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基于多智体的自动驾驶汽车停车空载收费策略

浙江大学学报（工学版） 2024年第8期58卷 1659-1670页

作者：黎文皓季彦婕吴浩贾叶雯张水潮东南大学交通学院江苏南京211189 名古屋大学土木与环境工程系爱知县名古屋464-8603 安徽三联学院交通信息与安全重点实验室安徽合肥230601 宁波工程学院建筑与交通工程学院浙江宁波315211

为了制订自动驾驶车辆(AV)停车需求管理方案,搭建多智能体停车模拟框架,提出2种空载行驶收费策略:基于行驶距离的静态收费和基于道路拥堵水平的动态收费,研究费率计算方法.建立空载行驶收费策略下停车场停车、居住地停车及持续空载巡航... 详细信息

为了制订自动驾驶车辆(AV)停车需求管理方案,搭建多智能体停车模拟框架,提出2种空载行驶收费策略:基于行驶距离的静态收费和基于道路拥堵水平的动态收费,研究费率计算方法.建立空载行驶收费策略下停车场停车、居住地停车及持续空载巡航3种停车模式的成本函数,使用logit模型描述不同停车模式下的选择行为.利用Simulation of urban mobility(SUMO),以南宁市主城区为例开展大规模路网下的仿真实验,研究2种策略下的AV停车行为及路网运行状态变化.仿真结果表明,静态收费策略和动态收费策略下的AV空载行驶里程分别减少了20.16%和10.85%,车辆总延误分别降低了39.80%和43.52%;动态收费策略能够灵活地根据路况变化进行实时调整,路网运行效率提升更显著.

关键词：停车空载收费自动驾驶汽车多智能体模拟 SUMO

基于共享单车接驳的城市轨道交通站点可达性评估方法

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城市轨道交通研究 2024年第3期27卷 87-91页

作者：张豫徽曹钰季彦婕无锡市规划设计研究院无锡214071 天津市城市规划设计研究总院有限公司天津300190 东南大学交通学院南京211189

[目的]共享单车是一种有效的城市轨道交通(以下简称“城轨”)站点接驳方式,有必要建立基于共享单车接驳的城轨站点可达性测度模型,并对其进行评估。[方法]基于南京共享单车出行数据与城轨站点数据,对各站点的共享单车骑行时长、骑行距... 详细信息

[目的]共享单车是一种有效的城市轨道交通(以下简称“城轨”)站点接驳方式,有必要建立基于共享单车接驳的城轨站点可达性测度模型,并对其进行评估。[方法]基于南京共享单车出行数据与城轨站点数据,对各站点的共享单车骑行时长、骑行距离及接驳量进行了统计,选取骑行距离作为城轨站点可达性评价指标。对城轨站点可达性测度所需的可动性、易达性、通达性,以及站点规模影响因子等指标进行了计算,构建了基于共享单车接驳的城轨站点可达性测度模型。对南京市城轨站点进行了聚类分析,并对该站点进行了基于共享单车接驳的城轨站点可达性测度与评估。[结果及结论]在区域层面,站点可达性测度值呈现出在城市核心区普遍较高、近郊区分布范围广泛、远郊区普遍较低的规律;在站点类型层面,综合型站点的可达性测度值普遍较高,其次是办公导向型站点和居住导向型站点,职住偏移型站点和其他型站点的可达性测度值普遍较低。

关键词：城市轨道交通站点可达性评估方法共享单车接驳

Multidimensional Visualization of Bikeshare Travel Patterns Using a Visual Data Mining Technique: Data Cubes

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Journal of Beijing Institute of Technology 2019年第2期28卷 265-277页

作者： Xinwei Ma yanjie ji Yang Liu Yuchuan jin Chenyu Yi School of Transportation Southeast UniversityNanjing 210096China jiangsu Key Laboratory of Urban ITS Nanjing 210096China jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Nanjing 210096China

In order to explore the travel characteristics and space-time distribution of different groups of bikeshare users,an online analytical processing(OLAP)tool called data cube was used for treating and displaying multi-dimensional *** extended and modified the traditionally threedimensional data cube into four dimensions,which are space,date,time,and user,each with a user-specified hierarchy,and took transaction numbers and travel time as two quantitative *** results suggest that there are two obvious transaction peaks during the morning and afternoon rush hours on weekdays,while the volume at weekends has an approximate even *** weather condition significantly restricts the bikeshare ***,seamless smartcard users generally take a longer trip than exclusive smartcard users;and non-native users ride faster than native *** findings not only support the applicability and efficiency of data cube in the field of visualizing massive smartcard data,but also raise equity concerns among bikeshare users with different demographic backgrounds.

关键词： bikeshare smartcard data travel pattern multidimensional visualization

Support Vector Regression for Bus Travel Time Prediction Using Wavelet Transform

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Journal of Harbin Institute of Technology(New Series) 2019年第3期26卷 26-34页

作者： Yang Liu yanjie ji Keyu Chen Xinyi Qi School of Transportation Southeast University Nanjing 210096 China Guangzhou Urban Planning & Design Survey Research Institute Guangzhou 510060 China

In order to accurately predict bus travel time, a hybrid model based on combining wavelet transform technique with support vector regression(WT-SVR) model is employed. In this model, wavelet decomposition is used to extract important information of data at different levels and enhances the forecasting ability of the model. After wavelet transform different components are forecasted by their corresponding SVR predictors. The final prediction result is obtained by the summation of the predicted results for each component. The proposed hybrid model is examined by the data of bus route No.550 in Nanjing, China. The performance of WT-SVR model is evaluated by mean absolute error(MAE), mean absolute percent error(MAPE) and relative mean square error(RMSE), and also compared to regular SVR and ANN models. The results show that the prediction method based on wavelet transform and SVR has better tracking ability and dynamic behavior than regular SVR and ANN models. The forecasting performance is remarkably improved to obtain within 6% MAPE for testing section Ⅰ and 8% MAPE for testing section Ⅱ, which proves that the suggested approach is feasible and applicable in bus travel time prediction.

关键词： intelligent transportation bus travel time prediction wavelet transform support vector regression hybrid model

Exploring the Evolution of Passenger Flow and Travel Time Reliability with the Expanding Process of Metro System Using Smartcard Data

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Journal of Harbin Institute of Technology(New Series) 2019年第1期26卷 17-29页

作者： Xinwei Ma yanjie ji Yao Fan Chenyu Yi School of Transportation Southeast University

Metro system has experienced the global rapid rise over the past decades. However,few studies have paid attention to the evolution in system usage with the network expanding. The paper's main objectives are to analyze passenger flow characteristics and evaluate travel time reliability for the Nanjing Metro network by visualizing the smart card data of April 2014,April 2015 and April 2016. We performed visualization techniques and comparative analyses to examine the changes in system usage between before and after the system expansion. Specifically,workdays,holidays and weekends were specially segmented for *** showed that workdays had obvious morning and evening peak hours due to daily commuting,while no obvious peak hours existed in weekends and holidays and the daily traffic was evenly distributed. Besides,some metro stations had a serious directional imbalance,especially during the morning and evening peak hours of workdays. Serious unreliability occurred in morning peaks on workdays and the reliability of new lines was relatively low,meanwhile,new stations had negative effects on exiting stations in terms of reliability. Monitoring the evolution of system usage over years enables the identification of system performance and can serve as an input for improving the metro system quality.

关键词： metro expansion smart card data passenger flow characteristics travel time reliability visualization

Hsp90/C terminal Hsc70-interacting protein regulates the stability of Ikaros in acute myeloid leukemia cells

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Science China(Life Sciences) 2021年第9期64卷 1481-1490页

作者： Meng Liu jin jin yanjie ji Huizhuang Shan Zhihui Zou Yang Cao Li Yang Ligen Liu Li Zhou Hu Lei Yunzhao Wu Hanzhang Xu Yingli Wu Hongqiao International Institute of Medicine Shanghai Tongren Hospital/Faculty of Basic MedicineChemical Biology Division of Shanghai Universities E-InstitutesKey Laboratory of Cell Differentiation and Apoptosis of the Chinese Ministry of EducationShanghai Jiao Tong University School of MedicineShanghai 200025China Department of Ultrasound Second Affiliated Hospital of Zhejiang UniversityHangzhou 310009China Department of Hematology The Third Affiliated Hospital of Soochow UniversityChangzhou 213003China Shanghai Institute of Hematology State Key Laboratory of Medical GenomicsNational Research Center for Translational Medicine at ShanghaiRuijin Hospital affiliated to Shanghai Jiao Tong University School of MedicineShanghai 200025China

The stability of Ikaros family zinc finger protein 1(Ikaros),a critical hematopoietic transcription factor,can be regulated by cereblon(CRBN)ubiquitin ligase stimulated by immunomodulatory drugs in multiple ***,other stabilization mechanisms of Ikaros have yet to be *** this study,we show that the pharmacologic inhibition or knockdown of Hsp90 downregulates Ikaros in acute myeloid leukemia(AML)*** inhibitor MG132 but not autophagy inhibitor chloroquine could suppress the Hsp90 inhibitor STA-9090-induced reduction of Ikaros,which is accompanied with the increased ubiquitination of ***,Ikaros interacts with E3 ubiquitin-ligase C terminal Hsc70 binding protein(CHIP),which mediates the STA-9090-induced ubiquitination of *** addition,the knockdown of Ikaros effectively inhibits the proliferation of leukemia cells,but this phenomenon could be rescued by Ikaros ***,our findings indicate that the interplay between HSP90 and CHIP regulates the stability of Ikaros in AML cells,which provides a novel strategy for AML treatment through targeting the HSP90/Ikaros/CHIP axis.

关键词： Ikaros CHIP Hsp90 AML STA-9090

Analysis of temporal and spatial usage patterns of dockless bike sharing system around rail transit station area

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Journal of Southeast University(English Edition) 2019年第2期35卷 228-235页

作者： ji yanjie Cao Yu Liu Yang Ma Xinwei School of Transportation Southeast UniversityNanjing 211189China

In order to study the spatiotemporal characteristics of the dockless bike sharing system(BSS)around urban rail transit stations,new normalized calculation methods are proposed to explore the temporal and spatial usage patterns of the dockless BSS around rail transit stations by using 5-weekday dockless bike sharing trip data in Nanjing,***,the rail transit station area(RTSA)is defined by extracting shared bike trips with trip ends falling into the ***,the temporal and spatial decomposition methods are developed and two criterions are calculated,namely,normalized dynamic variation of bikes(NDVB)and normalized spatial distribution of trips(NSDT).Furthermore,the temporal and spatial usage patterns are clustered and the corresponding geographical distributions of shared bikes are *** results show that four temporal usage patterns and two spatial patterns of dockless BSS are finally *** type(urban center and suburb)has a great influence on temporal usage *** usage patterns are irregular and affected by limited directions,adjacent rail transit stations and street *** findings can help form a better understanding of dockless shared bike users behavior around rail transit stations,which will contribute to improving the service and efficiency of both rail transit and BSS.

关键词： dockless bike sharing system rail transit station usage pattern cluster

停车场内部泊车行为特性分析及最优泊位选择模型

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东南大学学报（自然科学版） 2009年第2期39卷 399-403页

作者：季彦婕王炜邓卫东南大学交通学院南京210096

在详细分析有无诱导条件下的停车场内部泊车行为异同的基础上,提出服务于车位引导系统的最优泊位选择模型.结合国内外微观泊车行为调查分析结果,确定了停车场内泊位选择过程中的主要影响因素,包括步行距离、行驶距离、安全性、遮荫时长... 详细信息

在详细分析有无诱导条件下的停车场内部泊车行为异同的基础上,提出服务于车位引导系统的最优泊位选择模型.结合国内外微观泊车行为调查分析结果,确定了停车场内泊位选择过程中的主要影响因素,包括步行距离、行驶距离、安全性、遮荫时长和有效泊位两侧车辆占用情况等.将各影响因素视为泊位的多项属性,建立了基于灰熵的最优泊位选择模型,对某一时刻停车场内所有的空余有效泊位进行排序,确定最优泊位.实例分析表明,该模型客观、简单、实用,有助于车位引导系统为停车者选择实时的最优泊位.

关键词：车位引导系统泊车行为特性最优泊位选择模型灰熵理论

Available parking space occupancy change characteristics and short-term forecasting model

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Journal of Southeast University(English Edition) 2007年第4期23卷 604-608页

作者：季彦婕王炜邓卫东南大学交通学院南京210096

Based on an available parking space occupancy （APSO） survey conducted in Nanjing, China, an APSO forecasting model is proposed. The APSO survey results indicate that the time series of APSO with different time-sections are periodical and self-similar, and the fluctuation of the APSO increases with the decrease in time-sections. Taking the short-time change behavior into account, an APSO forecasting model combined wavelet analysis and a weighted Markov chain is presented. In this model, an original APSO time series is first decomposed by wavelet analysis, and the results include low frequency signals representing the basic trends of APSO and several high frequency signals representing disturbances of the APSO. Then different Markov models are used to forecast the changes of low and high frequency signals, respectively. Finally, integrating the predicted results induces the final forecasted APSO. A case study verifies the applicability of the proposed model. The comparisons between measured and forecasted results show that the model is a competent model and its accuracy relies on real-time update of the APSO database.

关键词： available parking space occupancy change characteristics short-term forecasting wavelet analysis weighted Markov chain