Consumers' Travel Behavior to Shopping Centers

Based on the questionnaire data,this study analyzes the characteristics of Wuhu citizens' travel behavior in shopping centers.The following conclusions are drawn:(1)the frequency of trips to shopping centers has a great correlation with consumersJ economic level and social status;(2)the time spent to purchase goods is positively correlated with the level of goods;(3)multipurpose shopping becomes the mainstream;(4)traffic becomes the primary factor for consumers to consider;(5)the availability of supermarkets and cinemas at shopping centers affect consumers'choice of shopping centers.

Residents′Activity-travel Behavior Variation by Communities in Beijing,China

China's transition from a planned economy to a market economy has resulted in many changes in its urban structure and society and provided an opportunity for a quasi-longitudinal case study on the relationship between the built environment and activity-travel behavior.This paper draws upon data from an activity diary survey conducted in Beijing in 2007.The survey sample comprised 652 residents living in Danwei(work unit),commodity housing,and affordable housing neighborhoods.On the basis of the three-dimensional geo-visualization analysis of the space-time path and statistical multivariate regression models of daily travel and leisure time,it was found that both residential spatial factors and socio-demographics influence residents' daily behaviors.The findings show that Danwei residents have less daily travel time than those who live in commodity housing,but people living in affordable housing endure the longest travel time.Daily leisure time is associated more with individual attributes.We argue that although China's transition is currently gradual,the Danwei system may continue to play significant roles in daily life,and it might provide a valuable model for neighborhood spatial planning.

Evidence-based practices in sustainable travel behavior intervention: A knowledge graph-based systematic review

Sustainable travel behavior intervention is an essential strategy to promote the development of urban transportation.The interventions offer personalized strategies based on certain scenario and participants to promote its effectiveness over hard travel restrictions.However,personalized strategies may also bring about difficulties to identify the actual effect of the measures.Furthermore,based on current practice,to make full use of travel behavior interventions,it is necessary to construct a unified methodological evidencebased framework to assess the reliability and effectiveness of travel behavior intervention studies.In response to these issues,we applied evidence-based knowledge graph to the field of sustainable travel behavior interventions to help decision supporters design sustainable travel behavior interventions wisely and in turn avoid excessive use of hard travel restrictions.We introduced concept of evidence-based practice to conduct a systematic analysis concerning reliability and validity of current full volume empirical studies by dimensions of scenarios,types of interventions and targets.In addition,we took advantage of high extensivity and integrability of knowledge graph to organize evidence-based related elements.Result of the systematic analysis shows that in terms of reliability of evidence,school intervention is the best scenario,knowledge incentive is the best intervention type and promoting public transit and walking proportion are the best targets.Oppositely,the reliability of interventions in workplace,belonging to reward and threat along with aiming at changing travel patterns generally and lowering travel carbon emission need to be enhanced.From the study,various research prospects are raised to promote evidence quality in the field of travel behavior intervention implementation.As a pioneer study,our research contributes to the field of urban transportation in introducing concepts of evidence-based practice and enabling optimization and extension of our achievement via the usage of knowledge graph,enhancing reliability and objectivity in urban transportation decision-making.

Understanding travel behavior adjustment under COVID-19

The outbreak and spreading of the COVID-19 pandemic have had a significant impact on transportation system.By analyzing the impact of the pandemic on the transportation system,the impact of the pandemic on the social economy can be reflected to a certain extent,and the effect of anti-pandemic policy implementation can also be evaluated.In addition,the analysis results are expected to provide support for policy optimization.Currently,most of the relevant studies analyze the impact of the pandemic on the overall transportation system from the macro perspective,while few studies quantitatively analyze the impact of the pandemic on individual spatiotemporal travel behavior.Based on the license plate recognition(LPR)data,this paper analyzes the spatiotemporal travel patterns of travelers in each stage of the pandemic progress,quantifies the change of travelers'spatiotemporal behaviors,and analyzes the adjustment of travelers'behaviors under the influence of the pandemic.There are three different behavior adjustment strategies under the influence of the pandemic,and the behavior adjustment is related to the individual's past travel habits.The paper quantitatively assesses the impact of the COVID-19 pandemic on individual travel behavior.And the method proposed in this paper can be used to quantitatively assess the impact of any long-term emergency on individual micro travel behavior.

Travel Patterns and Street Networks: A Novel Visualization Methodology of City-Level Traffic Flows and Network Usability

Street Networks, knitted in the urban fabric, facilitate spatial movement and control the flow of urbanization. The interrelation between a city’s spatial network and how the residents travel over it has always been of high interest to scholars. Over the years, multifaceted visualization methods have emerged to better express this travel trend from small to large scale. This study proposes a novel approach to 1) visualize city-wide travel patterns with respect to the street network orientation and 2) analyze the discrepancies between travel patterns and streets to evaluate network usability. The visualizations adopt histograms and rose diagrams to provide several insights into network-wide traffic flows. The visualization of four New York City (NYC) boroughs including Queens, Brooklyn, Bronx, and Staten Island was generated for the daily traffic and the average hourly flows in the morning and evening rush hours. Then the contrasts between built-in street network topology and travel orientation were drawn to show where people travel over the network, travel demand, and finally which segments experience high or light traffic, revealing the true picture of network usability. The findings of the study provide an insight into the novel and innovative approach that can help better understand the travel behavior lucidly and assist policymakers in decision making to maintain a balance between urban topology and travel demands. In addition, the study demonstrates how to further investigate city street networks and urbanization from different diverse dimensions.

A RESEARCH ON URBAN RECREATIONISTS' TRAVELING BEHAVIORS IN SHANGHAI

Urban recreationists consist of those who have used urban recreational facilities, no matter they are local residents or nonlocals. Traveling models will exert impacts not only on the use of urban recreational facilities but also on the development and management of recreational resources. Taking Shanghai as a sample of destinaton and origin of urban recreationists, the author did his study based on data from comprehensive travel measurement and users' survey, including field questionnaire survey, mailing questionnaire survey, home survey, and cordon monitonng. To analyze traveing models of urban recreationists in Shanghai, the author used techniques of Recreational Activity Space (RAS) and the Use Curve (UC) Analysis. Rogarding Shanghai as an origin, the author first discussed types and characteristics of the RASs which are presented by isotourist lines in the proper and outskirts of Shanghai, the Yangtze Delta and the China's Mainland respectively. These RASs reflect the trave directional bias of Shanghainese. Then the author regarded Shanghai as a deshnahon and analyzed the RASs of tounsts from Otier provinces, which demonstrated the attractiveness of and distance decay of Shanghai. He found that a U-shaped UC model existed in the distance decay under the influence of attractiveness and distance. Finally, the author suggested, that the availability, periodicity and attractiveness, besides distance, are the basic mechanisms that affect the urban recreationists' traveling models in a city such as Shanghai.

Study of Work-Travel Related Behavior Using Principal Component Analysis

The main objective of this study is to analyze work travel-related behavior through a set of variables relative to socio-economic class, urban environment and travel characteristics. The Principal Component Analysis was applied in a sample consisting of workers of the S?o Paulo Metropolitan Area, based on the origin-destination home interview survey, carried out in 1997, in order to: 1) examine the interdependence between travel patterns and a set of socioeconomic and urban environment variables;2) determine if the original database can be synthetized on components. The results enabled to observe relations between the individual’s socio-economic class and car usage, characteristics of urban environment and destination choices, as well as age and non-motorized travel mode choice. It is then concluded that the database can be adequately summarized in three components for subsequent analysis: 1) urban environment;2) socio-economic class;and 3) family structure.

Dynamical behaviors of traveling wave solutions to a Fujimoto-Watanabe equation

We study dynamical behaviors of traveling wave solutions to a Fujimoto-Watanabe equation using the method of dynamical systems. We obtain all possible bifurcations of phase portraits of the system in different regions of the threedimensional parameter space. Then we show the required conditions to guarantee the existence of traveling wave solutions including solitary wave solutions, periodic wave solutions, kink-like（antikink-like） wave solutions, and compactons. Moreover, we present exact expressions and simulations of these traveling wave solutions. The dynamical behaviors of these new traveling wave solutions will greatly enrich the previews results and further help us understand the physical structures and analyze the propagation of nonlinear waves.

基于出行链的铁路车站开通初期客流预测研究

【目的】为解决铁路车站开通初期客流预测缺乏数据支撑,以及估计不同交通方式成本来计算客流转移量结果与实际偏差较大的问题。【方法】以新开通南沿江城际铁路江阴站为例,考虑该线与既有高速及城际铁路的线位关系,基于城际出行链,依托旅客出行行为调查对区域内可选择的不同交通方式的城际出行效用进行定量计算,采用Multinominal Logit(MNL)模型,区分工作日与非工作日,结合客流分配现状对效用变量系数进行标定,据此预测南沿江城际铁路江阴站开通后发往南京、上海枢纽的客流量,同时结合城市经济和社会发展推演计算发往沿线其他站点的客流。【结果】结果表明,南沿江城际铁路江阴站的开通可以有效吸引江阴地区原本选择既有铁路、公路去往南京、上海的客流以及选择公路去往南沿江城际铁路沿线其他城市的客流。【结论】因此,南沿江城际铁路的开通能有效缓解辐射范围内既有铁路、公路的运输压力,客流预测结果还将支撑站点运力资源配置优化研究。

考虑低碳出行意愿的地铁公交接驳满意度分析

现如今,城市地铁建设规模日益增大,公交作为最常见的接驳方式,接驳满意度直接影响着居民的出行体验。文章通过问卷调查分析城市居民低碳出行的意愿和对地铁与公交接驳的满意度,在处理问卷数据后,对量表进行信效度检验,并对变量进行相关性分析。结果表明:绝大部分居民倾向于使用低排放的交通方式出行,当小汽车拥有数量越多,居民对当前低碳出行的接受意愿和环境满意度、地铁公交接驳的满意度、接驳的需求程度和优化意愿均有所降低。

不确定环境下收费与信息对路径选择行为影响的实验研究

在不确定环境下考虑信息发布与拥挤收费两种措施,基于交通网络均衡,推导了两路径简单路网的最优收费模型,并推广至一般路网。基于两路径路网设计逐日路径选择行为实验,分析了两种措施对路径选择行为的影响。结果表明:完美信息与收费的实施均能减少流量波动,单独实施收费的效果最佳,但只有两种措施相结合时,路网流量趋于用户均衡的趋势最稳定;完美信息会增加路径切换行为,而收费可有效抑制大幅的路径切换;无收费时路径切换往往会造成出行成本增加,而收费时则相反;收费与信息结合时的出行时间比两种措施单独实施时小。

交通需求管理的通勤福利效应——以“禁摩限电”为例

在市民个体层面,“禁摩限电”政策的实施效果尚缺乏定量评估。本研究将交通模式特征和土地利用特征整合到离散选择模型中,模拟计算了“禁摩限电”对市民通勤福利(模式转变和成本变化)的影响。研究发现,实施“禁摩限电”后:(1)超过35%的摩托车和电动自行车使用者转向小汽车出行。小汽车分担率由不足30%上升到50%以上;(2)弱势群体的福利损失高于其他群体。单程通勤的时间平均增加6.9min以上,经济成本平均增加0.5元以上。(3)郊区镇居民的单程通勤时间和经济成本分别比其他区域市民多增加20%和0.2元。城市中心周边市民的换乘次数和候车时间增加明显。在我国实施公交优先发展战略,倡导绿色出行的背景下,本研究对于优化相关政策实施具有重要参考价值。

基于手机信令数据的小城市居民出行时空特征研究——以铜仁市为例

居民出行特征与交通设施建设、居民生活质量、疫情防控等密切相关,是城市规划领域研究的重要主题之一。当前居民出行特征研究主要集中于特大城市,对中小城市的研究相对较少。本文以贵州省铜仁市为例,基于2019年5月、2019年11月、2020年5月三个时段,61543902条铜仁市常住人口出行OD手机信令数据,对小城市居民出行的规模、时耗、距离、分布空间与网络特征进行研究。结果发现:一、小城市出行规模在一天中有3-4个高峰,大城市则仅有2个高峰,小城市高峰出行量占比在冬季更高;2020年初新冠疫情后,铜仁市人口密度较大的区县内部出行比例上升。二、铜仁市的区县内部每次出行平均时耗与人口规模之间有较强的正相关性。三、铜仁市每次出行距离分布在群体层面上服从幂律分布;且冬季的区县内长距离出行的次数衰减较快。四、小城市居民出行空间分布呈现明显的向心性,大城市向心性相对较弱。五、铜仁市城镇化率较高地区在出行网络中的重要程度在冬季往往上升。研究结论进一步认识了小城市居民出行特征,为交通规划和交通政策制定提供了参考。

手机信令数据在职住空间、出行行为和交通碳排放研究中的应用进展与前景

手机信令数据具有覆盖范围广、获取成本低、时空精度较高、稳定实时追踪等优势,能够有效识别大规模人群的空间活动和出行特征,已成为应用最广泛的交通大数据类型之一。文章在手机信令数据的分类和特征基础上,总结了其在职住空间关系和交通出行行为研究中的技术应用,随后结合上述应用成果和已有文献对其在交通碳排放研究中的应用潜力和场景进行了探讨,最后总结了手机信令数据在职住空间、出行行为和交通碳排放研究中的应用框架、应用机遇与挑战以及未来研究内容与技术创新方向。目前,手机信令数据在职住空间领域中的应用包括职住地识别、职住关系和通勤网络特征及其影响因素解析,在出行行为领域中的应用包括驻留-出行识别、出行方式和路径识别,以及人群移动普适规律解析。以上技术应用能够有效服务交通碳排放领域研究,为交通碳排放测算以及城市空间结构、居民出行行为对交通碳排放的影响研究奠定了基础。未来,相关研究应进一步关注长时序动态追踪、大范围对比分析以及人口和交通新现象研究,并注重多源数据的融合、传统方法与机器学习的结合以及数字孪生模型的构建。

计及出行行为调整的综合能源系统双层博弈优化策略

针对园区综合能源系统中各个主体的利益难以兼顾及新能源汽车出行计划临时变动会对系统运行带来不利影响的问题,提出了考虑车主出行行为调整的电热氢综合能源系统双层博弈优化运行策略。首先,建立以能源运营商(IESO)、负荷聚合商(ULA)和新能源汽车负荷聚合商(NEVLA)为主体的Stackelberg-Shapley双层博弈框架;其次,将双层博弈框架嵌入两阶段模型预测控制滚动调度模型中,并在第1阶段引入惩罚博弈机制,抑制车主按照个人意愿无序改变充电计划的行为;最后,联合沙丘猫优化算法与CPLEX求解器对博弈模型进行求解。仿真结果表明:所提策略与无惩罚博弈机制的滚动优化运行策略及考虑惩罚博弈机制的单断面优化运行策略对比,能源运营商的收益分别提高了4.43%、7.75%,负荷聚合商的剩余价值分别提高了6.48%、12.18%,电动汽车负荷调度成本分别减少了13.64%、4.43%,验证了所提策略具有更好的系统运行经济性。

旅游产品直播购物情境下消费者购买行为的前因及其影响机制

直播购物已成为一种新的消费模式,但目前缺乏对直播间消费者购买旅游产品的行为研究。基于刺激-机体-反应范式,文章采取质性研究方法,探讨旅游产品直播购物情境下消费者购买行为的前因及其影响机制。研究发现:1)除信息质量和主播信息源特性外,旅游产品的独特性和直播购物平台的类型、可信度及营销力亦是影响消费者购买行为的外部刺激;2)消费者对外部刺激的内在感知包括观看旅游产品直播时的沉浸状态、感知易用性和感知有用性,影响其对旅游产品直播购物的态度、观看意愿和购买行为;3)消费者是否会从直播间的“观望者”转变成“购买者”,受旅游消费者自身特质及其感知风险的影响。通过厘清各前因变量之间的关系,及其对直播间消费者购买旅游产品行为的影响机制,文章深化了对消费者购买行为的理解,并为旅游产品直播购物行业长效发展提供了理论支撑。

Rosenau方程的显式行波解及动力学行为

找到Rosenau方程的显式精确解十分困难,研究方法常采用数值离散求解技术.首先,采用李群分析法给出了Rosenau方程的对称群、约化常微分方程和群不变解;其次,构造了一种精确求解非线性偏微分方程的exp(-φ(ξ))展式法,利用此方法找到了Rosenau方程的显式行波解,分析了解的动力学行为;最后,所获得的显式行波解既证明了Rosenau方程显式精确解的存在性,又可用于验证数值解的精度、检验数值离散方案的优劣,为工程领域的实际应用提供理论依据和参考.

基于充电概率的区域电动汽车充电负荷预测

在“双碳”战略的引导下,我国电动汽车行业发展迅猛,但同时也给区域内电网的配置以及充电站的运营带来了挑战。为更准确地预测区域内电动汽车在不同时刻的充电负荷,提高现有研究的精细度,首先分析了上海市某一区域内电动汽车用户的出行行为和充电行为数据,考虑用户在一天内不同时段的充电概率,然后基于蒙特卡洛方法建立了区域电动汽车充电负荷预测模型。结果显示,该区域的电动汽车日均行驶里程高出私人乘用车37.5 km;不同电池型号的电动汽车百公里耗电量差异较大;该区域内充电负荷存在明显的“三峰”现象,分别出现在7:00、14:00和22:00。最后,针对区域内公共充电站的供需情况,以实现资源最大化利用为目标,提出了优化区域电网配置、提高充电站利用率的针对性建议。基于蒙特卡洛方法提出的电动汽车充电负荷预测模型能丰富区域充电负荷预测方法,研究结果对电动汽车基础设施规划建设提供了参考。

差异化收费下货车空车出行选择行为研究

为制定高速公路货车空车差异化收费策略提供理论基础,解决高速公路货车由计重收费调整为车型收费导致货车空车分流的问题。本文构建基于逻辑回归模型和随机效用最大化理论的货车空车出行选择行为模型,以高速公路和平行老路构成的运输通道为例,分析货车空车在差异化收费场景下的出行选择行为及影响因素。研究结果表明,高速公路费率折扣率对各类货车空车出行选择影响最为显著,此外,车籍地对一类、四类货车空车出行选择影响较大,云南籍一类、外省籍四类货车空车在高速公路费率折扣率下倾向于继续走老路;运输类型对二类、三类和六类货车空车出行选择影响较大,跨省运输的二类和六类货车空车、省内运输的三类货车空车在高速公路费率折扣率下倾向于改变出行路径走高速公路。