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    Decision-making Forum
    Green Traffic and Urban Sustainable Development
    PENG Hong-qin,ZHANG Guo-wu
    2018, 18(2): 1-6. 
    Abstract ( )   PDF (3779KB) ( )  

    Urban development is on the transformation stage that from "quantity" to "quality". The 50th conference of “Traffic and Transportation 7 + 1” sets its theme as “Green Traffic and Urban Sustainable Development”. Ten principles are summarized that about promoting green development of city and traffic. The objective, strategy and details listed of “Guidelines for Street Design of Kunming” is analyzed, which can provide guidance for building the public living space that safety, order, convenient, cultural characteristics and ecology green. It puts forward five steps to improve the quality of living in low cost. The design goal, norm mode, key factors and implementation effect of bus subsidy system are discussed. Big data and Internet can be used for TOD index analysis, all-people participation, sharing and improvement of traffic environment.

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    Intention Formation Mechanism in the Intercity Travel Mode Choice Influenced by the Habit
    LI Jun, JIA Shun-ping, QIAN Jian-pei, WANG Yu-qiong, ZHANG Si-jia
    2018, 18(2): 7-12. 
    Abstract ( )   PDF (3336KB) ( )  

    Passengers have a tendency that trust their experience and wouldn’t have a try in travel decision making process. This paper studies the intention formation mechanisms and effects of the habit in the intercity mode choice among railway, bus and high-speed railway. Based on the definition and psychological test, the habit is introduced to improve the theory of planned behavior as a latent variable. Three structural equation models are built to examine the relationships between the habit and the intention. Results shows that the explained variance of the intention contributed by the latent variables are up to 71.7%, 54.9% and 62.3% in the choice of railway, bus and high-speed railway separately. The total effects on the intention explained by the habit are 0.538, 0.851 and 0.538, while the indirect effects are 0.538, 0.513 and 0.258 respectively. It is indicated that there is an obvious habitual tendency in the choice of intercity travel mode. The habit has direct and indirect effects on the intention, and the latter is stronger. The choice of bus is significantly influenced by the habit.

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    Forum about Comprehensive Transportation System
    Forecast Study of Regional Transportation Carbon Emissions Based on SVR
    CHEN Liang, WANG Jin-hong, HE Tao, ZHOU Zhi-hua, LI Qiao-ru, YANG Wen-wei
    2018, 18(2): 13-19. 
    Abstract ( )   PDF (3788KB) ( )  

    Based on the STIRPAT model, seven influence factors are selected to build a forecasting model based on the SVR (support vector regression), including passenger-kilometers, freight ton-kilometers, per capita GDP, vehicle population, carbon intensity, energy structure and urbanization rate. Data of Beijing province from 1900 to 2016 is taken as an example for the case study. The results show that the optimal parameters of C and γ are gotten with the training samples’cross-validation mean square error of 0.008 040. With the correlation coefficients of 0.984 2 and 0.995 0, the SVR model had a good ability of learning and promotion. Although under a slowing growth trend of carbon emissions, the total transportation carbon emissions would continue to show an upward trend and the society is still faced with great pressure on the reduction of greenhouse gas emissions.

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    Estimating CO2 Emissions from Inland Railway Transport Chain of International Containers
    TAO Xue-zong, WU Qin, YIN Chuan-zhong
    2018, 18(2): 20-26. 
    Abstract ( )   PDF (3846KB) ( )  

    The CO2 emissions from railway transport chain would be underestimated if the emissions from the activity of loading and unloading, pre-/post- haulage of containers, distribution of empty containers, and the life cycle of fuel are neglected. Focusing on the inland transport of international containers, we investigate the CO2 emissions from railway transport chain (RTC, from loading empty container on truck to full container unloaded at seaport terminal) based on the perspective of transport chain and the idea of fuel life cycle. According to the ASIF (Activity-Structure-Fuel Intensity-Emission Factor) equation, a mathematical model is proposed to estimate the CO2 emissions from RTC of the inland leg of international containers. Then the exported containers from Yiwu City by railway via Ningbo Port Area to overseas are taken for case study, and the CO2 emissions from RTC under different scenarios are estimated. The results show that the CO2 emissions from RTC between Yiwu and Ningbo are underestimated at most by 99.215%, and building new railways can reduce CO2 emissions by up to 22.821%. The findings can provide technical support for evaluating the effect of multimodal transport on reducing of CO2 emissions.

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    Efficiency of Highway Cargo Transportation and Its Effect Factors Based on Perspective of Wanjiang Demonstration Zone
    LIU Hong-wei, WU Jie, LIANG Wen
    2018, 18(2): 27-32. 
    Abstract ( )   PDF (3440KB) ( )  

    Using estimation method of exogenous factors and stochastic frontier production function model, an empirical study on highway freight efficiency in Anhui province is carried out. Results show that highway freight transport technology is still in the low efficiency during the investigation in Anhui province, the extensively highway freight industry development and wasting of resources. The level of economic development, finance and the degree of opening promote technical efficiency, but there are regional differences in this effect. Industrial structure and level highway of blocking technology efficiency, the increase of transport demand and the level of highway investment don’t mean the promoting of the efficiency of transportation. Finally, based on the above findings and combined with practical, suggestions on optimizing highway freight efficiency in Anhui province are proposed.

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    Market Share Forecasting Method of International Routes in Alliance Environment
    ZHAO Xiao-song, ZHU Jin-fu, GE Wei
    2018, 18(2): 33-39. 
    Abstract ( )   PDF (3679KB) ( )  

    Unlike the forecast of general routes’ market share, the routes’ attributes are complex and difficult to predict the market share, for international routes often need cooperation of two or more carriers, and the corresponding products are unified or diversified. It is necessary to explore a scientific and reasonable method of forecasting. Based on the QSI model, this paper proposes an improved QSI index system by selecting the attributes of the transportation products among the large data of international air transport. The proposed model in this paper is also used to predict the market share of China-USA. The results show that the improved QSI model is more suitable for predicting the market share of international routes than the classical QSI model.

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    Intelligent Transportation System and Information Technology
    A General Framework for Intelligent Railway Passenger Station
    ZHANG Chun-jia, SHI Tian-yun, LV Xiao-jun, BAI Wei, LIANG Bo, HU Hao
    2018, 18(2): 40-44. 
    Abstract ( )   PDF (3038KB) ( )  

    This paper focuses on the development of the Intelligent Railway Passenger Station (IRPS), and designes a general framework for IRPS. Firstly, the basic ideas of IRPS, which are based on the current situation and requirements analysis of the railway passenger station, is introduced from two different point of views, and the definition and features of IRPS are proposed. Secondly, a general framework for IRPS is designed to deal with the actual problems. Thirdly, the primary service and smarter functions are proposed from the perceptive of the technology combining with the service. At last, the test prototype is build in Taiyuan Station, the authenticity and feasibility of the proposed framework and the intelligence function are verified.

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    Taxi on Service Trip Characteristics Based on Multi-source Data Fusion: A Case of Yueyang
    TANG Yan-li, JIANG Chao, ZHENG Bo-hong, LI Qian-ming
    2018, 18(2): 45-51. 
    Abstract ( )   PDF (3850KB) ( )  

    In order to explore the characteristics of taxi on service, those are fused that resident trip survey data, urban land use data and weather data, basis on the large data of taxi GPS trajectory. A passenger taxi travel volume regression model is constructed. It is concluded that there is a strong correlation between the passenger travel volume and the number of posts, weather conditions, time period, area of the district. Regression model and RBF neural network is constructed based on the above four factors on the increase in the district of the resident population and whether weekdays. Through 10 fold cross validation indicate that the fitting effect of RBF neural network model is better than multivariate linear regression model.

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    A Simulation Model for Traffic Mode Choice under the Provision of Real-time Parking Lot’s Information
    LIANG Jing-jing, ZHANG Xiao-ning
    2018, 18(2): 52-59. 
    Abstract ( )   PDF (3927KB) ( )  

    Various parking Apps have been introduced into our daily lives, which make real-time parking lot’s information become easier to be accessed. Providing real- time parking lot’s information also is a new way of dealing with parking problems. However, there has little theoretical research focusing on the mechanism of their impacts on the traffic system, as well as the quantitative analysis on them. In this paper, we take two kinds of realtime parking lot’s information as the subjects to study their impacts on the traffic system, which include real-time remained parking spaces and parking guidance information. Based on theories of point- queue model, learning behavior and Logit-based discrete traffic choice model, a simulation model for traffic mode choice is developed in the case of providing two kinds of real-time parking lot’s information. After that, three scenarios are designed and tested by simulation experiments. Then, the mechanism of their impacts is presented by analyzing simulation results. Finally, sensitivity analyses on serval parameters are carried out with the aim of finding effective ways to improve the efficiency of the traffic system.

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    Car-following Modeling for CACC Vehicles and Mixed Traffic Flow Analysis
    QIN Yan-yan, WANG Hao, RAN Bin
    2018, 18(2): 60-65. 
    Abstract ( )   PDF (3853KB) ( )  

    A Car-following model of cooperative adaptive cruise control (CACC) vehicles is built. At the same time, capacity, rear- end collision safety, and traffic emissions of the mixed traffic flow are also analyzed under different CACC proportions. By considering the traffic flow characteristics that desired headways of vehicles change dynamically with respect to speeds, the non- linear dynamic headway policy based CACC model is presented. Then, the fundamental diagram model of the mixed traffic flow is derived under different CACC proportions, in order to analyze traffic flow operation mechanism which improves capacity. Numerical simulations are designed near bottleneck of the freeway with an on- ramp, based on which rear- end collision risk, fuel consumption, CO, HC, and NOx are evaluated. Research results show that the presented CACC model can have high traffic flow density to improve capacity obviously for the case in which speeds are basically not changed. Moreover, CACC benefits the decrease of rear-end collision risks and traffic emissions.

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    Analysis of Microscopic Driving Behavior and Modeling of Decision-making Effected by Green Signal Countdown
    JIANG Ze-hao, YANG Xiao-guang, WANG Tao
    2018, 18(2): 66-72. 
    Abstract ( )   PDF (4349KB) ( )  

    Driving behavior during the signal switching interval is crucial to the safety of urban traffic, this paper investes the microscopic driving behavior and“go/stop”decision which are affected by the green signal countdown (GSC). Firstly, a single- blind experiment is conducted using the eight- degree- of- freedom driving simulator, and the approach velocity, perception-reaction time, and deceleration of vehicles is obtained. Secondly, the microscopic driving behavior from entering the intersection to the stop line is described in detail. Thirdly, a random- effect Logistic model is built to describe the“go/stop”decision, and the explanatory variables in this model included traffic parameters and drivers’ individual characteristics. The results show that, when entering the intersection, the vehicle will first slow down , then speed up, and then slow down again, moreover, the acceleration usually appears at a distance of 30~40m from the stop line, this shows that GSC and the early stage yellow light has an obvious urging effect on drivers. Secondly, vehicle’s velocity, distance from the stop line, driver’s age and sex has a significant influence on the "pass/stop" decision. The random- effect Logistic model can express the factors not in the model and the heterogeneity of intersections and drivers better.

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    An Arterial Signal Coordination Optimization Model for Trams Considering Timetable Constraints
    ZHOU Yang-fan, WANG Ying, WEI Wei, HONG Zi-xuan, GUO Xiao-jun
    2018, 18(2): 73-79. 
    Abstract ( )   PDF (3531KB) ( )  

    For considering the trams travelling as timetable and keeping signal priority, the timetable constraints including departure interval, stopping time, running time of section, and arterial travel time are supplemented in the model BAM-TRAMBAND. Two arterial signal coordination optimization models for trams are developed with hard constraints and soft constraints which named HT-TRAM model and ST-TRAM model separately. The case study and simulation results show that the modified models both got the arterial green- waves with timetable constrains for trams in two directions. Moreover, the average green-wave bandwidths with hard and soft constraints are both narrow less than 1s compared with BAM-TRAMBAND model.

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    An Area-wide Traffic Signal Coordination Method Based on the Deep First Search of Intersection’s Importance
    LU Ting, BEI Xiao-xu, LIU Gui-yun
    2018, 18(2): 80-86. 
    Abstract ( )   PDF (4092KB) ( )  

    The continuous expansion of urban road network challenges the urban traffic control system seriously. This paper analyzes the traffic correlation between the intersections and the traffic flow parameters that represent the correlation, so as to clarify the topology of the road network. The intersection importance estimation model is built based on the road network topology. Then the area-wide traffic signal coordination method is designed by the deep first search of priority order. This method establishes a balanced network traffic flow signal coordination control method from a global perspective. At last, the proposed method is compared with the signal control scheme optimized by Synchro 7. The micro-simulation program SUMO is used to evaluate the control effectiveness. The simulation result shows that the proposed method can improve signal control performance effectively.

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    Systems Engineering Theory and Methods
    Encroaching Time Interval Distribution Models of Permitted Left-turning Vehicles with Non-strict Priority
    QU Zhao-wei, BAI Qiao-wen, CHEN Yong-heng, XIONG Shuai, DENG Xiao-lei
    2018, 18(2): 87-93. 
    Abstract ( )   PDF (4497KB) ( )  

    A new concept, encroaching time interval, is proposed to describe the micro-characteristic of the permitted left-turning flow under non-strict priority. According to different locations of crossing-through vehicles when left-turns are crossing through, there are four traffic statuses. Then seven distribution models are used to analyze the encroaching time interval with a large number of measured data. Parameters in these models are solved by the maximum likelihood estimation method. And the goodness of fit to these models is given by KolmogorovSmirnov test. The Log-Logistic model is found to be the best choice in different kinds of traffic status. And its parameter values are heavily correlated to different traffic status. At last, a verification test is conducted at other two intersections. The result shows the applicability of the Log-Logistic model in describing the encroaching time interval distribution.

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    Evaluation of Urban Road Importance Based on the Weight Determination Method of Maximization of the Information Volume
    WANG Qing-guo, ZHANG Kun-lun, HU Yi-xi
    2018, 18(2): 94-99. 
    Abstract ( )   PDF (4109KB) ( )  

    Aiming at the determination of the weight of each index in the comprehensive evaluation of the importance of urban roads, based on the standard deviation method, the weight calculation model by maximization of the information volume is established in this paper, which takes the correlation between the evaluation indexes into account. Then, experiments are made based on Wuhan road network data, road stroke as the basic structural element, and the dual topology as the geometrical and topological expression. The results show that the evaluation result of road importance based on the maximization of information volume is in good agreement with the general structure of the road network, and the one-sided and conflicting results based on single index are well avoided. Moreover, the weight determined by the maximization of the information volume can change with the change of the network structure, so it has good adaptability.

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    Public Transport Commuter Identification Based on Individual Travel Graph
    LIANG Quan, WENG Jian-cheng, LIN Peng-fei, ZHOU Wei, RONG Jian
    2018, 18(2): 100-107. 
    Abstract ( )   PDF (3835KB) ( )  

    To obtain elaborate travel characteristics and better meet travel demands for different public transport passengers, it is necessary to find ways identifying public transport commuter accurately. Based on public transport smart card transaction and network data, travel chain is obtained by data processing and matching. Taking travel behavior data of April, 2017 in Beijing, China, individual travel graph is constructed by adopting multi- layer planning theory. Seven feature indexes are extracted from individual travel graph and set as input for passenger classification model. Revealed Preference survey is conducted to collect travel behavior category attributes, which is the output of classification model. A back propagation neuron networks based public transport passenger classification model is constructed. Validation results indicate that the average classification accuracy and Kappa coefficient are 94.5% and 0.879, respectively. The study results contribute to identify public transport passengers of different types accurately and further support to optimize public transport operating and improve service level precisely.

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    Macroscopic Fundamental Diagram Model of Urban Network Based on Multi-source Data Fusion
    JIN Sheng, SHEN Li-xiao, HE Zheng-bing
    2018, 18(2): 108-115. 
    Abstract ( )   PDF (4379KB) ( )  

    The macroscopic fundamental diagram (MFD) is the relationship between average flow and average density of networks and plays an important role in network service level assessment, regional control and macro traffic modeling. In this paper, an MFD method is proposed to fuse the data of the remote traffic microwave sensor and the license plate recognition data by using the networked weighted flow and the weighted density as the MFD description indexes. In order to evaluate the effectiveness of MFD under different data sources, the difference of MFD is described by traffic state ratio. Taking the data of Qingdao City as an example, the MFD’s law of single data source and fusion data are analyzed. The results show that the fusion model can accurately describe the network MFD when there are different types of detectors in the network.

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    Constrained Reliable Shortest Path Problem in Stochastic Traffic Network
    PAN Yi-yong, CHEN Lu, SUN Lu
    2018, 18(2): 116-121. 
    Abstract ( )   PDF (3333KB) ( )  

    In order to simulate the behavior of route choice considering risk with resource constraints in traffic network, the mathematical model of constrained reliable shortest path problem in stochastic traffic network is established and its dual problem is discussed. Gradient descent algorithm is used to solve the dual problem, and obtain the upper and lower bounds of the optimal value of the original problem. The approximate solution of the original problem is obtained by iterative approximation. Numerical test is developed on the Sioux Falls network and the numerical results are analyzed. Numerical results show that the reliable shortest paths obtaining under resource unconstraint and constraint are different, and the reliable shortest path obtaining under different resource constraint is also different in stochastic traffic network; the resource constraint has a great influence to the choice of reliable shortest path.

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    Impacts of Built Environment on Commuting Behavior Based on a Multilevel Modeling Approach
    YIN Chao-ying, SHAO Chun-fu, WANG Pin-xi, MI Xue-yu
    2018, 18(2): 122-127. 
    Abstract ( )   PDF (3786KB) ( )  

    Considering the hierarchical characteristics of social-demographic factors at individual level and built environment factors at traffic analysis zone (TAZ) level, a multilevel approach is proposed to investigate the influences of built environment on commuting time and distance. The impacts of social- demographic factors at individual level and built environment factors at TAZ level on commuting time and distance are analyzed respectively. And the model parameters are estimated based on Changchun household travel survey data. The study infers that the multilevel modeling approach yields better fitting results than the traditional regression model. Additionally, after controlling for commuters’ social-demographics characteristics, the model results show that land use mix, intersection density and transit station density have significantly negative influences on commuting time and distance. And the distance to Central Business District (CBD) is positively associated with commuting distance merely. The research results can provide theory basis for optimizing the commuting structure by means of urban planning.

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    Identification of Urban Road Network’s Critical Links Set under Emergency Environment
    LI Yan-jin, LUO Xia
    2018, 18(2): 128-135. 
    Abstract ( )   PDF (4033KB) ( )  

    In order to determine critical links of urban road network better under emergency environment, this paper combines with network’s vulnerability analysis to structure a critical links’ identification model, which covers single and multiple failure links. Firstly, getting random attack on network and using network efficiency and maximal connected subgraphs to find potential critical links; then, introducing 0-1 variables to establish a nonlinear optimization model with road’s capacity; on the basis, handled objective function and constraints by piecewise linearization and translating the model into a mixed 0-1 programming problem; finally, using branch and bound method to solve model and an example is given to verify it. The results shows that: the critical links set is not a simple integration with single critical links, whose constituent elements don’t have adjacency relationship each other on geometric topological level. But with the number of failure links increasing, there is a significant negative correlation that can be described by reverse curve between the robustness of network and its total impedance variation, which owns well-tried effect.

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    The Effects of Mobile Phone on Pedestrian Crossing Behavior and Safety at Uncontrolled Mid-block Crosswalks
    ZHANG Cun-bao, CHEN Feng, WEI Yuan-yuan, ZHANG Hua-long
    2018, 18(2): 136-141. 
    Abstract ( )   PDF (3408KB) ( )  

    Using mobile phone may have effect on pedestrian crossing behaviors and traffic safety. Based on the data, which collected from six uncontrolled mid- block crosswalks in Wuhan city of China by field survey, the paper establishes the pedestrian- vehicle conflict analysis model based on Order Probit regression analysis. The results show that: 11.76% of pedestrian used the mobile phone when crossing streets. Among them, staring at the mobile phone, making phone calls and listening to music on their mobile phones account for 6.65%, 2.83% and 2.28%, respectively. Moreover, using mobile phone has obvious impacts on their crossing behaviors. When using the mobile phone, pedestrian spent more time getting through the street, and looked around less often, etc. Furthermore, PVCA model indicate that pedestrian who using mobile phone had significantly greater chances to conflict with vehicles than those who do not use it. For example, talking on the mobile phone has the biggest influence on slight conflict, and staring at the mobile phone has the largest impact on serious conflict.

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    Traffic Conflict Identification Model Based on Post Encroachment Time Algorithm in Ramp Merging Area
    MA Yan-li, QI Shou-ming, WU Hao-tian, FAN Lu-yang
    2018, 18(2): 142-148. 
    Abstract ( )   PDF (4558KB) ( )  

    In order to identify the traffic conflicts between the entrance ramp and the main line, the study of vehicle traffic conflict identification in ramp merging area is carried out. We built a traffic conflict identification model based on PET (Post Encroachment Time) algorithm in ramp merging area, considering vehicle movement information and the influence of vehicle size on traffic conflict and gave the method for determining the severity of traffic conflict. The validity of the model is verified by simulation analysis, and the PET threshold range is confirmed by the measured data. The results show that the accuracy rate using PET algorithm in ramp merging area is 91.71%, which can effectively identify the potential conflicts in the ramp zone. The results can provide a safe early warning for confluence vehicle under collaborative environment, reduce accidence of the vehicle collision and raise the level of road traffic safety in the mixed zone.

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    Uncertainty Analysis to Passenger Flow of Bus Stations Based on Multivariate Data Fusion
    LIU Wu-sheng, ZHOU Xiang-dong, TAN Qian
    2018, 18(2): 149-156. 
    Abstract ( )   PDF (3999KB) ( )  

    Using the data of smart card of bus station collected in the long term, a method of the interval uncertainty passenger flow derivation of the bus station is proposed based on the interval uncertainty theory. On condition that the bus smart card data and GPS data as well as bus station information are fused, boarding stations of bus passengers are identified, and then interval uncertainty passenger flow of boarding stations are inferred. By analyzing the behavior of bus swiping card, and considering the individual trip characteristics and the travel distance of passengers to attract the weight of the station, the probabilistic model of alighting passenger flow and its corresponding algorithm are proposed, and the interval value of the passenger flow at the alighting station is obtained according to interval number processing method. An example is given and analyzed by taking smart card data and GPS data of No. 21 bus in Shenzhen City from November 13, 2015 to December 25, 2015.

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    Design of Demand-responsive Service by Mixed-type Vehicles
    ZHENG Han, ZHANG Xing-chen, WANG Zhi-mei
    2018, 18(2): 157-163. 
    Abstract ( )   PDF (4667KB) ( )  

    For solving contradictions between service quality and service efficiency, this paper proposes a method designing demand-responsive service by mixed-type vehicles. Firstly, a k-means-based algorithm is used to cluster requests which scatters in spatiotemporal space, into service units. Then the assigning and routing of vehicles is viewed as a pickup and delivery problem with time windows; a model whose objective are minimizing total running distance and count of vehicles is made by Dantzig-Wolfe decomposition. In order to have an exact and efficient solution for problem, a distributed column generation algorithm based on MapReduce framework is proposed, with an approach avoiding infeasibility of solution caused by linear relaxation. Finally, taking Beijing as the background of a case, the feasibility and accuracy of our study is proved.

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    Simulation Model of Evacuation Process in Metro Station under Dynamic and Uncertain Environment
    HUANG Jia-jun, XU Rui-hua, HONG Ling, HUANG Zhao-hong
    2018, 18(2): 164-170. 
    Abstract ( )   PDF (3766KB) ( )  

    The dynamic and uncertain environment will cause the uncertainty of the initial status of passengers, evacuation behavior, and the global evacuation path. Considering those problems mentioned above, an agent-based model of dynamic evacuation behavior switch is established, which is able to describe passengers’ switch from various evacuation behaviors with the cost of change. On the other hand, according to the spatial cohesion from the normal simulation, the approach for global path finding based on optimized Dijkstra algorithm is proposed. Finally, simulation on emergency evacuation is conducted in the case of a particular metro station. The result validates that the model is feasible and can reflect environmental effects on passengers’evacuation process dynamically. Meanwhile, the simulation precision is further improved, which enables to evaluate emergency plan with accuracy.

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    An Energy-delay Optimization Method for Real-time Train Path Disturbances in Transportation Network
    ZENG Yi, ZHANG Qi, CHEN Feng
    2018, 18(2): 171-176. 
    Abstract ( )   PDF (3585KB) ( )  

    The timing when trains occupy and clear a track could be affected by external factors and result in delay. Processing of train delay is mainly involved with adjusting timetable in macroscopic level, and train path in microscopic level. The paper investigates state of the art of train delay problem, and puts forward an energy-delay optimization method for real-time train path disturbances which alters train path to leave affected blocks, meanwhile tractive energy and delay are decremented. Delay modeling of the method is based on blocking time model. Through the examples prepared with real-time data and section parameters from Guangzhou railway group CTC system, the model is verified to handle tractive energy saving and delay problems. Simulation results shows that the more sub-sections capable for speed reduction, the more probable a large delay would be handled. Processing of large delay need more real-time data, or the problem should be converted and solved with macroscopic timetabling methods.

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    Algorithm of Dynamic Rebalance Time Ranges for Bicycle Sharing System
    LIU Dong-xu, DONG Hong-zhao
    2018, 18(2): 177-182. 
    Abstract ( )   PDF (3675KB) ( )  

    The reasonable rebalance time of the Bicycle Sharing System (BSS) are important factors that influence service quality and rebalance costs of BSS. However, few relevant studies have focused on it. A bicycle self-moving model considering the reference threshold, bicycle turnover rate, quantitative difference between rentals and returns, etc. is established to characterize the state change of BSS stations. Based on the self-moving model, the method to acquire the rebalance time range of BSS service station is proposed. The method includes how to calculate occupancy-capacity ratio threshold for assessing the empty/full status of stations and the algorithm for time ranges of positive/negative redistribution for BSS rebalance. Based on the Hangzhou dockbased BSS historical data in 2016, an experiment is conducted on the No. 3758 station to analyze and compare the effects of rebalance time ranges by dynamic threshold and fixed reference threshold of the station’s occupancycapacity ratio. The results show that the proposed method can obtain the exact rebalance time range and help decrease the rebalance frequency of the station. It can not only reduce the rebalance cost but also improve the service quality.

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    Optimization on the Truck-trailer Routing Problem with Time Window Constraints
    BIAN Zhan, XU Qi, JIN Zhi-hong
    2018, 18(2): 183-193. 
    Abstract ( )   PDF (4027KB) ( )  

    Aiming at truck-trailer routing problem with time windows, two transportation modes, vehicle and truck transportation, and three routes, vehicle, truck and hybrid are considered. Travelling time is taken as objective function, and a two-stage hybrid heuristic algorithm based on two strategies A, B is proposed. Numerical result shows that for the small-scale cases within 100 customers, the results can be obtained in 3 s. The solution time of strategy B is less than strategy A, but the objective function of strategy A is superior to strategy B. When the customer scale increases to 900, strategy A can achieve higher efficiency. So the model and algorithm constructed in this paper is feasible and effective, and have certain reference value for the vehicle assignment and path optimization in actual distribution.

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    Model and Algorithm of the Vehicle Routing Problem with Request Selection
    SUN Liu-cheng, SUN Yan
    2018, 18(2): 194-200. 
    Abstract ( )   PDF (3549KB) ( )  

    Joint distribution is an effective way to make better utilization of logistics resources and reduce the logistics cost. In this context, the paper proposes a new variant of Vehicle Routing Problem called Vehicle Routing Problem with Request Selection, where a carrier can entrust requests to an external carrier or receive requests from other partners. The carrier needs to optimize the routes as well as selecting the requests. For this problem, a mixed integer programming model is established to maximize the benefit of the carrier. A genetic algorithm is designed to solve the NP-Hard problem. And an optimal split algorithm is proposed to obtain the feasible solution construction of the decimal chromosome coding. We further conduct numerical experiments on instances with different sizes with Matlab. The results show that the two-way entrustment can help reduce the vehicle miles traveled and increase the benefit of the carrier, which also provides the theoretical basis for the individual behavior of joint distribution.

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    Satellite Fire Stations Location and Allocation Model under the Hypercube Queuing Equilibrium
    LIU Han, WANG Jian, AN Shi, CUI Na
    2018, 18(2): 201-207. 
    Abstract ( )   PDF (4703KB) ( )  

    In this paper, a hybrid integer programming model for the gradual coverage in satellite fire stations is proposed. The model considers the hypercube queuing equilibrium and correlation mechanism between the main station and the vice station of satellite fire stations in emergency services, and maximize the gradual coverage of the vehicle locating and dispatching for different levels of disasters. The model is coded and solved by the software GMAS and a local search algorithm. A case study of the satellite fire station in the main city of Harbin in Heilongjiang Province is conducted. The result shows that the correlation mechanism of satellite fire stations can benefit more in comparison with the traditional mechanism. Sensitivity analysis of satellite fire station associated costs are illustrated and provide an accurate reference for the Harbin City Fire Planning Department.

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    Inland Container Liner Route Stowage Planning Decision with Uncertain Container Weight
    LI Jun, ZHANG Yu, JI San-you, CHENG Zhao, MA Jie
    2018, 18(2): 208-215. 
    Abstract ( )   PDF (4145KB) ( )  

    The inland container liner shipping has its particularity comparing with the maritime container shipping. For the domestic trade containers, the uncertainty of weight information which is provided by the cargo owners when booking the shipping space has made the route stowage planning decision more complex. Considering the uncertain container weight, the stochastic programming model for inland container liner route stowage planning decision is built with the objective of minimizing the ship stack occupancy number over the full route. The stochastic programming model is translated into the stochastic chance-constrained programming model based on the stochastic programming theory by describing the stochastic constraints with chance constraints. The hybrid neighborhood search algorithm consisting of Monte Carlo stochastic simulation, neural network training, and neighborhood search heuristics is designed for solving the proposed model. Numerical examples show the hybrid neighborhood search algorithm has a good robustness as it can make the stowage plan to absorb the uncertainty effectively.

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    The Study of Fast Boarding Sequence Characteristics Based on Simulated Annealing Algorithm
    QIANG Sheng-jie, JIA Bin, HUANG Qing-xia
    2018, 18(2): 216-223. 
    Abstract ( )   PDF (4145KB) ( )  

    A well-organized passenger boarding process can effectively shorten the boarding time, and finally reduce the operation and management costs of airlines and airport managers. We firstly analyze various factors causing boarding delay, and then build a passenger boarding simulation model based on cellular automata, in which the characteristics of passengers are described in detail. By utilizing the simulated annealing algorithm, combined with the proposed simulation model, the minimum boarding time and the corresponding boarding sequence are explored. Finally, the correlation characteristics of the optimized sequence are analyzed, and the results show that the aisle interference is the main cause of time delay, the seat interference influences the total boarding time only if it evolves into aisle interference; besides, the seat distance between adjacent boarding passengers in the optimal sequence has different numerical distribution with the change of luggage storage time per passenger.

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    Cases Analysis
    Significant Factors on Service Satisfaction of Rural Passenger Transport in China
    GE Xiao-peng, WANG Qing-yun, ZHANG Yi
    2018, 18(2): 224-229. 
    Abstract ( )   PDF (3454KB) ( )  

    To compare the influence degree of different influence factors on the satisfaction degree of rural passenger transport service, a case-comparative study between Changping District, Beijing and Qiannan State, Guizhou Province is conducted. Various characteristics and events, including educational level, ride frequency, trip purpose, waiting time, walking distance and ticket price, are evaluated as influencing factors for service satisfaction of rural passenger transport in China. To identify the significant factors, a multilevel mixed-effect ordered Logistic model for matched data is established. The results show that: the factor plays a different role in region with stage of various social economic development level; The influence of service accessibility on rural passenger service satisfaction is greater than that of service economy; The influence factors of supply side are more influential on rural passenger service satisfaction than those on demand side; Passenger heterogeneity affected rural passenger service satisfaction indirectly. Further, to improve the efficiency on supple side of rural passenger transport service, this paper discusses the targeted policy from the perspectives of network planning, government investment and operation.

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    Driving Mechanism of Traffic Carbon Emissions in Sichuan Province Based on Path Analysis
    ZUO Da-jie, DAI Wen-tao
    2018, 18(2): 230-235. 
    Abstract ( )   PDF (3629KB) ( )  

    To further analyze the internal driving mechanism of carbon emissions in the transportation industry, this paper takes the measurement data of Sichuan Province during 1995 to 2014 as an example. Then ASIF data structural principles and stepwise regression methods are used to identify the valid driving factors. Furthermore, the direct and indirect effect of each factor on carbon emissions' growth is obtained by path analysis. The result shows that economic intensity, transportation intensity, relative structure and energy consumption intensity are the primary factors affecting the carbon emissions there. Economic intensity is the dominant determiner of carbon emissions, and its direct pull on that is remarkable. The effects of transportation intensity and relative structure on carbon emissions are motivated strongly by economic strength, while energy intensity can apply directly to that. It can be confirmed that the transportation and energy consumption intensity improves at a certain extent in Sichuan Province with the promotion of its transportation industry, but it still not enough to offset the growth of carbon emissions which led by the economic strength steadily ascending.

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    An Method of High-resolution of Urban Traffic Emission for Pollution Control: A Case Study in Beijing
    CHENG Ying, CHEN Yan-yan, LIU Ying, WU Ke-han, HE Wei-nan, ZHAO Jin
    2018, 18(2): 236-244. 
    Abstract ( )   PDF (6034KB) ( )  

    Traffic pollution reduction policy has shown the trend of diversification, refinement and differentiation, the limitations of the traditional traffic emission model in evaluation scope and scale have become increasingly prominent. This paper focus on the research of traffic flow simulation model based on real-time monitoring data, analysis of fleet structure based on visual detection method, the correction relationship of velocity emission factor based on local operating model, from which a high resolution analysis method of urban traffic emission is proposed. This method can reach the hour and the road section level. The emission sources can be distinguished to the different traffic modes and the local field. In addition, based on a case study of Beijing, an empirical analysis of the temporal and spatial distribution characteristics of NOx emission from the road traffic is conducted. The result shows that during the peak period, the NOx emission on the road network can take up to 31.2% of the whole day. Besides, highway and expressway account for 37.9% and 38.8% of the total emission respectively. The emission intensity between the 5th and 6th ring road is the highest, which accounts for 38.32% within the 6th ring. The emission of freight vehicles can reach up to 47% of all. Finally, the research points out that the high resolution analysis method of urban traffic emission is of significance to the accurate temporal, spatial and vehicle positioning of urban traffic pollution control, as well as contributes to the fine decision-making.

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