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25 August 2019, Volume 19 Issue 4 Previous Issue    Next Issue
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Decision-making Forum
Forum about Comprehensive Transportation System
Intelligent Transportation System and Information Technology
Systems Engineering Theory and Methods
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Decision-making Forum

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Intelligent Transportation and Intelligent Logistics PENG Hong-qin, ZHANG Guo-wu 2019, 19(4): 1-4.  Abstract ( )   PDF (275KB) ( )   Intelligent transportation and intelligent logistics are the important contents of building a smart city. The innovation and development of technology promotes the upgrading of intelligent transportation. It is the basis of intelligent transportation that solving the large-scale data computing problem. The 55th conference of“Traffic and Transportation 7 + 1 Forum”sets its theme as“Intelligent Transportation and Intelligent Logistics”. It introduces the theory, practice and achievements of safe driving, and discusses the promoting role of new generation of information technology in development and innovation of intelligent transportation. The general framework, development and application of unmanned driving technology are introduced. It is also discussed that large-scale data computing problem and solution in intelligent logistics. Related Articles | Metrics

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Influence of Travel Information Release on the Operation of Taxi Transportation System YUE Hao, GAO Wen-can, HUANG Yi-ran 2019, 19(4): 5-12.  Abstract ( )   PDF (511KB) ( )   The influence of travel information release on the efficiency of taxi transportation system is studied based on simulation. The release degree of travel information is divided into three types mode: the no-release, the full- release and the half- release information. This paper formulates road network construction rules, passenger generation and disappearance rules, taxi and passenger matching rules, taxi driving rules, taxi system evaluation rules. It is simulated that the running process of taxis searching, matching, carrying and delivering passengers. Analyzing the impact of different information disclosure on taxi vacancy rate, passenger waiting time, number of passengers, average driver income. It is found that the half-release mode with only the origin site information can help improve the taxi transportation system operation efficiency and service quality. Compared with the other two modes, because of taxi-drivers only knowing the passengers' origin position, the half-release mode effectively not only improve the efficiency of the taxi driver searching travel passengers, but also avoid the "invisible refuse" problem arised from taxi driver deliberately chosing the passengers who bring higher benefits. In order to ensure the equity of every passengers, it is recommended to adopt the half- release mode with only the origin site information in taxi transportation system. References | Related Articles | Metrics

Forum about Comprehensive Transportation System

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Path Optimization of Green Multimodal Transportation under Mixed Uncertainties LI Jun, YANG Bin, ZHU Xiao-lin 2019, 19(4): 13-19.  Abstract ( )   PDF (370KB) ( )   When the quadruple mixed uncertainties of the transportation time, transit LCL time, customer demand and the transit freight volume are subject to stochastic distribution, the green multimodal transportation path optimization problem is researched. Using stochastic optimization theory, aiming at transportation cost, carbon emission cost and time penalty cost, a green multimodal transport path optimization model under mixed uncertainties is established. By assigning the weights of each sub-objective function, a multimodal transportation path optimization scheme considering different cost factors is obtained. The sensitivity analysis of time, demand and network service capabilities on the results of multimodal transport path planning is discussed. The law that each objective function cost changes with time, and service time when the marginal transportation cost is the smallest are obtained. The marginal transportation cost is reduced when the freight volume forms a scale effect. Transportation path optimization results for different network service scales and minimum network configurations to meet customer uncertain needs are received. References | Related Articles | Metrics

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Scheduling Activity and Travel Patterns in Multi-modal Transit Networks with Customized Bus Services FU Xiao, GU Yu, LIU Zhi-yuan 2019, 19(4): 20-27.  Abstract ( )   PDF (459KB) ( )   In recent years, emerging mobility services are developed rapidly which make people face a wide range of transport modes in multi-modal transit networks. As an innovative mode of public transit, customized bus (CB) services attract increasing attention in many cities of China. In this paper, an activity- based model is proposed for scheduling individuals’daily activity- travel patterns (DATPs) in multi-modal transit networks with the emerging CB services. The change of individuals’activity and travel choice behavior is investigated after CB services are introduced in multi-modal transit networks. A super- network platform is adopted to simultaneously consider individuals’activity and travel choices. To describe the CB subscription process considering capacity constraint, a day- to- day learning and adjustment process is incorporated in the proposed model. A numerical example is conducted to illustrate the proposed model. The results show that the operation of CB significantly impact individuals’DATP choices. References | Related Articles | Metrics

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Capturing Car Ownership Behavior Considering Spatial Autocorrelation in Traffic Analysis Zones WANG Xiao-quan, SHAO Chun-fu, YIN Chao-ying, DONG Chun-jiao 2019, 19(4): 28-32.  Abstract ( )   PDF (276KB) ( )   In order to investigate the influence of built environment factors on household car ownership, a multilevel Bayesian model is employed considering the spatial autocorrelation among traffic analysis zones (TAZs). In the Bayesian model, three types of adjacent matrix are used to specify the spatial autocorrelation term including 0-1 adjacent matrix, common boundary adjacent matrix and centroid distance adjacent matrix. The models are calibrated based on the Changchun household travel survey data. The result shows that the spatial autocorrelation exists significantly. Among the calibrated models, the multilevel Bayesian model with common boundary adjacent matrix fit the data best. Additionally, residential density, land use mix, intersection density and transit station density all have significantly negative influence on household car ownership. It suggests that it can be effective for reducing car ownership by optimizing urban built environment. References | Related Articles | Metrics

Intelligent Transportation System and Information Technology

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Influence of Different Vehicle Operating Conditions on Driving Safety of CACC Platoon QIN Pin-pin, PEI Shi-kang, HOU Xiao-lei, WU Feng-min,WAN Qian 2019, 19(4): 33-42.  Abstract ( )   PDF (714KB) ( )   Based on the lateral controller and longitudinal controller model, including the corrected preview driver model, acceleration control model, throttle control model and brake control model, the Matlab/Simulink and CarSim vehicle co-simulation platform is established and its feasibility is analyzed and verified. The platform is used to simulate the cooperative adaptive cruise control (CACC) fleet vehicle driving safety under four scenarios: emergency braking, communication delay, start-up, deceleration and inserting a lane change vehicle in front of the team. The simulation found that the platoon can achieve better emergency collision avoidance during emergency braking; in the case of communication delay, the team can still ensure driving safety; the starting and slowing conditions of the platoon are relatively stable, but the acceleration is not stable, which is not conducive to the platoon and the comfort of the rear vehicle; when inserts vehicles of different speeds in front of the team, the team can respond in time and eventually restore the safe driving distance. References | Related Articles | Metrics

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An Intra-street Source Routing Mechanism Based on Genetic Algorithm in VANETs CAI Zhen, LIANG Man-gui 2019, 19(4): 43-49.  Abstract ( )   PDF (410KB) ( )   In most of existing intersection-based routing protocols in urban vehicular ad hoc networks (VANETs), geographical greedy forwarding strategy is still adopted for packets delivery in intra- streets. The heavy network load on some certain nodes caused by large data traffic would likely incur large end-to-end delay and even packets dropping. In this paper, we propose an intra-street source routing mechanism based on genetic algorithm (ISSR). By recording the driving data of each individual vehicle instead of the mean value of the traffic flow, we estimate the connectivity in the street. And we are the first to calculate the optimal nodes sequence based on genetic algorithm taking account of the factors of connectivity, node load and hops. The simulation results show that ISSR outperforms the traditional protocol GPSR in terms of packet delivery ratio, average end-to-end delay. In especial, under the condition of 250 veh· lane- 1 · h- 1 , it has a performance improvement about 13% in the packet delivery ratio. This research can provide reliable support for the information communication in ITS. References | Related Articles | Metrics

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Conflict Handling Strategies of Lane-changing Decision Model of Multi-lane Cellular Automata DENG Jian-hua, FENG Huan-huan, GE Ting 2019, 19(4): 50-54.  Abstract ( )   PDF (300KB) ( )   Lane-changing model is one of the core sub-models of multi-lane cellular automata traffic flow model. Based on the analysis of the process of dealing with vehicle conflict when drivers change lanes in reality, according to the different characteristics of lane- changing driving behavior, the conflict strategies adopted by drivers are divided into conservative, astute and radical ones. By further optimizing the vehicle status update algorithm, a multi-lane change model with multi-strategy and random order of vehicle status updating is proposed. Under different occupancy conditions, lane- changing motives, successful lane- changing times are generated by running the proposed multi- lane change model when drivers adopt conservative, astute or radical strategies. Through analysis, it is found that different lane- changing conflict handling strategies will lead to significant difference in lane- changing motivation probability and lane- changing success probability in specific space occupancy rates. References | Related Articles | Metrics

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Identification Model for Horn's Intention of Intelligent Connected Vehicle under the Mixed Traffic Stream LIANG Jun, XU Peng, CAI Ying-feng, CHEN Long, HUA Guo-dong 2019, 19(4): 55-62.  Abstract ( )   PDF (535KB) ( )   With the aim that intelligent connected vehicles is able to identify horn's intention to follow the driving intention of the conventional vehicles better under the mixed traffic stream, perception-location-recognition model is proposed of ICV to the horn of conventional vehicles. Deep convolution recurrent neural network is used to percept the horn of the horning vehicles. time difference of arrival is exploited for the location of the HV. Support vector machine based on motion time window is applied to recognize the HI of the HV. The experimental results indicate that such a model enables the average accuracy rate of perception that the ICV conducts on the horn of the HV in the mixed traffic stream to amount to 90.4%, the error of positioning angle is within 5 degrees and the average recognition rate of HI is 82.5%, which provides the basis for the intelligent driving decision of the ICV in the mixed traffic stream. References | Related Articles | Metrics

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Signal Control Optimization for Short Length Intersections Based on Critical Distance WU Xian-yu, LI Lu-bing 2019, 19(4): 63-71.  Abstract ( )   PDF (498KB) ( )   This paper regards the short length intersection as the research object. It is actively explored to find the methods of intersection signal control and the plans of traffic management using NEMA standard, PARAMICS simulation software and critical distance. Firstly, the short length intersection is classified into two typical types, including merging signals and coordinated signals, based on traffic characteristics analysis. Secondly, a selection model is established for the mode of signal control. The mode of control is judged by comparing the distance between two intersections and the critical value. Based on NEMA TS- 2 Dual- Ring- Barrier phase structure, the corresponding signal phase setting strategy and signal timing method are put forward for the two kinds of different control modes respectively. Finally, the traffic simulation software of PARAMICS is used to analyze the current traffic scheme and the optimized scheme of the two practical investigated close quarter intersections. Through the simulation evaluation index, the optimized results are proved. Meanwhile, it is actively proved that the methods and theories of short length intersection in the research are effective and feasible. References | Related Articles | Metrics

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Simulation and Analysis of Intersection Signal Control Based on Vehicle Emission LI Su-lan, ZHANG Xie-dong, SHI Jun-qing,WANG Xiao-jia 2019, 19(4): 72-78.  Abstract ( )   PDF (443KB) ( )   The relationship between signal timing and vehicle emission at intersections is studied by combining cellular automata model and MOVES model. Cellular automaton model divides intersections and road sections into 3.5 m× 3.5 m cells, each vehicle occupies two cells. In the intersection, turning vehicles slow down, and through vehicles move without restiction, which improves the authenticity of traffic simulation and the accuracy of vehicle emission estimation. The simulation results show that the optimal signal cycle increases with the increase of vehicle arrival rate, which maximizes the efficiency of intersections. The travel time increases with the increase of left-turn ratio, and there is a limit value for each vehich arrival rate. When the left-turn ratio is lower than the limit value, the travel time does not change much. When the left-turn ratio is higher than the limit value, the travel time increases rapidly. From the perspective of capacity, travel time and exhaust emissions, intersections have different characteristics, the optimum signal period is quite different. References | Related Articles | Metrics

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Lane-level Traffic Speed Prediction for Expressways Based on A Combined Deep Learning Model GU Yuan-li, LU Wen-qi, LI Meng,WANG Shuo, SHAO Zhuang-zhuang 2019, 19(4): 79-86.  Abstract ( )   PDF (545KB) ( )   With the increasing application of internet of things, cloud computing and big data in the field of intelligent transportation system, traditional traffic prediction methods which take the road sections as research object cannot satisfy the development of intelligent connected technique. To forecast the traffic state of lanes, a novel combined deep learning (CDL) model is proposed to predict the travel speed of the lanes of expressways. First, the CDL model introduces an entropy- based grey relation analysis to extract the variables of spatial characteristics. Then, the CDL model uses long short- term memory neural network to capture the temporal characteristics of the extracted spatial variables. Finally, the gated recurrent unit neural network is utilized to predict the travel speed of target lane section in the next time intervals. Validated by the ground-truth microwave data of lane sections on the 2nd ring road of Beijing, the proposed model can well capture the trend of speed change during different time periods of the different lanes and realize the single-step and multi-step prediction of lane speed effectively. The prediction results illustrate that the CDL model outperforms many traditional methods in terms of accuracy and stability. References | Related Articles | Metrics

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Vehicle Trajectory Reconstruction in Signalized-link Using Vehicle Identification Data YU Zhi, LIAO Qiong-hua, HE Zhao-cheng 2019, 19(4): 87-93.  Abstract ( )   PDF (484KB) ( )   Vehicular trajectory data provide a detailed picture of the whole traffic dynamics in time and space, which are critical in analyzing traffic characteristics. However, most of existing methods upon reconstructing vehicle trajectory are carried out using data from inductive loop detectors or/and mobile sensors, and oversaturated conditions are always ignored. In this paper, we present a vehicle identification data- based trajectory reconstruction method for signalized-link, by constructing a phase-to-phase backtracking framework and using the shockwave theory to reconstruct vehicular trajectory segments involved in each backtracking step; in addition, each step consists of two main operations, vehicle state estimation and trajectory reconstruction for two states of vehicles separately. The proposed method is validated using micro-simulation data from Paramics, and the experimental results is satisfactory in both normal condition and over-saturated condition. References | Related Articles | Metrics

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Vehicle Trajectory Optimization Model for Ramp Based on Connect Automatically Vehicles LUO Xiao-ling, JIANG Yang-sheng 2019, 19(4): 94-100.  Abstract ( )   PDF (392KB) ( )   Vehicles from ramp need to reduce the speed and stop at the ramp for merging when signal is red, which causes the long- time delay. A two- level trajectory optimization model based on connected automatically vehicles was proposed. The merging sequence of vehicles is optimized in the first level and the trajectory of vehicles is optimized in the second level. A heuristic model was proposed to solve the first level model and the GPOPS tool was used to solve the second level model. A simulation experiment was carried out to evaluate the proposed approach. 20 min random arrival flow simulation process was used in the simulation experiment. The experiment results show that the proposed method can decrease the total delay and gas consumption by 59.7% and 10.5%, respectively. The vehicle can pass through the conflict zone at high speed, which can reduce the delay and gas cost by using the proposed method. References | Related Articles | Metrics

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Multilayer Perceptron Self-supervised Online Correction Road Recognition Algorithm GONG Jin-liang, SUN Xiao-feng, ZHANG Yan-fei 2019, 19(4): 101-107.  Abstract ( )   PDF (439KB) ( )   For autonomous mobile robot, the performances such as accuracy, robustness and real- time were crucial during the process of unstructured road recognition. A self-supervised online correction algorithm based on region of interest (ROI) and multi-layer perceptron (MLP) was proposed to solve the problem. Firstly, the effective computing region of processed image was defined by the ROI algorithm. Secondly, using multilayer perceptron to train the sample data to classify the region of interest according to the corresponding features, then using morphological processing and feature extraction to select the effective driving area. Lastly, the self- supervised online correction algorithm was used to correct the error processing results to ensure the accuracy of road classification and recognition. The experimental results show that the improved algorithm can accurately identify the road region in the environment. The algorithm is of high real-time and reliability References | Related Articles | Metrics

Systems Engineering Theory and Methods

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Potential High Value Passenger Forecast Based on RBM-GASA-BPNN XU Tao, LIU Ze-jun, LU Min 2019, 19(4): 108-114.  Abstract ( )   PDF (393KB) ( )   Aiming at the problems of weak feature expression ability, poor stability and higher local optimal probability of the potential high-value passengers discovery method based on BP neural network (BPNN), a novel potential high value passengers discovery method based on RBM-GASA-BPNN is proposed in this paper. Firstly, clustering algorithm is used to classify passengers and set category labels. Then the restricted Boltzmann machine (RBM) is used to automatically extract the passenger's behavior features and provide the optimal range of initial weight and bias for BPNN. And the genetic algorithm-simulated annealing (GASA) algorithm is used to adjust the parameters precisely to find the optimal initial weight and bias of BPNN. Finally, the optimized BPNN is used to classify passengers. The experimental results show that the proposed method overcomes the shortcomings of existing method based on BPNN and has a better classification prediction accuracy and potential high value passenger forecast ability. References | Related Articles | Metrics

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Short-term Passenger Flow Prediction Method on Bus Stop Based on Improved Extreme Learning Machine HUANG Yi-shao, HAN Lei 2019, 19(4): 115-123.  Abstract ( )   PDF (598KB) ( )   A short-term passenger flow prediction model on bus stop of optimized extreme learning machine and improved particle swarm optimization is proposed based on the bus IC card and GPS data. According to the characteristic and connection of IC card and GPS data at the bus station, station spacing is defined. Through analyzing the relationship between station spacing and the distance from the traffic to central station, a method to determining the bus passenger boarding station is proposed, and then get the number of boarding passenger at each stop. By analyzing the passenger flow data features of the bus, the dimension of input parameters of ELM is determined. Besides, the improved particle swarm optimization algorithm is used to find the optimal hidden layer node parameters of the extreme learning machine. Finally, the automated fare collection data of the 19 bus in Guangzhou city are taken to method verification. The results show that the prediction error of the optimized ELM method is less than 10%. Compared with SVM, ARIMA and traditional ELM which are widely used, the improved ELM methods has better reliability and generalization performance. References | Related Articles | Metrics

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Travel Time Prediction of Main Transit Line Based on Multi-source Data Fusion LIU Ying, GUO Xiu-cheng, ZHOU Run-xuan, LV Fang 2019, 19(4): 124-129.  Abstract ( )   PDF (428KB) ( )   In order to improve the travel time prediction accuracy of the main transit line in the city center, based on the analysis of the distribution characteristics of the bus travel time, the method of forecasting the transit time based on multi- source data is proposed. The actual data obtained by radio frequency identification and global positioning equipment are preprocessed, and the fitting analysis is carried out by mathematical statistics model. The mixed Gaussian distribution function is suitable for single-segment fitting, and the lognormal distribution is suitable for multi- segment fitting. The Pearson correlation coefficient is used to sort the time series and spatial factors affecting the travel time. The average travel time of the first two time windows of the upstream road segment has the greatest impact. The travel time is predicted by using ARIMA and SVM models, respectively. The mean absolute percentage error of the ARIMA model is 11.69%, and the mean absolute percentage error of the support vector machine model is 6.26%. References | Related Articles | Metrics

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Promoted Short-term Traffic Flow Prediction Model Based on Deep Learning and Support Vector Regression FU Cheng-hong, YANG Shu-min, ZHANG Yang 2019, 19(4): 130-134.  Abstract ( )   PDF (2950KB) ( )   Short- term traffic flow prediction is the basis of an Intelligent Transport Systems (ITS) project. However, in current practice, the methods for short-term traffic flow prediction have encountered many challenges in fitting the traffic flow data, one is it depends too much on historical data. Therefore, a novel short-term traffic flow forecasting method based on Deep Learning and Support Vector Regression (DL-SVR) is proposed in this paper. Firstly, the DL-SVR model is composed by a Restricted Boltzmann Machine (RBM) visible inputting layer with some RBM intermediate layers and a radial SVR output layer. Furthermore, in order to enhance the generalization of the model, an improved Particle Swarm Optimization (PSO) algorithm is designed to optimize the number of nodes in the inputting layer. Finally, the DL-SVR method is compared with other typical short-term traffic flow prediction algorithms on the same computing platform. The experimental results show that the proposed DL-SVR method gets a higher accuracy in its real-time prediction. References | Related Articles | Metrics

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Travel Mode Choice Forecasting Based on Nested Logit-cumulative Prospect Theory Model MA Shu-hong, ZHOU Ye-chao, ZHANG Yan 2019, 19(4): 135-142.  Abstract ( )   PDF (4157KB) ( )   In order to optimize the structure of travel mode choice forecasting model, and deal with the limitations of utility theory in terms of individual risk appetite, incomplete rational decision making, and overall utility of travel mode, a two-factor travel plan is constructed by combining travel mode with departure time, and a joint model based on Nested Logit-cumulative Prospect Theory is established. The objective utility and selection probability of the NL model are subjected by cumulative prospect theory, and two functions (cumulative weight function and value function) are constructed to describe the actual perceived value of travel mode to travelers in the form of prospect value. Finally, the forecasting model is calibrated and tested by the survey data. Results show that the prediction accuracy of the Nested Logit-cumulative Prospect Theory model is higher than NL model, and comprehensive hit ratio rises from 74.8% to 85.2%. The prediction hit ratio of each mode is more balanced. References | Related Articles | Metrics

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Risk Evaluation of Rail Vehicles Based on Risk Network JIA Wen-zheng, WANG Yan-hui, SU Hong-ming, LIU Yue, LIN Shuai 2019, 19(4): 143-148.  Abstract ( )   PDF (3307KB) ( )   The risk network and evaluation method of rail vehicles was discussed. The risk network model is established by taking system components and their connections as nodes and edges, and the factors affecting the inherent risk of components were analyzed, and the calculation method of inherent risk was proposed. Based on the probability of fault propagation, the action intensity of edges was obtained, and the path propagation risk was put forward. The comprehensive risk of nodes was proposed by taking the inherent risk and path risk of nodes into consideration, and solved by power method. Taking the bogie system as a case, the results show that there is no positive correlation between inherent risk and comprehensive risk, but is related to the connection relationship and action intensity of components. Compared with the comprehensive risk ranking of key components obtained by practical experience, the ranking consistency rate of key components obtained by using this method is significantly improved compared with other methods. References | Related Articles | Metrics

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Optimization Model of Emergency Bus Dispatching in Response to Operational Disruptions of Urban Rail Transit WANG Jia-dong, YUAN Zhen-zhou, NING Shang-bin 2019, 19(4): 149-154.  Abstract ( )   PDF (4100KB) ( )   Along with the urban rail transit network expansion and rapid growth in passenger flow, the risk of passengers stranded at the station and emergency response problem are getting more attention. A flexible dispatching strategy was proposed to solve the bus bridging problem in the operational disruption of urban rail transit. Buses are allowed to flexibly serve different bridging routes. An optimization model of multi- objective programming based on flexible routes was proposed to minimize the total evacuation time and average travel delay of all stranded passengers. The model was solved through the ideal point method and genetic algorithm. A case study was carried out and analyzed. Compared with the traditional strategy of fixed routes, the total evacuation time and average travel delay are respectively reduced by 4.2% and 4.4% by this optimized bus dispatching strategy. The results suggested that our approach can improve the efficiency of bus bridging and reduce travel delay. References | Related Articles | Metrics

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An Optimization Method of Hybrid Flexible Feeder Transit Service to Rail Stations LU Xiao-lin, PAN Shu-liang 2019, 19(4): 155-163.  Abstract ( )   PDF (4719KB) ( )   To solve the“last mile”problem faced by people that travels between rail line and community, this paper proposes a new hybrid flexible feeder model, and a new coordinate operation that integrates the traditional fixed-route feeder service with a demand-adaptive flexible feeder service in the passenger-attracting scope of rail stations. Given the passenger demands and fleet size, a route planning and scheduling model of hybrid flexible feeder service is developed with considering the operator cost, passenger cost and departure time of the rail line and fixed-route feeder service. A gravity-based genetic algorithm is given to solve the model rapidly and a case study illustrates the effectiveness and practicability of the proposed model. The results show that the new hybrid model can feeder more people to rail stations with lower operator cost and lower passenger cost. The hybrid flexible feeder service outperforms the single flexible feeder service. References | Related Articles | Metrics

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Traffic Equilibrium Organization Method for Neighbor Weaving Sections Based on Lane-changing Constraints MA Qing-lu, QIAO Ya, FENG Min 2019, 19(4): 164-171.  Abstract ( )   PDF (5203KB) ( )   Aiming at improving the traffic efficiency and safety in the weaving sections, a traffic equilibrium organization method for neighbor weaving sections based on lane-changing constraints is proposed to calculate the optimal early lane-changing distance of the neighbor weaving sections corresponding to traffic volume in different periods, so as to reduce the mutual interference of vehicles in the neighbor weaving sections and reduce the traffic volume. The simulation models of daily average traffic volume (4 092 pcu/h), early peak traffic volume (5 340 pcu/h), late peak traffic volume (4 596 pcu/h) and annual average traffic volume (3 276 pcu/h) in three continuous weaving sectionss of Chongqing Strait Road were analyzed. The multi-objective cumulative average delay in the neighbor weaving sections is selected as the evaluation index of the neighbor weaving sections. The results of 40 continuous simulations with Vissim 4.3 show that the optimal distance of advance lane change constraint is 60% of the length of interlaced zone, and the corresponding average traffic delay is reduced by 57%, 73%, 63% and 72% respectively. References | Related Articles | Metrics

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Model for Un-signalized Intersection Risk Evaluation Based on Traffic Conflict Line Theory YUAN Li, HE Juan, ZHANG Xuan 2019, 19(4): 172-178.  Abstract ( )   PDF (3450KB) ( )   In order to analyze the safety of un-signalized intersections more objectively and systematically, and make up for the deficiency of traditional research focuses on the conflict between two-vehicle,“traffic flow conflict line”was proposed. By analyzing the leading vehicle conflict potential probability, collision severities and transmission length of traffic conflicts, the safety risk assessment model of un-signalized intersections was constructed. The results show that the leading vehicle collision probability model based on the critical collision distance value, considering the speed, angle, acceleration and reaction time of two vehicles, is closer to the real process of traffic conflict. And three traffic conflicts weights were discussed when accident occurs (crossing conflict∶diverge conflict∶merge conflict is 12.705∶1.000∶1.000) according to the principle of physical collision. The model of equivalent expected vehicle-flow conflict at intersections based on mathematical expectation knowledge can describe the actual vehicle- flow conflict behavior more realistically by taking the potential probability, traffic volume, vehicle location and other factors into consideration. References | Related Articles | Metrics

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Traffic Flow Model of Signalized Intersection with Non-motor Vehicle Waiting Area KUANG Xian-yan, CHEN Zi-ru 2019, 19(4): 179-186.  Abstract ( )   PDF (5106KB) ( )   The management and control of urban mixed flow intersection is an important part of traffic management. Aiming to the traffic organization mode of setting up non-motor vehicle waiting area at signalized intersection, a cellular automata model of intersection is built. An improved NS-based multi-lane CA model is used to modeling the motor vehicle flow, in which the lane-changing rules and active deceleration rules are established. The non-motor vehicle flow is modeled using extended multi-value CA model with lateral motion. The traffic flow characteristics and effects of non- motor vehicle density and longitudinal length of waiting area on signalized intersection are researched. The simulation results show that, the waiting area can improve capacity of intersection to a certain extent, if the length of the area is too long, the blocking to motor vehicle flow will increase under certain conditions. On the whole, the waiting area is a kind of worth learning mode. The density of non-motor vehicles has a significant effect on the basic diagrams of motor vehicle flow. References | Related Articles | Metrics

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Optimization of Multi-group Train Operations for Transit Urban Rail with Even Load RONG Ya-ping 2019, 19(4): 187-192.  Abstract ( )   PDF (3555KB) ( )   Multi-group train operations is one important part of the network operation technologies. In order to solve the problem that the train with fewer vehicles is over oversaturated and the train with more vehicles has a lower load factor, a bi-level programming model is established considering the equilibrium of load factor between different trains. The constraints are policy headway, platform length, maximum load and fleet size. The upper-level model is an optimization model of train plan, which is used to determine the optimal frequencies of two types of trains. The lower-level model is an optimization model of equilibrium of load factor, which is to determine the optimal formation plans and departure interval. And a nested genetic algorithm is also proposed. The results indicate that when the train formation and frequency is fixed, the average load of the trains under the even headways is 50%, the difference is only 0.8% under the uneven headways. The number of vehicles of two kinds of trains has minor differences can improve the equilibrium of train load factor under even headways. Besides, adjusting the headways between different train formations under uneven headways can realize the equilibrium of load factor in time and space. References | Related Articles | Metrics

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Performance Analysis of Car Assembly Queuing Model of Marshalling Station in the Time-fixed Mode with Softened Terms LI Jing, SHUAI Bin, XU Min-hao, ZHU Wei-bo, HE Chun-yan 2019, 19(4): 193-201.  Abstract ( )   PDF (6163KB) ( )   The assembly mode determines the end condition of a car assembly process. Time-fixed assembling is a highly efficient mode, which is propitious to improve transport quality. For the problem that cars assemble in a marshalling station in the time-fixed mode with soften terms, a discrete time queuing model with batch-arrival and batch- service was built. Queue length distributions at departure epochs were obtained based on the embedded Markov chain technique. Next, queue length distributions at arbitrary epochs were derived. Based on these probabilities, various performance measures of interest such as the mean queue length, the mean accumulation delay, efficiency, traffic volume in one day were discussed though analyzing the impacts of minimum number of cars, batch size distributions, arriving intensity, service time distributions. The analysis shows that these factors have significant effect on the system performance. Therefore, this model can be used to provide decision references for the delicacy management of the marshalling yard and optimization of car flows. References | Related Articles | Metrics

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Passenger-cargo RORO Ships Stowage Planning Decision with Two-dimensional Packing Constraints ZHANG Yu, MA Shao-kang, MA Jie, LI Jun 2019, 19(4): 202-210.  Abstract ( )   PDF (4747KB) ( )   The stowage planning for the passenger-cargo RORO(Roll-on/roll-off) ship still stays in the manual decision stage. Its particularity makes it impossible to adopt existing stowage methods for RORO ships. In order to improve the stowage planning decision of passenger-cargo RORO ports, the stowage planning decision model is constructed with the maximization of ship cabin area utilization considering two- phase and two- dimensional packing characteristics of stowage planning process. The biased random key hybrid genetic algorithm which composed of a multi- phase heuristic and biased random key genetic algorithm is designed to find large- scale solutions. The initial solution is constructed firstly through the multi- phase heuristic including the first layer stowage planning, main stowage planning and supplementary stowage planning. And then the ship’s stability is modified through the heeling and trimming moment optimization strategy. Numerical example shows that the algorithm performs well and has a good robustness for large- scale application experiments. It can achieve the effective stowage planning for the passenger-cargo RORO ship. References | Related Articles | Metrics

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Airport Network Spillover Effect with Spatial Econometric Models CHEN Xin, YUAN Jian, DAI Liang 2019, 19(4): 211-217.  Abstract ( )   PDF (4292KB) ( )   Airport plays an important role in developing regional economy, but there are few studies on this topic from the flight network perspective. This paper established spatial panel econometric models, and studied the direct effects, network spillover effects and total effects of the airport on regional economy with 45 major hub airports in China mainland as an example. The results show that passenger traffic volume of the airport has a significant positive network spillover effect on the regional economy. For every 10% increase in passenger traffic, the network effect reaches 8.25%. The air cargo volume has only a positive impact on the GDP of the local city, and its spillover effect fails to pass significant test. Meanwhile, it is found that the spillover effect of airport passenger and cargo on connected cities in the network is greater than its direct effect on the local economy. Neglecting the network spillover effects will underestimate the overall contribution of airports to regional economy. The research results have reference values for evaluating the effects of airport on economic development. References | Related Articles | Metrics

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Method for Determining Road Boundaries Based on Pollutant Diffusion XU Yao-fang, GONG Hua-feng 2019, 19(4): 218-226.  Abstract ( )   PDF (5709KB) ( )   Based on the combination of MOVES and road diffusion model CAL3QHC, the analysis of pollutant concentration from sensitive point to global pollutant condition is realized by comparison interpolation method, and an integrated platform framework for visual analysis of pollutant emission and diffusion is established, which can be used to carry out the global analysis of pollutants around road construction. Based on this framework, taking the Nanwan Avenue (located in Zhuhai Province of China) as a case, the proportion of high- emission sections on this Avenue decreased by 13.64% after the implementation of traffic diversion strategy. It shows that the way of changing road grades and increasing the number of traffic diversion routes achieves effective diffusion of traffic emissions. After determining the traffic diversion strategy, emissions on different Nanwan Avenue sections are discussed. It is found that emissions of the 17th and 18th sections are the most serious, and the limit value is 315 m at the widest point in the lateral direction and 19 m at the highest point in the longitudinal direction. In addition, the intersection is taken as the object of diffusion analysis, and the intersection boundaries are determined after synthesizing different pollutant diffusion ranges. References | Related Articles | Metrics

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Ladder Probability Rule Optimization of License-plate Lottery in Beijing LI Tao, YANG Wen-yin, WANG Lei, YAN Hai 2019, 19(4): 227-232.  Abstract ( )   PDF (3211KB) ( )   Due to the rapid growth of the number of vehicles, Beijing has implemented license- plate lottery policy to control the number of vehicles increasing since 2011. In order to solve the problem that some groups of people participated for a long time but never won the lottery, the "ladder probability" rule has been implemented since 2014. However, the effect is not significant. This paper establishes an evolutionary model to describe the probability change of different groups based on the analysis of the current license-plate lottery rule in Beijing. The rationality of the current "ladder probability" is analyzed, and the improved "ladder probability" rule is proposed. Through the analysis, it is found that the current "ladder probability" rule could not continuously improve the winning probability of earlier participants, the main reason is that the degree of probability improvement is insufficient. The improved "ladder probability" rule can increase the winning probability of all groups with time when the adjustment intensity is reasonable. The disadvantage of this rule is that it reduces the winning probability of new participants in the current period. The research conclusions provide theoretical support for managers to carry out scientific license-plate lottery policy. References | Related Articles | Metrics

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Exploring the Relationship Between Built Environment and Bus Transit Usage Based on IC Card Data ZHAO Li-yuan, WANG Shu-xian, WEI Jia-ling 2019, 19(4): 233-238.  Abstract ( )   PDF (4247KB) ( )   Researches regarding the impact of the built environment on transit usage have gradually attracted wide attention. This study captures correlations between transit usage with attributes from different spatial scales, and reals the causality of differences found in these correlation results. Drawing on the smart card data in Wuhan, this study proposes a bi- level hierarchical linear model (HLM) to explore the compound influence of both the surrounding built environmental factors at neighborhood level and socioeconomic variables at regional level on bus transit trip ratio. The results show that there are obvious differences in the effect and extent of builtenvironment on transit usage across different spatial regions. The population and public transportation investment at regional level are important factors leading to these differences, and further produce additional effects to transit usage. This study could provide theoretical and technical support to guide practice in transit oriented and low carbon urban development. References | Related Articles | Metrics

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City Transport Planning Oriented Research on Multi Cellular Signaling Data Relationship ZHANG Xiao-chun, YU Zhuang, DUAN Bing-ruo, GAO Yong, AN Jian 2019, 19(4): 239-245.  Abstract ( )   PDF (4245KB) ( )   With the popularity of the smart phone, the cellular signaling data become an effective data resource to obtain the city traffic pattern. However, most of analyzing results of cellular signaling data were obtained from one carrier instead of all carriers in the city. It is hard to answer whether the one-carrier-based result can satisfy the demand of city transport planning. Aiming at this problem, this paper from the perspective of data analysis, based on two carriers’cellular signaling data of one city, China, analyzed whether the result of city population distribution and city traffic pattern obtained from two carriers signaling data was significantly different. Based on the research result of this paper, it is found that the city traffic and resident movement patterns computed by two carriers’data are pretty similar. Especially for city OD matrix and moving resident distribution, their correlation coefficients were large even the time and space scale was changing. However, there are big difference between the results of stop people distribution before dawn, which derived from the difference of position update cycle between carriers. References | Related Articles | Metrics

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Influencing Factors of Truck Operating Speed at High Altitude Area XU Duo, FANG Shou-en, CHEN Yu-ren, ZHUANG Jia-feng 2019, 19(4): 246-251.  Abstract ( )   PDF (3764KB) ( )   In order to study the speed of heavy trucks at high altitude area, the GPS data of 20 trucks in Tibet were collected. Through the calculation of the variable, the alignment was restored. The model of the upper and lower slope of the truck was constructed with longitudinal slope, horizontal curve, altitude and time as the key variables. The results show that horizontal curve and longitudinal slope have significant influence on the speed of the truck uphill, while horizontal curve, longitudinal slope, the time and the altitude have significant influence on the speed of trucks downhill. Alignment factors on the upper and lower slopes are different, but the position of the speed high risk area is similar. Drivers with resting time below 2 h have no significant differences on speed control, but have differences on speed dispersion uphills. The study can be used to analyze the speed variation of trucks at high altitude areas, and at the same time to improve the driving safety of drivers. References | Related Articles | Metrics