based on GPS Trajectory Data. International Journal of Environmental Research and Public Health 2020, 17, 9446 .

AMA Style

Beibei Hu, Yue Sun, Huijun Sun, Xianlei Dong. A Contrastive Study on Travel Costs of Car-Sharing and Taxis Based on GPS Trajectory Data. International Journal of Environmental Research and Public Health. 2020; 17 (24):9446.

Chicago/Turabian Style

Beibei Hu; Yue Sun; Huijun Sun; Xianlei Dong. 2020. "A Contrastive Study on Travel Costs of Car-Sharing and Taxis Based on GPS Trajectory Data." International Journal of Environmental Research and Public Health 17, no. 24: 9446.

Article
Published: 08 September 2020 in Networks and Spatial Economics
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This paper investigates the implementation of a dynamic reference point scheme to capture traveler’s mental characteristics, with their day-to-day route choice behavior and heterogeneity. The traveler’s heterogeneity focuses on their different risk attitudes. On each day, travelers choose the routes based on their estimated travel costs, which can be affected by the reference point structure and its update. Most existing studies on the day-to-day traffic assignment models are proposed to capture day-to-day flow fluctuations through a learning model based on traveler’s past experience and information, but did not work on the consideration of gain and loss, which is described by the reference point scheme, comparing with traveler’s previous experience. This study aims to develop a day-to-day dynamic evolution model, in which travelers take on a tendency to refer to their previous travel experience as a reference when coping with different travel scenarios. First, the multi-class dynamic system is proposed to model traveler’s route choice behavior in a transportation network with two traveler classes. Then, the equilibrium state and stability of the evolution model is examined. We further investigate the class-specified update structure of the reference point. Finally, numerical experiments are presented to illustrate the application of our method.

ACS Style

Huijun Sun; Si Zhang; Linghui Han; Xiaomei Zhao; Lu Lou. Day-to-Day Evolution Model Based on Dynamic Reference Point with Heterogeneous Travelers. Networks and Spatial Economics 2020, 20, 935 -961.

AMA Style

Huijun Sun, Si Zhang, Linghui Han, Xiaomei Zhao, Lu Lou. Day-to-Day Evolution Model Based on Dynamic Reference Point with Heterogeneous Travelers. Networks and Spatial Economics. 2020; 20 (4):935-961.

Chicago/Turabian Style

Huijun Sun; Si Zhang; Linghui Han; Xiaomei Zhao; Lu Lou. 2020. "Day-to-Day Evolution Model Based on Dynamic Reference Point with Heterogeneous Travelers." Networks and Spatial Economics 20, no. 4: 935-961.

Journal article
Published: 04 September 2020 in Transportation Research Part A: Policy and Practice
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In recent years, the concept of carsharing is rapidly gaining popularity in China, and the round-trip carsharing has become a common mode. However, few studies have revealed the role of round-trip carsharing in users’ travel. In this study, the round-trip GPS data provided by a carsharing company in Beijing, China is used to analyze the users’ usage patterns based on their trip chains. Through the extraction and analysis of trip information, all trip chains are grouped into three clusters, each of which has a different usage pattern. Then the consumption features and the shared car pick-up and return time of these three patterns are discussed. Further, the Bayes’ rule is used to predict the activity purpose, and the proportion and spatial distribution of different purposes are analyzed. Results reveal that the carsharing program presents multiple usage patterns to meet the different travel needs of users. Price incentives like coupons, discounts, and packages can attract more shared car trips. Users' demand for price incentives increases with longer travel distance and time. Also, users’ usage of vehicles and parking spaces has obvious peak hours. The spatial distribution of user activities has distinctly different hotspots. This paper can be beneficial for operators to set a reasonable pricing plan and provide better services.

ACS Style

Xiaoyan Feng; Huijun Sun; Jianjun Wu; Zhiyuan Liu; Ying Lv. Trip chain based usage patterns analysis of the round-trip carsharing system: A case study in Beijing. Transportation Research Part A: Policy and Practice 2020, 140, 190 -203.

AMA Style

Xiaoyan Feng, Huijun Sun, Jianjun Wu, Zhiyuan Liu, Ying Lv. Trip chain based usage patterns analysis of the round-trip carsharing system: A case study in Beijing. Transportation Research Part A: Policy and Practice. 2020; 140 ():190-203.

Chicago/Turabian Style

Xiaoyan Feng; Huijun Sun; Jianjun Wu; Zhiyuan Liu; Ying Lv. 2020. "Trip chain based usage patterns analysis of the round-trip carsharing system: A case study in Beijing." Transportation Research Part A: Policy and Practice 140, no. : 190-203.

Journal article
Published: 29 June 2020 in International Journal of Environmental Research and Public Health
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The emergence and development of car sharing can not only satisfy people’s diverse travel demands, but also can bring a new solution to facilitate urban low-carbon and green development. With the increasing acceptance of car sharing, the market competition between car sharing and traditional taxis is becoming increasingly fierce. Therefore, we explore the advantages of car sharing to travelers compared with taxis. In this paper, we first use the GPS (Global Positioning System) trajectory data of car sharing orders to construct a comparative advantage model based on travel-cost. Then, we take Beijing as the research area to explore the travel-cost advantages of car sharing in terms of the time and space dimensions compared with taxis, through calculating the travel-cost of car sharing and using simulation to calculate that of taxis. The results of the comparison between car sharing and taxis from the perspective of travel-cost are as follows: (1) Compared with short trips, the travel-cost advantage of car sharing is relatively higher in medium and long trips; for travelers, the taxi has a higher travel-cost advantage when the travel time is either very long or very short. (2) On weekdays, it is more cost-effective to travel by shared cars for travelers before the rush hours in the evening, and the travel-cost advantage of using taxis is greater after the evening peak. (3) Compared with weekdays, it is more cost-effective to travel by shared cars on weekends wherever travelers are living in the main urban areas or in the remote suburbs. It is suggested that relevant departments should understand the travelers’ preference and analyze the influence mechanism of other various factors on the market demand for car sharing as per the focus on the market on the travel-cost advantages of car sharing, so as to promote the healthy and sustainable development of urban shared transportation.

ACS Style

Xianlei Dong; Yongfang Cai; Jiaming Cheng; Beibei Hu; Huijun Sun. Understanding the Competitive Advantages of Car Sharing from the Travel-Cost Perspective. International Journal of Environmental Research and Public Health 2020, 17, 4666 .

AMA Style

Xianlei Dong, Yongfang Cai, Jiaming Cheng, Beibei Hu, Huijun Sun. Understanding the Competitive Advantages of Car Sharing from the Travel-Cost Perspective. International Journal of Environmental Research and Public Health. 2020; 17 (13):4666.

Chicago/Turabian Style

Xianlei Dong; Yongfang Cai; Jiaming Cheng; Beibei Hu; Huijun Sun. 2020. "Understanding the Competitive Advantages of Car Sharing from the Travel-Cost Perspective." International Journal of Environmental Research and Public Health 17, no. 13: 4666.

Journal article
Published: 17 June 2020 in Energy
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Station-skipping and deadheading for subway operation regulations are two effective ways to reduce the effects of train variations, such as large passenger flow and unexpected incidents. These variations, if not properly eliminated through strategies, will lead to a gap in the train and eventually increase passenger waiting time and energy consumption. This paper addresses the last-train station-skipping, transfer-accessible, and energy-efficient scheduling problem for the subway system by optimizing the subway schedule and the last train station-skipping scheme. First, an integrated last train operational model was developed to achieve energy savings and better performance of transfer waiting and in-train travel times by adjusting train acceleration, cruising, coasting, and braking times on each rail segment. Second, a heuristic evaluation-based optimization algorithm was designed to solve a real-life case study of the Beijing Subway to demonstrate the effectiveness of our methods. Two operational strategies (station-skipping and deadheading) for the last trains were designed and compared quantitatively. The results indicate that the station-skipping plan shows an advantage in minimizing the in-train travel time and energy consumption.

ACS Style

Liujiang Kang; Huijun Sun; Jianjun Wu; Ziyou Gao. Last train station-skipping, transfer-accessible and energy-efficient scheduling in subway networks. Energy 2020, 206, 118127 .

AMA Style

Liujiang Kang, Huijun Sun, Jianjun Wu, Ziyou Gao. Last train station-skipping, transfer-accessible and energy-efficient scheduling in subway networks. Energy. 2020; 206 ():118127.

Chicago/Turabian Style

Liujiang Kang; Huijun Sun; Jianjun Wu; Ziyou Gao. 2020. "Last train station-skipping, transfer-accessible and energy-efficient scheduling in subway networks." Energy 206, no. : 118127.

Journal article
Published: 20 January 2020 in Applied Mathematical Modelling
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Urban rail traffic congestion is becoming increasingly serious due to the large traffic demands in modern cities. In order to ensure the safety and quality of station services in peak hours, it's necessary to adopt some reasonable and effective passenger flow control strategies. In this study, through considering the time-dependent passenger demands, a passenger flow control model based on the network-level system is explicitly developed. The passenger successive motion process is discretized by the modeling method. Systematically considering the coordinated relationship between traffic demands and strict capacity constraints (including station passing capacity, platform load capacity and train transport capacity), we establish a mixed integer linear programming model to minimize the total passenger waiting time (including passengers outside stations and on the platforms). The optimization software Cplex is adopted to solve the developed model, and a real network of Beijing urban railway is calibrated to verify the effectiveness of the suggested model. As a result, the proposed flow control strategies can provide detailed information about control stations, control durations and control intensities, and can effectively reduce the total waiting time and relieve the number of stranded passengers in the urban rail transit network.

ACS Style

Fuya Yuan; Huijun Sun; Liujiang Kang; Jianjun Wu. Passenger flow control strategies for urban rail transit networks. Applied Mathematical Modelling 2020, 82, 168 -188.

AMA Style

Fuya Yuan, Huijun Sun, Liujiang Kang, Jianjun Wu. Passenger flow control strategies for urban rail transit networks. Applied Mathematical Modelling. 2020; 82 ():168-188.

Chicago/Turabian Style

Fuya Yuan; Huijun Sun; Liujiang Kang; Jianjun Wu. 2020. "Passenger flow control strategies for urban rail transit networks." Applied Mathematical Modelling 82, no. : 168-188.

Journal article
Published: 16 January 2020 in Transport Policy
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We analytically examine the decision of high-speed rail (HSR) operator from the social welfare-maximizing perspective under quantity competition, price competition, quantity competition with train speed determination (quantity-speed competition) as well as quantity and frequency competition between air transport (AT) and HSR, respectively. A basic Assumption underlying each competition model is that the AT aims at maximizing its profit, while the objective function of HSR which can be manipulated by the government is given by a weighted sum of HSR profit and social welfare. It is demonstrated that under quantity, price and quantity-speed competition between AT and HSR, the socially optimal objective weight of HSR operator depend mainly on both the potential market size of the AT-HSR transportation system and the attractiveness of HSR. However, under quantity-frequency competition, the socially optimal decision weight of HSR operator has nothing to do with the market size and the attractiveness of HSR. These results offer some important insights for government which has the power to influence the decision of HSR authority and aims to maximize the social welfare.

ACS Style

Wei Wang; Huijun Sun; Jianjun Wu. How does the decision of high-speed rail operator affect social welfare? Considering competition between high-speed rail and air transport. Transport Policy 2020, 88, 1 -15.

AMA Style

Wei Wang, Huijun Sun, Jianjun Wu. How does the decision of high-speed rail operator affect social welfare? Considering competition between high-speed rail and air transport. Transport Policy. 2020; 88 ():1-15.

Chicago/Turabian Style

Wei Wang; Huijun Sun; Jianjun Wu. 2020. "How does the decision of high-speed rail operator affect social welfare? Considering competition between high-speed rail and air transport." Transport Policy 88, no. : 1-15.

Journal article
Published: 05 July 2019 in Sustainability
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At present, most urban rail transit systems adopt an operation mode with a single long routing. The departure frequency is determined by the maximum section passenger flow. However, when the passenger flow varies greatly within different sections, this mode will lead to a low load factor in some sections, resulting in a waste of capacity. In view of this situation, this paper develops a nonlinear integer programming model to determine an optimal timetable with a balanced scheduling mode, where the wasted capacity at a constant departure frequency can be reduced with a slight increase in passenger waiting time. Then, we simplify the original model into a single-objective integer optimization model through normalization. A genetic algorithm is designed to find the optimal solution. Finally, a numerical example is presented based on real-world passenger and operation data from Beijing Metro Line 4. The results show that the double-routing optimization model can reduce wasted capacity by 9.5%, with a 4.5% increase in passenger waiting time, which illustrates the effectiveness of this optimization model.

ACS Style

Qiuchi Xue; Xin Yang; Jianjun Wu; Huijun Sun; Haodong Yin; Yunchao Qu. Urban Rail Timetable Optimization to Improve Operational Efficiency with Flexible Routing Plans: A Nonlinear Integer Programming Model. Sustainability 2019, 11, 3701 .

AMA Style

Qiuchi Xue, Xin Yang, Jianjun Wu, Huijun Sun, Haodong Yin, Yunchao Qu. Urban Rail Timetable Optimization to Improve Operational Efficiency with Flexible Routing Plans: A Nonlinear Integer Programming Model. Sustainability. 2019; 11 (13):3701.

Chicago/Turabian Style

Qiuchi Xue; Xin Yang; Jianjun Wu; Huijun Sun; Haodong Yin; Yunchao Qu. 2019. "Urban Rail Timetable Optimization to Improve Operational Efficiency with Flexible Routing Plans: A Nonlinear Integer Programming Model." Sustainability 11, no. 13: 3701.

Articles
Published: 26 May 2019 in Transportmetrica A: Transport Science
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In this paper, we present a series of machine learning approaches for better understanding people’s travel mode choice. The widely used Logit model is dependent on the assumption that the utility items are independent, violating of this assumption caused inconsistent parameter estimations and biased predictions. To improve the prediction accuracy of mode choice, this paper employs the data fusion model based on stacking strategy and proposes a hybrid model of the unsupervised Denoising Autoencoder (DAE) combining with the supervised Random Forest (RF). A variety of features that may impact mode choice behavior are ranked and selected by using the feature selection algorithms. The proposed model, which is particularly useful and powerful in the choice behavior analysis and outperforms other widely used classifiers, is verified by travel diary data from Germany and Switzerland. The results can be used for better understanding and effectively modeling of human travel mode choice behavior.

ACS Style

Ximing Chang; Jianjun Wu; Hao Liu; Xiaoyong Yan; Huijun Sun; Yunchao Qu. Travel mode choice: a data fusion model using machine learning methods and evidence from travel diary survey data. Transportmetrica A: Transport Science 2019, 15, 1587 -1612.

AMA Style

Ximing Chang, Jianjun Wu, Hao Liu, Xiaoyong Yan, Huijun Sun, Yunchao Qu. Travel mode choice: a data fusion model using machine learning methods and evidence from travel diary survey data. Transportmetrica A: Transport Science. 2019; 15 (2):1587-1612.

Chicago/Turabian Style

Ximing Chang; Jianjun Wu; Hao Liu; Xiaoyong Yan; Huijun Sun; Yunchao Qu. 2019. "Travel mode choice: a data fusion model using machine learning methods and evidence from travel diary survey data." Transportmetrica A: Transport Science 15, no. 2: 1587-1612.

Research article
Published: 01 April 2019 in Journal of Advanced Transportation
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This paper studies the travel behavior of travelers who drive from the living area through the highway to the work area during the morning rush hours. The bottleneck model based on personal perception travel behavior has been investigated. Based on their willingness to arrive early, travelers can be divided into two categories: active travelers and negative travelers. Three possible situations have been considered based on travelers’ personal perception. Travelers’ travel choice behaviors are analyzed in detail and equilibrium is achieved with these three situations. The numerical examples show that the departure time choice of the travelers is related not only to the proportion of each type of travelers, but also to personal perceived size.

ACS Style

Xiao Guo; Huijun Sun. Modeling the Morning Commute Problem in a Bottleneck Model Based on Personal Perception. Journal of Advanced Transportation 2019, 2019, 1 -12.

AMA Style

Xiao Guo, Huijun Sun. Modeling the Morning Commute Problem in a Bottleneck Model Based on Personal Perception. Journal of Advanced Transportation. 2019; 2019 ():1-12.

Chicago/Turabian Style

Xiao Guo; Huijun Sun. 2019. "Modeling the Morning Commute Problem in a Bottleneck Model Based on Personal Perception." Journal of Advanced Transportation 2019, no. : 1-12.