2017 No. 2

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2017, 35(2)
Abstract(93) PDF(2)
Abstract:
Overview
A Review on Human Factors in Maritime Accidents
FAN Shiqi, YAN Xinping, ZHANG Jinfen, ZHANG Di
2017, 35(2): 1-8. doi: 10.3963/j.issn.1674-4861.2017.02.001
Abstract(464) PDF(3)
Abstract:
75%-96% of maritime accidents are caused by human factors.It is thus vital for navigation safety to explore the relationship between physical or physiological state and operational errors during seafarers′ operations on board.This paper introduces contents of human factors in maritime accidents, and measurements of human factors, e.g.electroencephalography (EEG) and Near-Infrared Spectroscopy (NIFS).Studies on physiological signals and human factors are reviewed.Relationships among neurophysiologic data changes, workload, attention, stress and fatigue of seafarers are elaborated.Ultimately, the prospect of human factor studies is discussed.It tends to study seafarers′ behavior, force-warning human failures, optimization of crews training systems, and improvement of duty system based on neurophysiologic data.It is significance to help decrease human errors in maritime accidents and enhances safety of shipping.
Transportation Safety
Effects of Fatigue Driving on Lateral Performance with Consideration of Horizontal Curve Design
2017, 35(2): 9-15. doi: 10.3963/j.issn.1674-4861.2017.02.002
Abstract(144) PDF(2)
Abstract:
Different geometric design of roads has different requirements for lateral performance.Drivers affected by increased fatigue level will also show a decline in the ability to maintain in the lane.Current studies do not take interaction effects of geometric design and degrees of fatigue on lateral performance of drivers into consideration.This study aims to explore impacts of horizontal road design on lateral performance of fatigued drivers.In total, 41 middle-aged drivers in China were recruited to participate in a field driving test of 550 km.The self-reported fatigue level was recorded according to the Karolinska Sleepiness Scale (KSS);the standard deviation of lateral position (SDLP) was recorded for performance analysis, and the GPS data were recorded as location information.Driving performance under different fatigue levels and at different horizontal types and radii of road curves are analyzed.A multi-linear regression model is further proposed in this study to analysis the correlation among the SDLP, fatigue level and radius of circular curve.The results indicate that when participants are driving along a circular curve, their SDLP is greater than when they driving along a tangent or transition curve at the same fatigue level.The analysis on the impacts of curve radius on SDLP indicates that the driving performance of participants is worse when the circular radius is higher, especially when it is greater than 5 500 m.In conclusion, this study demonstrates the impacts of geometric design of horizontal curve types and curve radius on driving performance when drivers are influenced by different fatigue levels.In addition, if horizontal geometrical parameters can be obtained during driving, the accuracy of identifying fatigued driving based on driving performance can be improved.
A Model for Calculating Reliability of Airport Road Network Considering Congestion Cost
JIA Junhua, BAO Danwen, GU Jiayu
2017, 35(2): 16-22,34. doi: 10.3963/j.issn.1674-4861.2017.02.003
Abstract(115) PDF(1)
Abstract:
Traditional algorithms to calculate the reliability of travel time applied in airport road network have two main problems, which are neither considering actual conditions of road network nor airport access cost of travellers.To resolve these two problems, congested-road amendment factors and cost factors are used to develop a time estimation model for travel time to an airport.A method of minimum square error sum (LSE) is proposed to validate this improved model.The road network of Nanjing airport is taken as a case study.It shows that the LSE of the improved method is 0.57 and lower than 0.03 of traditional algorithms.Therefore, the improved method is closer to actual conditions of the road network.Reliability of travel time in the road segment of Nanjing airport is predicted between 0.69 and 0.89, while that in the road network is between 0.65 and 0.78.The improved method shows that the reliability of travel time in the road network is unevenly distributed and low in the core segments.The improved method that is proposed in this paper can be used to close the gap between the traditional algorithms and actual conditions of road network.
Evaluation Methods of Severity Level of Water Traffic Flow Conflict Based on BP Neural Network
FAN Yaotian, WANG Chi
2017, 35(2): 23-29. doi: 10.3963/j.issn.1674-4861.2017.02.004
Abstract(159) PDF(2)
Abstract:
Existing approaches to evaluate ship traffic flow are difficult to use when the relationships among the indicators are not clear.These methods are subjective and the results are usually deviated from the real cases.In order to reduce effects of experts' subjectivity when evaluating the severity of marine traffic flow conflicts, a model based on BP neural network is proposed in this paper, in which the precision of Trainlm function is calculated and the number of iterations is determined using network training.In order to avoid the influences of the data on training efficiency and accuracy of BP neural network, a new model based on clustering analysis and BP neural network is proposed.The training data is classified according to Euclidean metric in order to carry out neural network training.This model is then used to evaluate the severity of the conflicts of water traffic flow.A case study of 9 channels is then performed to evaluate the proposed model.Comparing the processed data by clustering analysis with the original data, the evaluation error is reduced to 23.74% from 42.05%, which verifies the feasibility of BP neural network in this case.The modified model, which combining BP neural network with cluster analysis, has higher precision and more objectivity.
An Algorithm for Ripple Suppression of Inland Ship Detection Based on SuBSENSE
LI Jing, LIU Qing, YAN Weilang
2017, 35(2): 30-34. doi: 10.3963/j.issn.1674-4861.2017.02.005
Abstract(150) PDF(1)
Abstract:
SuBSENSE is a universal detection algorithm for moving objects which combines color and texture features.The background model can adapt to a variety of inland environments and achieve parameter optimization through its adaptive feedback mechanism.However, the ripples cannot be removed when directly detecting inland ships by SubSENSE.Aiming at solving this problem, a novel algorithm combining SuBSENSE and a method for detecting significant regions based on global contrast is proposed.There is a fact that the saliency values of ships and ripples are typically different, ships and ripples are separated in binary saliency image.Logical bitwise AND is performed between the binary saliency image and the SuBSENSE detection image to get final results.The method has shown excellent results in simulations, with a 14.6% margin over the original SuBSENSE performance.
A Study on Demographics of Drunk Drivers Using a Log-linear Model
HE Qing, WAN Meina, LI Yang, GAO Aixia, WANG Ying
2017, 35(2): 35-39,58. doi: 10.3963/j.issn.1674-4861.2017.02.006
Abstract(157) PDF(1)
Abstract:
A study on the demographics of drunk drivers is conducive to improve the pertinence of traffic safety education.The data of 1 072 drunk drivers concerning four demographic variables, including age, gender, household registration, and educational level, is collected in a city within a one-year period.Afterwards, a log-linear model is developed to analyse the data.The results show that: ① Drunk drivers have significant differences on all the four variables;the male, the elder, the non-local, and the highly educated drivers are more likely to be involved in drunk driving.It finds that the non-local are more involved in drunk driving than the local, which is contrary to current studies and intuitive feelings.Therefore, the local have higher safety awareness than the non-local when it comes to drunk driving;② The interaction effects between two of the four variables are significant (p<0.01);the interaction effects between gender and age, gender and household registration are positive, while the other interaction effects are negative.Educational level adjusts the impacts of age, gender, and household registration.Age adjusts impacts of household registration on drink driving.The adjustment can explain the cause of drunk driving to a certain extent.Finally, based on this study, counter-measures about how to improve traffic safety education on drunk driving are discussed.
Transportation Information Engineering and Control
An Approach of Extracting Information for Maritime Unstructured Text Based on Rules
YU Chen, MAO Zhe, GAO Song
2017, 35(2): 40-47. doi: 10.3963/j.issn.1674-4861.2017.02.007
Abstract(363) PDF(2)
Abstract:
Structural processing of maritime data plays an important role in maritime safety.There is a plenty of maritime related information on internet.However, most of the information is unstructured data which has different formats.An approach of extracting maritime information and converting unstructured text into structural data is proposed in this paper.Web crawlers are used to obtain the text data from maritime-related Web pages.According to the definitions of the texts, they are divided into four items, which are time, location, vessel name, and type of accident.According to the extraction process and its common trigger words, the maritime lexicon for segmentation of Chinese words and part-of-speech tagging is constructed.Relying on an analysis of a large number of accident corpuses, the rules for extraction of information are summarized.The structured maritime data is then formulated.In order to verify the feasibility of this approach in term of extracting information based on rules, the data from the website of The Yangtze river maritime bureau is applied as a case study.The results indicate that the precision of extracting time information is 100%, with the recall rate of 91%.The precision of extracting location information is 94.52%, with the recall rate of 69%.The precision of extracting vessel name information is 97.75%, with the recall rate of 86%.The precision of extracting accident type information is 96.6%, with the recall rate of 87%.
Development of an Automatic Control System for Delivery and Recovery of Road Cones
HUANG Zhen, SHU Xin, TANG Wenlong, XIANG Yanhua, LI Xiaowei
2017, 35(2): 48-58. doi: 10.3963/j.issn.1674-4861.2017.02.008
Abstract(211) PDF(3)
Abstract:
In order to meet the growing need of rapid isolation, warning and protection in traffic accident scene on expressways, a new design scheme of automatic control system for the delivery and recovery of road cones is developed.In view of the disadvantages of traditional delivery and recovery devices of road cones including high cost and complex structure, virtual prototype technology is used to carry out a new design of mechanical structure of a automatic integration device that can compactly and deliver and recover road cones, including superposition, picking, transfer, placement, and other institutions.Then, simulation tests are launched on the platforms of Pro/E, ADMAS, etc.An overall design scheme of embedded system based on ARM is proposed with uCOS-II operating system as the platform, and the STM32 Series MCU as the CPU.Hardware and software of the controller are designed.The control strategy of "S" type is used to achieve the smooth control of the motor.Based on Android platform, an convenient operation and friendly man-machine interface is developed, which uses "Bluetooth" as the communication bridge between the upper and lower computer, and RSA algorithm is used to ensure the security of data exchange.The test results show that the success rate of delivery and recovery of road cones is 95%, which basically meets the requirements.However, there is a great difference of the success rate (6%) between high and low speed when placing and recycling road cones.In addition, the lodging rate of road cones reaches to 5%, and the single index can't meet the design requirements.
A Pothole Detection System and Method Based on Mobile Sensing Techniques
CHEN Zhihua, LIN Chunhao, LUO Jiqun
2017, 35(2): 59-67. doi: 10.3963/j.issn.1674-4861.2017.02.009
Abstract(185) PDF(3)
Abstract:
A real-time pothole detection approach is proposed based on mobile sensing and cloud computing.The Euler angles are used to normalize the accelerometer data of mobile device.A pothole detection algorithm is applied to find pothole, and the spatial interpolation method is used to improve accuracy of global positioning system (GPS).The pothole information is sent to a cloud server.Finally, the pothole information can be transferred to user's mobile device in real time, and augmented reality (AR) navigation service is combined in the mobile device for pothole avoidance.According to practical experiments, the results indicate that this proposed method for pothole detection based on mobile sensing techniques can precisely detect potholes without any false-positives.
A Prediction Model for Short-term Traffic Flow Based on Space-time GPSO-SVM
MEI Duo, ZHENG Lili, LENG Qiangkui, E Xu
2017, 35(2): 68-74,120. doi: 10.3963/j.issn.1674-4861.2017.02.010
Abstract(96) PDF(2)
Abstract:
In order to improve accuracy of short-term forecasting of traffic flow on urban roads, a model is proposed by space-time genetic-particle swarm optimization (GPSO) and support vector machine (SVM).The spatial-temporal correlation of original traffic flow of a road network is analyzed based on a principal component analysis.Instead of original traffic flow, this paper takes less principal components as predictive factors.The crossover and mutation factors of a genetic algorithm are appiled into a particle swarm optimization algorithm, which can avoid local optimization.According to the improved particle swarm optimization algorithm, parameters of SVM model are optimized, then an optimal SVM model is developed, as well as forecasting of short-term traffic flow.A practical case study is taken based on the data of a road network in Changchun City.The results show that the GPSO algorithm does not fall into local optimum when the parameters of SVM model are optimized, and the effects of optimization is better;the relative error of this proposed model is stable compared with the particle swarm SVM model and GPSO-SVM model, and the average prediction accuracy is improved by 4.96% and 3.41%, respectively.
Establishment and Analysis of Equity Measure Index of Departure Flights
ZHAO Yifei, HUA Shanshan
2017, 35(2): 75-80. doi: 10.3963/j.issn.1674-4861.2017.02.011
Abstract(107) PDF(2)
Abstract:
Equity of departure flights is an important measurement of sustainable operations in civil aviation.However studies on it are relatively rare compared with flight efficiency.In order to more intuitively measure the degree of difference in delays of departure flights, taking equity value of departure flights of different airliners as object, the concept of equity of departure flights is defined.On this basis, combined with a normalization algorithm, a normalization index is established to evaluate equity level of departure flights.The four main departure directions of Beijing Capital International Airport are taken as a case study to analyze the equity value of departure flights of different airliners.The results show that equity values of four directions obey Normal distribution.The greater the equity value is, the worse the stability becomes.Field investigation verifies that the equity value calculated by the index conforms with practical operations, which means practical.
Transportation Planning and Management
Effects of Dividing Methods for Traffic Analysis Zones on Distribution of Road Network Flow
JIANG Menglu, SHAO Minhua, SUN Lijun
2017, 35(2): 81-88. doi: 10.3963/j.issn.1674-4861.2017.02.012
Abstract(141) PDF(4)
Abstract:
Different designing methods for Traffic Analysis Zones (TAZs) may lead to different forecasting results of traffic flow.It is important to select an appropriate dividing method to improve the precision of forecasting results.This paper takes arterials of Madrid, Spain as a case study to analyze the effects of different aggregation methods of TAZs.TransCAD software and a method of OD matrix estimations are adopted.Firstly, the effects of aggregating TAZs based on administrative districts and population distribution zones on forecasting results of distribution of road network flow are investigated.The number of TAZs is kept the same for different aggregation methods, namely the zonation effects on modifiable area unit.The results show that the dividing method for population distribution zones produces a result closer to the actual value.Then, the population distribution areas are further divided into three different degrees to compare the effects of number of TAZs on the forecasting result of road network flow, namely the scale effects on modifiable area unit.The results show that the accuracy is improved when the number of TAZs is increased.By incorporating population distribution or other traffic-geographic information into TAZs dividing, traffic flow of future years could be better predicted, and the smaller the TAZs are divided, the closer the prediction results would approach the actual situations.
A Game Analysis Between Carsharing and Private Cars Based on Evolutionary Game Theory
WANG Jian, CHENG Yuan, ZHANG Zening
2017, 35(2): 89-93. doi: 10.3963/j.issn.1674-4861.2017.02.013
Abstract(243) PDF(2)
Abstract:
Carsharing can effectively relieve traffic congestion and pollution in cities.It is considered as an alternative trip mode to private cars, and has significant effects on choosing behaviors of travelers.Based on Evolutionary Game Theory, a game process of traveler's trip mode between carsharing and private cars is analyzed.Based on choosing behavior of travelers, an evolution game model is established.This model focuses on different features of trip mode by carsharing and private cars, service level of carsharing changes with number of travelers, and government participation in management.Stable conditions of equilibrium points are obtained under different model parameters based on dynamics.The analysis results of evolutionary stable state may provide support for promotion of carsharing and setting of government policy.
A Study on Level of Walking Service of Transfer Process in Passenger Transport Hubs
ZHOU Kan, WANG Lianzhen, PEI Yulong, WANG Bo
2017, 35(2): 94-99. doi: 10.3963/j.issn.1674-4861.2017.02.014
Abstract(116) PDF(2)
Abstract:
For evaluating rationality of transfer facilities in passenger transport hubs, a study focusing on level of walk service is carried out.At first, walk time is selected as an index to evaluate the level of walk service, which is divided into 5 levels.Then based on continuous category evaluation theory, a classification method to evaluate level of walk service in passenger hubs is developed.According to the survey data of "experience-response" of passengers, the criteria ranges of 5 levels of walk are given.The results indicate that passengers generally perceive 10 min walking is acceptable when transfer in hubs;however, 18 min or more will beyond their tolerance.The results of this study also demonstrate that the continuous category evaluation method is similar with the psychological evaluation process of passengers on the level of walk service.It is suitable for determination of thresholds for each level of walk service.
A Study on Localization of Project-level Parameters of MOVES Model in Shenzhen
CAO Yang, GUO Yuanyuan, CAO Gang, ZHU Rongshu
2017, 35(2): 100-108. doi: 10.3963/j.issn.1674-4861.2017.02.015
Abstract(260) PDF(17)
Abstract:
MOVES model is a model of vehicle emission factors established based on actual conditions of US.To simulate urban vehicle emissions in China, the parameters of MOVES model should to be corrected.In order to enable the MOVES model to correctly simulate characteristics of vehicle emission in Shenzhen, a study on localization of MOVES model is developed based on actual situations in Shenzhen.Project-level parameters including geographic information, vehicle type, fuel, and simulation year are localized.Under the premise that how to define related parameters in MOVES model are clear, the parameters are assigned values according to actual conditions of vehicles in Shenzhen.In addition, comparison and analysis of the relative errors are conducted between emission factors simulated by MOVES model before and after localization, and the ones obtained from on-board emission measurement.The results show that the simulation results of NOx from localized model are improved significantly;in which, the relative errors reduce from 365% to 14% in expressway.The relative errors of CO2 simulated by before and after localized MOVES models are both small, which is within 20% after localization.The relative errors of CO are reduced by 30~50% after localization.However for HC, the simulation results are negligible in all situations, there is a room for improvement.
An Optimization of Bus Timetable During Peak Periods Based on Forecasts Passenger Flow Using Neural Network
GU Jinjing, JIANG Zhibin
2017, 35(2): 109-114. doi: 10.3963/j.issn.1674-4861.2017.02.016
Abstract(182) PDF(1)
Abstract:
To enhance coordination between departure time and fluctuation of passenger flow demand, timetable of buses need to be optimized based on real-time passenger demand.Based on boarding data of passengers collected from IC card, sectional passenger flows can be predicted and calculated individually using BP neural network and RBF neural network.Based on prediction of traffic flows, the optimization decisions and an evaluation model are employed to design a dynamic optimization process of bus timetable.The data of passenger flows of bus lines in Wenshan city is used and analyzed.The results show that accuracy of sectional passenger flows from RBF neural network is higher than which of BP neural network.Comparing to the former timetable, the travel cost can be reduced by 4.11% and 1.35% based on the optimized timetable using RBF neural network and BP neural network, respectively.The operating costs of enterprises can be reduced 7.06% and 4.60%, respectively.The feasibility and effectiveness of the proposed dynamic optimization method is verified.
An Investigation and Analysis on Current Status of Carpool in Xi′an: A Case Study of Yanta District
GAO Lina, MA Lijuan, HOU Maosheng
2017, 35(2): 115-120. doi: 10.3963/j.issn.1674-4861.2017.02.017
Abstract(148) PDF(1)
Abstract:
A questionnaire investigation is carried out to study the current situation and influencing factors of carpool in Yanta District of Xi'an City.1 000 car owners and 1 000 passengers are chosen as the subjects of the investigation based on non-proportional stratified sampling method.The results show that the percentage of people who have already participated in carpool is only 2.7%.Although it is a low proportion, car owners and potential passengers have shown willingness to cooperate in the future and the foundation of such cooperation is ready.Influencing factors on carpool includes safety, extra time-consuming, economic conditions, age, gender, etc.Suggestions that may promote carpool are given: ensure safety of carpoolers;enhance support for carpool;encourage commuters' carpool;use taxi stops as carpool waiting stops;and appropriate use of bus lanes.

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