Taking Guangzhou as a case,this paper adopted a questionnaire survey to gather first-hand data and analyzed the characteristics and influencing factors of private car travel in Chinese cities.As the research indicated...Taking Guangzhou as a case,this paper adopted a questionnaire survey to gather first-hand data and analyzed the characteristics and influencing factors of private car travel in Chinese cities.As the research indicated,trip purposes of private car travel are mainly commute and business affairs with a more flexible trip in the urban core area.And trip intensities are concentrated in a certain extent,with trip frequency being lower in the urban core area than the peripheral area.In addition,the trip time has two significant peaks occurring in the morning and afternoon,and one trough in the midday.And trip spatial distribution is mainly within commute with both residence and employment in urban area and inward commute with residence in suburban area while employment in urban area.Both kinds of commutes direct to the urban area.The study also shows that the characteristics of private car travel are principally influenced by two aspects:travelers' attributes and urban characteristics.The main travelers' social and economic attributes influenced it include the gender,education attainment,age,driving experience and per capita monthly household income.The urban characteristics influenced it mainly cover the land use pattern,public traffic facilities and spatial attributes of residential environment.展开更多
Bike sharing emerging from college campus in China's Mainland has become a major part in the daily traveling of Chinese urban residents.It changes the traveling behavior of urban residents,and simultaneously,raise...Bike sharing emerging from college campus in China's Mainland has become a major part in the daily traveling of Chinese urban residents.It changes the traveling behavior of urban residents,and simultaneously,raises higher requirements on urban transportation facility construction and management.However,the return of bike sharing to college campus causes more troubles to schools.The fundamental cause is the closed peculiarity of campus traveling comparing with city traveling,and also the discrepancy between college campuses of different types.This paper investigates the traveling characteristics of bike sharing in college campus in three different locations in Hangzhou City,Zhejiang Province of China in the questionnaire,and compares the discrepancy with urban bike sharing traveling characteristics and the discrepancy in bike sharing use between college campuses of different types.From the perspective of parking,maintenance and operation,and hardware design,the paper eventually raises suggestions to optimize independent college campus bike sharing service facility and management consistent with urban system.The research may also offer beneficial reference to the release of bike sharing facilities consistent with urban system in all sorts of independent parks,especially college campus.展开更多
The analysis of cutting regularity is provided through using and comparing two typical cooling liquids. It is proved that cutting regularity is greatly affected by cooling liquid＇s washing ability. Discharge characte...The analysis of cutting regularity is provided through using and comparing two typical cooling liquids. It is proved that cutting regularity is greatly affected by cooling liquid＇s washing ability. Discharge characteristics and theoretic analysis between two electrodes are also discussed based on discharge waveform. By using composite cooling liquid which has strong washing ability, the efficiency in the first stable cutting phase has reached more than 200 mm^2/min, and the roughness of the surface has reached Ra〈0.8 μm after the fourth cutting with more than 50 mm^2/min average cutting efficiency. It is pointed out that cutting situation of the wire cut electrical discharge machine with high wire traveling speed （HSWEDM） is better than the wire cut electrical discharge machine with low wire traveling speed （LSWEDM） in the condition of improving the cooling liquid washing ability. The machining indices of HSWEDM will be increased remarkably by using the composite cooling liquid.展开更多
In order to understand the travel characteristics and behavior patterns of women in Wangjing area and explore whether the existing situation can meet women's needs for the use of street space,the area around Wangj...In order to understand the travel characteristics and behavior patterns of women in Wangjing area and explore whether the existing situation can meet women's needs for the use of street space,the area around Wangjing South Station of Metro Line 14 was taken as an example for analysis and research.Wangjing area was classified to the following six use attributes:company enterprise,transportation hub,education and culture,residential area,municipal facilities,leisure and entertainment.The proportion of each use attribute was evaluated according to four levels:A 25%and above(including 25%),B 15%-25%,C 15%-5%,D 5%and below(including 5%).Finally,whether the plot had composite functions was judged,and the spatio-temporal laws and behavior patterns of surrounding women were analyzed from the perspectives of time and space.展开更多
Accurate and real-time passenger flow prediction of rail transit is an important part of intelligent transportation systems(ITS).According to previous studies,it is found that the prediction effect of a single model i...Accurate and real-time passenger flow prediction of rail transit is an important part of intelligent transportation systems(ITS).According to previous studies,it is found that the prediction effect of a single model is not good for datasets with large changes in passenger flow characteristics and the deep learning model with added influencing factors has better prediction accuracy.In order to provide persuasive passenger flow forecast data for ITS,a deep learning model considering the influencing factors is proposed in this paper.In view of the lack of objective analysis on the selection of influencing factors by predecessors,this paper uses analytic hierarchy processes(AHP)and one-way ANOVA analysis to scientifically select the factor of time characteristics,which classifies and gives weight to the hourly passenger flow through Duncan test.Then,combining the time weight,BILSTM based model considering the hourly travel characteristics factors is proposed.The model performance is verified through the inbound passenger flow of Ningbo rail transit.The proposed model is compared with many current mainstream deep learning algorithms,the effectiveness of the BILSTM model considering influencing factors is validated.Through comparison and analysis with various evaluation indicators and other deep learning models,the results show that the R2 score of the BILSTM model considering influencing factors reaches 0.968,and the MAE value of the BILSTM model without adding influencing factors decreases by 45.61%.展开更多
To relieve traffic congestion in urban rail transit stations,a new identification method of crowded passenger flow based on automatic fare collection data is proposed.First,passenger travel characteristics are analyze...To relieve traffic congestion in urban rail transit stations,a new identification method of crowded passenger flow based on automatic fare collection data is proposed.First,passenger travel characteristics are analyzed by observing the temporal distribution of inflow passengers each hour and the spatial distribution concerning cross-section passenger flow.Secondly,the identification method of crowded passenger flow is proposed to calculate the threshold via the probability density function fitted by Matlab and classify the early-warning situation based on the threshold obtained.Finally,a case study of Xinjiekou station is conducted to prove the validity and practicability of the proposed method.Compared to the traditional methods,the proposed comprehensive method can remove defects such as efficiency and delay.Furthermore,the proposed method is suitable for other rail transit companies equipped with automatic fare collection systems.展开更多
The incorporation of disruptive innovations into the transportation industry will inevitably cause major upheavals in the transportation sector.However,existing research lacks systematic theories and methodologies to ...The incorporation of disruptive innovations into the transportation industry will inevitably cause major upheavals in the transportation sector.However,existing research lacks systematic theories and methodologies to represent the underlying characteristics of future urban transport systems.Furthermore,emerging modes in urban mobility have not been sufficiently studied.The National Natural Science Foundation of China(NSFC)officially approved the Basic Science Center project titled“Future Urban Transport Management”in 2022.The project members include leading scientists and engineers from Beijing Jiaotong University,Beihang University,and Beijing Transport Institute.Based on a wide range of previous projects by the consortium on urban mobility and sustainable cities,this project will encompass transdisciplinary and interdisciplinary research to explore critical issues affecting future urban traffic management.It aims to develop fundamental theories and methods based on social and technological developments in the near future and explores innovative solutions to implement alongside these emerging developments in urban mobility.展开更多
基金Under the auspices of National Natural Science Foundation of China (No 40571052,40301014)
文摘Taking Guangzhou as a case,this paper adopted a questionnaire survey to gather first-hand data and analyzed the characteristics and influencing factors of private car travel in Chinese cities.As the research indicated,trip purposes of private car travel are mainly commute and business affairs with a more flexible trip in the urban core area.And trip intensities are concentrated in a certain extent,with trip frequency being lower in the urban core area than the peripheral area.In addition,the trip time has two significant peaks occurring in the morning and afternoon,and one trough in the midday.And trip spatial distribution is mainly within commute with both residence and employment in urban area and inward commute with residence in suburban area while employment in urban area.Both kinds of commutes direct to the urban area.The study also shows that the characteristics of private car travel are principally influenced by two aspects:travelers' attributes and urban characteristics.The main travelers' social and economic attributes influenced it include the gender,education attainment,age,driving experience and per capita monthly household income.The urban characteristics influenced it mainly cover the land use pattern,public traffic facilities and spatial attributes of residential environment.
基金This work was supported by the Natural Science Foundation of China(51608473)Shanghai philosophy and social science planning project(No.2017ECK004)+1 种基金2017 Zhejiang Provincial Department of Education General Research Project(Natural Science)(Y201738361)USST Innovation and Entrepreneurship Training Program(XJ2019132).
文摘Bike sharing emerging from college campus in China's Mainland has become a major part in the daily traveling of Chinese urban residents.It changes the traveling behavior of urban residents,and simultaneously,raises higher requirements on urban transportation facility construction and management.However,the return of bike sharing to college campus causes more troubles to schools.The fundamental cause is the closed peculiarity of campus traveling comparing with city traveling,and also the discrepancy between college campuses of different types.This paper investigates the traveling characteristics of bike sharing in college campus in three different locations in Hangzhou City,Zhejiang Province of China in the questionnaire,and compares the discrepancy with urban bike sharing traveling characteristics and the discrepancy in bike sharing use between college campuses of different types.From the perspective of parking,maintenance and operation,and hardware design,the paper eventually raises suggestions to optimize independent college campus bike sharing service facility and management consistent with urban system.The research may also offer beneficial reference to the release of bike sharing facilities consistent with urban system in all sorts of independent parks,especially college campus.
基金Provincial Key Laboratory of Precision and Micro-Manufacturing Technology of Jiangsu,China(No.Z0601-052-02).
文摘The analysis of cutting regularity is provided through using and comparing two typical cooling liquids. It is proved that cutting regularity is greatly affected by cooling liquid＇s washing ability. Discharge characteristics and theoretic analysis between two electrodes are also discussed based on discharge waveform. By using composite cooling liquid which has strong washing ability, the efficiency in the first stable cutting phase has reached more than 200 mm^2/min, and the roughness of the surface has reached Ra〈0.8 μm after the fourth cutting with more than 50 mm^2/min average cutting efficiency. It is pointed out that cutting situation of the wire cut electrical discharge machine with high wire traveling speed （HSWEDM） is better than the wire cut electrical discharge machine with low wire traveling speed （LSWEDM） in the condition of improving the cooling liquid washing ability. The machining indices of HSWEDM will be increased remarkably by using the composite cooling liquid.
基金Sponsored by 2022 Beijing Undergraduate Innovation and Entrepreneurship Training PlanConstruction of Demonstration Off-campus Practice Base for Integration of Industry and Education+1 种基金Beijing Municipal Education Commission Social Science Project(KM202010009002)“Young Yu You Talents Training Plan”of North China University of Technology。
文摘In order to understand the travel characteristics and behavior patterns of women in Wangjing area and explore whether the existing situation can meet women's needs for the use of street space,the area around Wangjing South Station of Metro Line 14 was taken as an example for analysis and research.Wangjing area was classified to the following six use attributes:company enterprise,transportation hub,education and culture,residential area,municipal facilities,leisure and entertainment.The proportion of each use attribute was evaluated according to four levels:A 25%and above(including 25%),B 15%-25%,C 15%-5%,D 5%and below(including 5%).Finally,whether the plot had composite functions was judged,and the spatio-temporal laws and behavior patterns of surrounding women were analyzed from the perspectives of time and space.
基金supported by the Program of Humanities and Social Science of Education Ministry of China(Grant No.20YJA630008)the Ningbo Natural Science Foundation of China(Grant No.202003N4142)+1 种基金the Natural Science Foundation of Zhejiang Province,China(Grant No.LY20G010004)the K.C.Wong Magna Fund in Ningbo University,China.
文摘Accurate and real-time passenger flow prediction of rail transit is an important part of intelligent transportation systems(ITS).According to previous studies,it is found that the prediction effect of a single model is not good for datasets with large changes in passenger flow characteristics and the deep learning model with added influencing factors has better prediction accuracy.In order to provide persuasive passenger flow forecast data for ITS,a deep learning model considering the influencing factors is proposed in this paper.In view of the lack of objective analysis on the selection of influencing factors by predecessors,this paper uses analytic hierarchy processes(AHP)and one-way ANOVA analysis to scientifically select the factor of time characteristics,which classifies and gives weight to the hourly passenger flow through Duncan test.Then,combining the time weight,BILSTM based model considering the hourly travel characteristics factors is proposed.The model performance is verified through the inbound passenger flow of Ningbo rail transit.The proposed model is compared with many current mainstream deep learning algorithms,the effectiveness of the BILSTM model considering influencing factors is validated.Through comparison and analysis with various evaluation indicators and other deep learning models,the results show that the R2 score of the BILSTM model considering influencing factors reaches 0.968,and the MAE value of the BILSTM model without adding influencing factors decreases by 45.61%.
基金The National Key Research and Development Program of China(No.2016YFE0206800)
文摘To relieve traffic congestion in urban rail transit stations,a new identification method of crowded passenger flow based on automatic fare collection data is proposed.First,passenger travel characteristics are analyzed by observing the temporal distribution of inflow passengers each hour and the spatial distribution concerning cross-section passenger flow.Secondly,the identification method of crowded passenger flow is proposed to calculate the threshold via the probability density function fitted by Matlab and classify the early-warning situation based on the threshold obtained.Finally,a case study of Xinjiekou station is conducted to prove the validity and practicability of the proposed method.Compared to the traditional methods,the proposed comprehensive method can remove defects such as efficiency and delay.Furthermore,the proposed method is suitable for other rail transit companies equipped with automatic fare collection systems.
基金This work was supported by the National Natural Science Foundation of China(Grant No.72288101).
文摘The incorporation of disruptive innovations into the transportation industry will inevitably cause major upheavals in the transportation sector.However,existing research lacks systematic theories and methodologies to represent the underlying characteristics of future urban transport systems.Furthermore,emerging modes in urban mobility have not been sufficiently studied.The National Natural Science Foundation of China(NSFC)officially approved the Basic Science Center project titled“Future Urban Transport Management”in 2022.The project members include leading scientists and engineers from Beijing Jiaotong University,Beihang University,and Beijing Transport Institute.Based on a wide range of previous projects by the consortium on urban mobility and sustainable cities,this project will encompass transdisciplinary and interdisciplinary research to explore critical issues affecting future urban traffic management.It aims to develop fundamental theories and methods based on social and technological developments in the near future and explores innovative solutions to implement alongside these emerging developments in urban mobility.
