2016 No. 1

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2016, (1) doi: 10.3963/j.issn.1674-4861.2016.01.001
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2016, (1) doi: 10.3963/j.issn.1674-4861.2016.01.002
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A Review and Prospect of Ship Intelligent Collision Avoidance System
XIE Shuo, CHU Xiumin, LIU Chenguang, WU Qing
2016, (1): 1-9. doi: 10.3963/j.issn 1674-4861.2016.01.001
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Owing to the increasing maritime transport volume and complexity of waterway,ship intelligent collision avoidance has attracted great attention in the field of maritime traffic safety.This review summarizes four important intel-ligent collision avoidance systems based on expert systems,fuzzy control,neural networks and artificial potential field, and discusses the key techniques,including collision avoidance model and collision avoidance information,to be chal-lenged.Then collision avoidance model with dynamics description and the classification of collision avoidance information based on the weights are elucidated.Finally,the prospects for ship intelligent collision avoidance system are considered, including the stereoscopic ship and online risk identification through collision model.
Hotspots and Challenges of Shipping Development Based on the World Shipping Summit 2015
WANG Kai, YUAN Yupeng, YAN Xinping, ZOU Minglei
2016, (1): 10-16,22. doi: 10.3963/j.issn 1674-4861.2016.01.001
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In view of the advances presented at the World Shipping Summit 201 5,the hotspots and challenges of the shipping development are reviewed under the new circumstances of the modern shipping industry,in order to provide a reference for the perspectives of the industry.The emerging concepts of the modern shipping industry mainly include:the applications of the big data,mobile internet services,and shipping industry based on the"Industry 4.0".The intelligent, high-performance and green ship has been highlighted as the develop trend of modern shipping industry.The major chal-lenges lie in the reduction of operation cost,innovation and upgrading of current business model,etc.
Characteristics Analysis of Lane Changing Behavior Based on the Naturalistic Driving Data
WANG Xuesong, LI Yan
2016, (1): 17-22. doi: 10.3963/j.issn 1674-4861.2016.01.001
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In order to study characteristics of drivers′lane changing behaviors,including lane changing frequency, motivations,gazing behavior and turn signal usage,drivers′behavior and vehicle operating data are collected from Shang-hai naturalistic driving study.Lane changing is identified by lane departure and its variables are thus extracted.Character-istics of lane changing behavior are analyzed and compared between different types of road.Lane changing behavior con-stantly occurs on urban arterial road,with a frequency of 0.82 per kilometer.The rate of the multilane changing on the freeway is relatively higher,being a potential threat to the drivers.Comparing with the study results by Olsen et al.,it appears that drivers rarely carry out"shoulder check"the blind spot before lane changing behavior although,the percent-age of side mirrors check and use of turn signal is relatively high.Potential risks exist in the frequent lane changes,multi-lane changing and blind spot ignorance,which deserve further studies.
Fast Sign Recognition Based on ORB Holistic Feature and K-Nearest Neighbor Method
HU Yuezhi, LI Na, HU Zhaozheng, LI Yicheng
2016, (1): 23-29. doi: 10.3963/j.issn 1674-4861.2016.01.001
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Traffic signs contain important traffic information.Automatic recognition of traffic signs is a crucial tech-nology for intelligent vehicles and advanced driver assistance systems (ADAS).Fast and accurate sign recognition is espe-cially important for safe driving.This paper proposes a fast sign recognition algorithm based on holistic features extracted through an Oriented FAST Rotated BRIEF (ORB)method.ORB is a local description operator,which is commonly used for local feature matching.In this paper,an input sign image is first normalized and the central point of the normalized image is set as the location of an ORB feature point.Regarding the normalized image as an ORB patch,the ORB feature point descriptor is computed as sign holistic feature.In the recognition stage,the K-Nearest Neighbor (KNN)method is utilized to recognize sign types based on Hamming distances.One advantage of KNN method is that all the signs recog-nized successfully can be further utilized as the samples in the training database.This proposed algorithm has been tested with public GTSRB traffic sign database.The recognition rate is 91%,and the average processing time including ORB feature extraction and sign recognition is less than 2 ms.Experimental results show that this proposed algorithm is fast, accurate,and robust for traffic sign recognition.
A method for estimating OD Matrix of Urban Road Network using RFID and Analysisof its Spatio-temporal Features
ZHAO Xiaoxiao, DU Wei, ZHOU Xu, GUO Jianhua
2016, (1): 30-36,50. doi: 10.3963/j.issn 1674-4861.2016.01.001
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In order to meet data requirement of modern urban traffic management systems,an acquisition technique for origin-destination (OD)matrix based on the radio frequency identification technology (RFID)is proposed.This paper takes RFID base stations installed along urban road network as origins and destinations,license plate data collected at ori-gins and destinations through RFID is matched using a set of data mining techniques,under different aggregate time reso-lutions.Based on this technique,a sample of road network extracted from City of Nanjing is selected as the case study,its OD data is collected,OD matrix is developed and its spatio-temporal features are analyzed.Empirical results show that the proposed technique is able to obtain the OD matrix under any aggregate time resolution,and the spatio-temporal fea-tures of the obtained matrices are consistent with observed traffic conditions.The proposed technique shows an excellent timeliness and operability,providing an important data tool for urban transportation management.
A Forecasting Model for Estimating Passenger Throughput of Civil Aviation at Navigable City
PENG Ting, ZHANG Yaping, HAO Siqi, FU Chuanyun
2016, (1): 37-44,63. doi: 10.3963/j.issn 1674-4861.2016.01.001
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Forecast of the passenger throughput of civil aviation is an important prerequisite for determining the timing and size of construction of airports.When proposing a forecasting model of passenger flow suitable for newly con-structed airports and improve the forecast accuracy of the traditional models,it should not only analyze the influences of social economy on passenger throughput of civil aviation,but also consider the factors,such as the structure of aviation network,etc.Meanwhile,in order to tackle the multicollinearity issue and ensure the accuracy of this model,a set of model forms are systematically compared.Results show that the passenger throughput of civil aviation in navigable cities is significantly affected by the output of tertiary industry,number of tourists,average path length and node degree.The explanatory power of the proposed forecasting model for the passenger throughput of civil aviation reaches 97.4%,and the forecast errors of most cities are within 10%.The proposed forecasting model has a high forecast accuracy.However, the forecast accuracy for some tourism cities or edge cities are found to be lower.
A Classification Method for Multimodal Passenger Hubs Based on SOM Neural Network
ZHU Canghui, LI Penglin, WANG Yadi
2016, (1): 45-50. doi: 10.3963/j.issn 1674-4861.2016.01.001
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In order to study the criteria for classifying multi-modal passenger hubs and to guide the construction of hubs of different importance,based on the design manual of terminal and yard of different transport modes and the trans-fer passenger volumes among the modes,total number of passengers traveling outside the region and total number of pas-sengers transferring from one mode to another are proposed as two classification criteria.The two reflect the factors large-ly determine the size of passenger hubs,which is required for supporting external travel and transfer.90 multimodal pas-senger hubs are selected as the case study.Self-organizing feature map (SOM)neural network,which is featured with un-supervised self-organization,self-learning and automatic classification and no need for testing data,is applied.A cumula-tive frequency method is used to determine the thresholds for classifying hubs and improve the Euclidean distance func-tion,which solves the problem related to the classification criteria with very strong correlation.Study results show that two selected,common classification criteria can reflect diversity of the construction size of the passenger hubs of different classes.The improved method also enhances the convergence speed and clustering accuracy of the neural network.
Research on Vehicle Running Characteristics Based on Driver′s Perception
CHANG Xin, RONG Jian, ZHOU Chenjing, CHEN Chunan
2016, (1): 51-56. doi: 10.3963/j.issn 1674-4861.2016.01.001
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In addition to mechanical characteristics of vehicle,driver′s perception also has certain effect on the oper-ation of the vehicle.However,quantitative and empirical analysis through field experiments is still relatively limited. Based on driving perception and force analysis,vehicle operation is divided into three acceleration/deceleration states;which are acceptable,barely acceptable,and unacceptable vehicles′operating states are determined by driver′s perception and vehicle speed.Driver′s perception data is recorded by in-vehicle observer,and vehicle speed data is collected by a high precision GPS (v-box).According to the Raff′s critical gap method,the critical thresholds of the three states are ob-tained.The results show that if the driver is in an acceptable state,the acceleration rate ranges from 0 ~3.28 m/s2 ;the deceleration rate ranges from -3.48~0 m/s2 .When vehicle operates normally,the critical thresholds of the three states rarely exceed the above ranges.Study results provide a reference to the understanding of vehicle operation characteristics and calibration of traffic simulation parameters.
A Study of Power-law Distribution of Headways at Urban Tunnel Entrance
CHEN Xinyu, ZANG Xiaodong, ZHAO Bin
2016, (1): 57-63. doi: 10.3963/j.issn 1674-4861.2016.01.001
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Headway is one of the most important parameters in traffic flow and random process.In order to study the statistical characteristics of traffic flow at tunnel entrance,this study investigates headway data on different lanes and different periods in Guanzhou tunnel and CBD tunnel in Guangzhou.The results show that the random process of vehicle headway deviates from the negative exponential distribution,and presents non-Poisson characteristics.A new power-law distribution function is therefore proposed to fit the headway distribution.Furthermore,the unknown parameters for the proposed power-law distribution are estimated by maximum likelihood estimation and genetic algorithm.The goodness-of-fit of model is verified through a Chi-square test against 9 sets of observed data.The results show that the empirical head-way distributions present the feature that the headways firstly increase and then decrease.The results also illustrate that the exponential distribution does not fit the observed data and is rejected by the Chi-square test.The non-Poisson charac-teristic of headway distribution is clear.On the other hand,the power-law distribution fits the observed datasets well with the fact that 8 out of 9 data sets passed the Chi-square test.In conclusion,the power-law distribution can fit the headway distribution well,especially when non-Poisson characteristics are dominant.The mechanism and dynamic effect behind the non-Poisson characteristics requires further study.
Modeling Safety of Urban Arterials and Identification of Impact Factors
FAN Tianxiang, WANG Xuesong
2016, (1): 64-70. doi: 10.3963/j.issn 1674-4861.2016.01.001
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Arterial roads are the framework of urban road network,where the crash occurs frequently due to com-plex traffic environment.It is necessary to conduct corresponding safety analysis,in order to propose constructive coun-termeasures.Geometric features,land use,traffic volume and average speed are gathered at a total of 1 76 road segments from 18 arterial roads in Shanghai.Average segment speed is calculated from floating car data (FCD),which solved the problems related to speed data collection with sensors installed on fixed locations.Considering correlations among seg-ments along an arterial roads,a set of Bayesian hierarchical Poisson log-normal models are developed.The Full Bayesian Method is used for parameter estimation and different prior distributions are tested.Crash features vary depending on time,so the models for peak and off-peak hours are developed separately.Results indicate that hierarchical models im-prove the goodness-of-fit of the data because deviance information criterion (DIC)values of hierarchical models are signifi-cantly less than maximum likelihood estimation (MLE)prior models.The reliability of parameter estimation can be im-proved by MLE prior.The standard deviations of parameters of the MLE prior models are less than those of non-informa-tive models.Along arterial roads,the longer the segment length,the more crashes.At the segment level,geometric fea-tures and land use are substantially associated with crash frequencies.Higher traffic volume is associated with increased crash frequencies especially during peak hours.Average segment speed contributes to increasing crash occurrence during peak hours.
A Study on the Algorithm for Real Time Flight Conflict Detection and Resolution During Low-altitude Rescue
ZHANG Ming, WANG Lei, WANG Shuo, YU Hui
2016, (1): 71-77,84. doi: 10.3963/j.issn 1674-4861.2016.01.001
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Real-time flight conflict detection and resolution algorithm is very important to aviation emergency rescue under the environment of complex low-altitude airspace.Based on low-altitude visual flight rules,this paper constructed a three-dimensional spatial grid,using the time window theory to analyze the temporal and spatial conflict of two flights. Based on visual flight rules during rescue and performance constraints of aircrafts,a feasible path set and Airspace model based on mesh generation for flight Agents are developed.Then priority of each Agent is identified at the conflicting point. Feasible non-conflict paths can be obtained by using the Agent model.Then an optimal path planning method is developed and the paths without any conflicts are created.The results are verified through a simulation,and the time window and the area of flight conflict,and the paths without any conflicts under different priority are analyzed.The results show that this method can provide a higher solution efficiency than non-collaborative methods,which can save a flight time of 146 s.
An Accident Prediction Model for Expressway Based on BP Neural Network
DENG Xiaoqing, MENG Xianghai, ZHENG Lai
2016, (1): 78-84. doi: 10.3963/j.issn 1674-4861.2016.01.001
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According to the geometric alignment,traffic volume and accident data of expressway in mountain and hilly areas in China,an accident prediction model is developed based on geometric alignment and traffic volume for expre-ssway segments.A correlation test for geometric features is undertaken by mean impact value.The results show that the features are found to be significant over the test including tangent length,horizontal curve radius,deflection angle,verti-cal curve radius and longitudinal gradient.Accident factors are divided according to the test results.An accident prediction model is developed based on BP neural network.The accuracy of this model reaches 88%,and its applicability on specific expressway segments is verified.The relationship between alignment features and accident rate is verified with sensitivity analysis.The results of model validation show that this model can be applied to all types of expressway segments in mountain and hilly areas with a high accuracy.
A Grid Based Model for Risk Index Evaluation of Railway Construction Projects
GUO Mengxin, ZHONG Yan, WANG Futian, YANG Huiwen
2016, (1): 85-90,102. doi: 10.3963/j.issn 1674-4861.2016.01.001
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Enhancing the level of risk management has become an important part of railway construction projects. However,there are limited refined and quantitative analysis in the present studies.According to the actual characteristics of railway construction and risk management in China,a quantitative risk evaluation model of railway construction pro-jects based on the grid and factors method is proposed and applied to the risk assessment of upgrade projects in China Railway Corporation in this paper.The results show that the risk indices of grid point G48,27 ;G49 ,27 ;G5 5 ,2 9 and G5 6 ,2 9 are 64.9;64.9;75.8 and 75.8,respectively.The first two grid points have Level Ⅲ risks within the warning category,while the latter two have Ⅳ level risks,belonging to the potentially risky category.This model is able to conduct refined,quan-titative and visualized risk assessment of railway construction project,and facilitate real-time risk control.
Analysis of Risky Driving Behaviors on Freeways Based on an AHP Method
HE Wenya, LYU Bin, WANG Zhongyu, WU Bing, LI Linbo
2016, (1): 91-95,102. doi: 10.3963/j.issn 1674-4861.2016.01.001
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In order to propose safety management measures for freeways and reduce accidents,a hierarchical model of risky driving behaviors on freeways based on an Analytic Hierarchy Process (AHP)is established.The matrices for judging whether driving behaviors are risky are determined by expert scoring.Then,the sorted single weight and com-bined weight of elements at all levels of the model are calculated.Then,the relative importance of risk driving behaviors on freeways is sorted.It shows that frequent lane change (lane change behavior)is the driving behavior of the highest risk.Finally,the measures to reduce risky driving behaviors on freeway are discussed.The proposed analysis process pro-vides a new method to evaluate the risky driving behaviors on freeways,and the findings from this paper can advise the drivers about which types of behaviors are more risky and the level of safety on freeways could be improved accordingly.
An E-bayes Reliability Analysis of the EIDI Power Supply Based on FTA Failure Assessment
LIU Lin, GE Hongjuan, CHEN Peng
2016, (1): 96-102. doi: 10.3963/j.issn 1674-4861.2016.01.001
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An E-bayes reliability analysis method is proposed based on FTA Failure Assessment to evaluate the reli-ability of airborne equipment in case of zero-failure data.The failure rate of electro-impulse de-icing (EIDI)power supply is calculated by FTA analysis,and incorporated to the E-bayes estimation for computing the censored time for the k+1 fix-time censored test.Then the E-bayes method is used to estimate the average life of EIDI power supply.The robustness of the average life estimation of power supply is studied via a comparison of traditional E-bayes method,synthetic expec-ted-bayes method and E-bayes reliability analysis method,based on FTA failure assessment.The results indicate that this E-bayes reliability analysis method based on FTA failure assessment is robust,feasible and convenient to be applied in en-gineering in the case of zero-failure data.
A Simulation Analysis of Waiting Area for Through Vehicle Considering Emission Reduction
LIN Fen, CHENG Lin
2016, (1): 103-109,129. doi: 10.3963/j.issn 1674-4861.2016.01.001
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Considering increasing congestion at intersections and air pollution in urban areas,this paper proposes a method of setting up a waiting area for through vehicles in front of through and right-turn sharing lane on the basis of e-mission reduction.This paper uses Vissim to study the sharing lane with waiting area for through vehicles.A control group without waiting area for through vehicles is setup for comparison.Parameters including link flows and right-turn ratio are changed systematically to evaluate their influences on a set of factors,including emissions,fuel consumption, average car delays and the number of stops.Weights are assigned to those factors to quantitatively evaluate the effective-ness of the lane configurations in terms of efficiency and environmental protection.This study finally develops an evalua-tion and optimization strategy with the consideration of energy conservation and emission reduction for through and right-turn sharing lane with waiting area for through vehicles.This paper also takes a signalized intersection of Jiangsu Road and Changning Road of Shanghai as a case study to illustrate the effectiveness of this strategy.Simulation results demon-strate that when the link flow is between 300~550 pcu/h and the right-turn ratio is between 40%~50%,it is the opti-mal point to set waiting areas for through vehicles.Under this condition,the through put efficiency improves by 22.9%;the automotive emission decreasesby 32.8%;and the fuel consumption decreases by 32%;the average car delays declines by 46%;and the number of stops increases by 43.7%.The benefit of setting waiting areas according to the proposed strat-egy is obvious,and the overall operating conditions at the signalized intersections can be greatly improved.
Simulation of the Impact of Departure Time Choice Behavior on Traffic Operation under ATIS
LI Chunyan, YE Xiaofei, CHEN Jun, SUN Zhengan
2016, (1): 110-115. doi: 10.3963/j.issn 1674-4861.2016.01.001
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To study the impacts of choice behavior of departure time on urban traffic operation under real-time pro-vision of traveler information through advanced traveler information systems (ATIS),taking drivers′choice behavior of different departure time as the target under 4 scenarios with different types of real-time information,which is descriptive, quantitative,forecasted and instructional information respectively.Vissim software is used to simulate and analyze the im-provement of traffic operation due to the choice behavior of different departure time.Using the trial and error method, traffic volume is used as an input to the simulation,in orderto ensure that the impact of different provision of real-time in-formation can be quantitatively expressed in the simulation experiments.By simulating choice behavior of different depar-ture time under the scenario without any real-time information and 4 above scenarios,the corresponding traffic delays are compared to evaluate their impact on traffic operation.Nanjing is taken as a case study for the simulation analysis.The re-sults show that the number of road segments with regular traffic delay decreases by 33% and the duration of traffic con-gestion decreases dramatically.It is found that Vissim can well simulate macroscopic traffic operation resulting from ag-gregated microscopic travel behavior.
A Study of the Impact of Vehicle Restriction Policies on Traffic Flow:A Case Study of Tianjin
YANG Yu, LI Geng, WANG Rong, QIU Peng, JIA Ning
2016, (1): 116-122. doi: 10.3963/j.issn 1674-4861.2016.01.001
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The effectiveness of the restriction policies has always been controversial since their wide implementa-tions at home and abroad.A multivariate linear regression model has been applied to quantitatively evaluate the impact of restriction policies on traffic flow of motor vehicles in a case study of Tianjin.The variation of traffic flow of motor vehi-cles after the implementation of restriction policies is investigated in different times of the day.By selecting different inde-pendent variables and dependent variables for the regression analyses,the impact of tail-number restriction policy on traf-fic flow of weekdays,the impact at road intersections,and variations of vehicle traffic flows on weekends are studied.It is shown that the traffic flow is closely related to the restriction rules.The traffic flows of workdays at major road intersec-tions are reduced by 1 6% at most while a maximum reduction rate of 27.4% is resulted by odd-even license plate rule dur-ing the APEC.Moreover,the traffic flow before the morning rush hour increased by 23.7% on weekdays when the two-number restriction policy is applied,indicating that people tend to travel earlier to work around the restriction policies. Traffic flow on weekend increases 8% ~ 22% after the implementation of two-number restriction policy on weekdays, suggesting more flexible travel demand are being shifted to weekends.
Development of the Level of Service for the Facilities of Urban Rail Transit Stations Based on Microscopic Simulation
YANG Taoyuan, WU Haiyan, YANG Jing, LIU Bo
2016, (1): 123-129. doi: 10.3963/j.issn 1674-4861.2016.01.001
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Level of Service (LOS)of pedestrian facilities of urban rail stations is a key indicator of the service quali-ty of rail transit system.Reasonable LOS is of great significance in station planning and design.This paper provides a re-view of previous studies on LOS of pedestrian facilities.Pedestrian space is selected as the target to evaluate the existing standards of LOS in terms of categorization,the thresholds of each category,the number of categories and the corre-sponding descriptions.To explore the practicality of existing evaluation standards for urban rail transit stations in China, this paper develops a LOS evaluation model for pedestrian facilities based on simulation results of the Legion software. Taking Hujialou subway station of Beijing as a case study,simulation and observed results are compared.The results in-dicate that,though the standards for free pedestrian flow in Transit Capacity and Quality of Service Manual need to be improved,this manual largely reflects the observed conditions of subway stations and is a useful reference for guiding sta-tion operations in China.
2016, (1): 130-130. doi: 10.3963/j.issn.1674-4861.2016.01.022
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2016, (1): 131-131. doi: 10.3963/j.issn.1674-4861.2016.01.023
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2016, (1): 131-131. doi: 10.3963/j.issn.1674-4861.2016.01.024
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2016, (1): 132-132. doi: 10.3963/j.issn.1674-4861.2016.01.025
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