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urban traffic congestion in China:causes and countermeasures

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China Finance and Economic Review 2015年第2期4卷 47-59页

作者： Liu Zhiyan Yue Xiaoyan Zhao Rui Zhang Ying Institute for urban and Environmental Studies Chinese Academy of Social SciencesBeijingChina

Based on the analysis of the current situation and causes of urban traffic congestion in China,this paper points out that the rapidly rising gap between demand and supply in transportation,inappropriate urban space arrangement,and inefficient traffic management are the underlying causes of traffic *** on the advanced experience of foreign countries,this paper also offers suggestions for countermeasures against urban traffic congestion in China.

关键词： urban traffic traffic congestion countermeasures

The comprehensive measure model for urban traffic congestion based on value function

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Journal of Southeast University(English Edition) 2015年第2期31卷 272-275页

作者：胡启洲邓卫孙煦南京理工大学自动化学院南京210094 东南大学交通学院南京210096 清华大学交通研究所北京100084

According to the distribution characteristics of traffic congestion in time and space, a measure index system of urban traffic congestion is set up based on the spatial and temporal distribution. Based on the analysis of the main characteristics of traffic congestion and the generation process of traffic congestion, the measure model for urban traffic congestion is constructed by the value function. Moreover, based on the measure values of traffic congestion in urban road networks with defined different levels, a method to prevent and control traffic congestion is designed. The application results confirm that the proposed method is feasible in comprehensive measures for urban traffic congestion and they are consistent with the results of other methods. The measuring results can therefore reflect the actual situation. The comprehensive measure model is scientific and the process is simple, and it has wide application prospects and practical value.

关键词： urban traffic congestion measure matrix valuefunction

urban traffic Lane Saturation Prediction with Least Square Support Vector Regression based on Genetic Algorithm

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Urban Traffic Lane Saturation Prediction with Least Square S...

Green Innovation for urban traffic

第30届中国控制与决策会议

作者： Langwen Zhang Xiaofeng Yang Wei Xie College of Automation Science and Technology South China University of Technology Guangzhou Institute of Standardization

In this paper, urban traffic lane saturation prediction model is built with Least Square Support Vector Regression（LSSVR） based on Genetic Algorithm（GA）. The traffic data is collected and the relationships among different road crosses are analyzed. The traffic data is preprocessed by correcting some unusual data with data filtering method. To construct the lane saturation prediction model, Principal component analysis（PCA） is adopted to select the appropriate input parameters. LSSVR method is then used to establish the lane saturation prediction model. The model parameters are optimized by using GA method. Finally, the real measured data is used to test the prediction model and the results show that the proposed model can forecast the lane saturation level effectively.

关键词： urban traffic Lane Saturation Prediction Least Square Support Vector Regression Genetic Algorithm

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Frontiers of Engineering Management 2015年第1期2卷 35-38页

作者： Yu Zhao Sheng-quan Wang Ke-chao Zhu School of Economics and Management Shanghai Institute of Technology

With the development of economy, the issue of urban traffic is becoming highlighted, the pollution of the urban traffic has become one of the main factors to in fluence environment. It faces the broader problem of achieving sustainable development of urban transportation at present. The current situation of urban traffic is analyzed through studying the existing articles at home and abroad in this paper; the problems such as green innovation of urban traffic are elaborated. In addition, this paper puts forward the relevant measures to promote the development of green innovation of the urban traffic.

关键词： urban traffic green innovation green transportation sustainable development

Simulation for urban traffic Based on Cellular Automaton

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Simulation for Urban Traffic Based on Cellular Automaton

Spatiotemporal Prediction of urban traffics Based on Deep GNN

Asian Simulation Conference/The 6th International conference on system Simulation and Scientific Computing

作者： GONG Xiaobo, LI Zhipeng, LIU Yuncai (Intelligent Transportation Research Center, Shanghai Jiaotong University, Shanghai, 200030)

A cellular automaton model with high computing performance is proposed for signalized street of urban traffic. In our CA model, a suitable discretization scheme is adopted to fit the dynamics of urban traffic. And the rules that govern the dynamics of CA system are sorted into two classes, one class is the interactions between vehicles, the other one is the vehicle's response to traffic signal. The software architecture of the CA model is also presented. Validations are performed based on field survey that shows that the proposed simulation is capable of describing urban traffic in terms of average speed and suitable tor on-line simulation of large-scale traffic network.

关键词： Cellular automaton Simulation urban traffic

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Computers, Materials & Continua 2024年第1期78卷 265-282页

作者： Ming Luo Huili Dou Ning Zheng School of Computer Science Hangzhou Dianzi UniversityHangzhou310018China Zhejiang Institute of Communications Hangzhou310012China School of Cyberspace Security Hangzhou Dianzi UniversityHangzhou310018China

traffic prediction already plays a significant role in applications like traffic planning and urban management,but it is still difficult to capture the highly non-linear and complicated spatiotemporal correlations of traffic *** well as to fulfil both long-termand short-termprediction objectives,a better representation of the temporal dependency and global spatial correlation of traffic data is *** order to do this,the Spatiotemporal Graph Neural Network(S-GNN)is proposed in this research as amethod for traffic *** S-GNN simultaneously accepts various traffic data as inputs and investigates the non-linear correlations between the *** terms of modelling,the road network is initially represented as a spatiotemporal directed graph,with the features of the samples at the time step being captured by a convolution *** order to assign varying attention weights to various adjacent area nodes of the target node,the adjacent areas information of nodes in the road network is then aggregated using a graph *** data is output using a fully connected layer at the *** findings show that S-GNN can improve short-and long-term traffic prediction accuracy to a greater extent;in comparison to the control model,the RMSE of S-GNN is reduced by about 0.571 to 9.288 and the MAE(Mean Absolute Error)by about 0.314 to *** experimental results on two real datasets,Pe MSD7(M)and PEMS-BAY,also support this claim.

关键词： urban traffic traffic temporal correlation GNN prediction

Prediction of urban human mobility using large-scale taxi traces and its applications

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Frontiers of Computer Science 2012年第1期6卷 111-121页

作者： Xiaolong LI Gang PAN Zhaohui WU Guande QI Shijian LI Daqing ZHANG Wangsheng ZHANG Zonghui WANG Department of Computer Science Zhejiang UniversityHangzhou 310027China Institut TELECOM SudParis 91011 Evry CedexFrance

This paper investigates human mobility patterns in an urban taxi transportation system. This work focuses on predicting human mobility from discovering patterns of in the number of passenger pick-ups quantity （PUQ） from urban hotspots. This paper proposes an improved ARIMA based prediction method to forecast the spatial-temporal variation of passengers in a hotspot. Evaluation with a large-scale real- world data set of 4 000 taxis＇ GPS traces over one year shows a prediction error of only 5.8%. We also explore the applica- tion of the pl^di^fioti approach to help drivers find their next passetlgerS, The sinatllation results using historical real-world data demonstrate that, with our guidance, drivers can reduce the time taken and distance travelled, to find their next pas- senger＋ by 37.1% and 6.4% respectively,

关键词： urban traffic GPS traces hotspots human mo-bility prediction auto-regressive integrated moving average(ARiMA)

urban underground logistics system in China:Opportunities or challenges?

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Underground Space 2017年第3期2卷 195-208页

作者： Zhilong Chen Jianjun Dong Rui Ren College of Defense Engineering The Army Engineering University of PLANo.88 Hou Biaoying RoadNanjingChina College of Civil Engineering Nanjing Tech UniversityNo.30 Puzhu South RoadNanjingChina

An urban underground logistics system(ULS)is one important means of solving urban traffic problems that has unique *** transportation in China requires a new transportation ***,ULS has garnered increasing ***,to date,few scholars and practitioners have investigated ULS in *** ULS shows good development opportunities,it also faces great *** on the Macro-environment and situation analysis(PEST-SWOT)model,which is a strategic analysis method that combines both SWOT and PEST to effectively identify advantages,disadvantages,opportunities and threats,this paper first uses PEST to analyze the macro-environment of ULS in China and identify its internal factors(i.e.,advantages and disadvantages)and external factors(i.e.,opportunities and threats).Next,based on the SWOT framework,this paper proposes several development strategies and recommendations that provide a comprehensive and novel perspective to the study of ULS in China.

关键词： Underground logistics system(ULS) PEST-SWOT model Logistics industry urban traffic

The Park-and-Ride Behavior in a Cumulative Prospect Theory-Based Model

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Journal of the Operations Research Society of China 2017年第3期5卷 363-376页

作者： Li-Jun Tian Cheng-Rui Lyu Yong-Xiang Zhao School of Economics and Management Fuzhou UniversityFuzhou 350116China

As an effective travel demand management means,park-and-ride(P&R)mode is an important part of urban *** a traffic corridor with P&R service,suppose that the travel time on highway is uncertain,a cumulative prospect theory(CPT)-based travel decision-making model is established with two travel modes of driving all the way and(P&R).With this setting,the effect of various factors such as the transit fare rate,the parking fee and the total travel demand on the CPT-based and expected utility theory(EUT)-based equilibrium results are *** addition,the sensitivity analysis focus on CPT-related parameters are also *** numerical results in our case show that the equilibrium flow on P&R mode is always underestimated in an EUT-based model,especially for a low total travel ***,it is found that reducing the transit fare rate or parking fee for P&R station and raising the parking fee for CBD has the same effect on promoting more commuters transfer to P&R mode,whatever CPT-based or EUT-based model is ***,commuter’s reference dependence characteristic is also observed in a CPT-based model,and it is especially noticeable when the road uncertainty is large.

关键词： urban traffic Park-and-ride Cumulative prospect theory Commute behavior Equilibrium model