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.

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.

Evaluating COVID-19’s impacts on Puerto Rican’s travel behaviors

The COVID-19 pandemic has completely disrupted and possibly permanently changed the way humans travel.In Puerto Rico,major travel restrictions to the island have persisted at different levels since March 2020,which heavily influenced residents’travel behaviors.However,it remains unclear about how big the impact is and how inequitable it might be.The goal of this study is to evaluate COVID-19’s impacts on Puerto Rican’s travel behaviors by analyzing travel flows from Puerto Rico to the contiguous US with a modified gravity model.The roles of socioeconomic factors regarding the Puerto Rican travelers and COVID-19 factors regarding the destination US states have been assessed.COVID-19 was a strong deterring factor of travel at the beginning of the pandemic and also in the winter of 2020,but it did not keep Puerto Ricans from traveling during the summer 2020 when most travel restrictions were lifted.We found that the elderly population of Puerto Rico,despite being more vulnerable to COVID-19,were much more likely to travel during the pandemic.We also found that,during the holiday season in 2020,some socioeconomically disadvantaged populations were more likely to be traveling,a direct contradiction to their travel flows the year prior.These findings shed light on about how disproportionately affected populations behavior changed from pre-pandemic to after the pandemic started.With the continuance of the pandemic,this information is extremely valuable for future planning with respect to emergency management,travel regulation,and social benefit.

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.

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.

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.

Research on Behavior on Travel Mode, Going to Metro Station at Ho Chi Minh City

This research presents an analysis of travel mode choice for trips to Ho Chi Minh City metro station. Research methods were inherited through a formula to calculate passenger traffic forecasts to predict passengers, going to the station. Based on the collected data of interviews, traffic surveys, and ＂Irwin ＆ Von Cube＂ function, forecast the proportion of travel mode, and use to go to the station and leaving from the station. The results of study are used for the purpose of calculating the size of the metro station parking lots and parking layout plan.

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.

考虑出行偏好的城市群交通方式选择行为影响因素研究

针对城市群旅客出行方式选择行为影响机理不够明晰的问题,开展旅客城市群交通方式选择行为影响因素研究.设计问卷对关中城市群内出行行为进显性偏好(Revealed Preference,RP)调查,并对调查数据的效度、信度进行检验,基于调查所得出行数据,采用梯度提升决策树(Gradient Boosting Decision Tree,GBDT)模型构建了考虑出行偏好的出行方式选择预测模型,并采用可解释机器学习框架SHapley Additive exPlanations(SHAP)模型对预测结果进行解析,所构建模型结合旅客实际决策逻辑将出行方式多元选择行为解构为多次二元选择行为,以增强模型的可解释性.研究结果表明:所构建考虑出行偏好的GBDT预测模型能有效预测旅客城市群出行方式选择行为;私家车与公共交通之间的二元选择行为,会受到小汽车拥有状况,旅客对方便性、安全性、快捷性、舒适性的偏好程度、家庭居住区位、出行距离的显著影响;高速巴士与铁路系统、普通铁路与高铁动车之间的二元选择行为,均会受到出行距离、旅客对舒适性、安全性、快捷性、准时性的偏好程度的显著影响;小汽车拥有状况、家庭居住区位会显著影响高速巴士与铁路系统的选择行为,收入状况会显著影响普通铁路与高铁动车的选择行为.研究成果可为决策者从旅客出行偏好的角度进行更加切实有效的决策提供参考.

Riding towards a sustainable future:an evaluation of bike sharing’s environmental benefits in Xiamen Island,China

In the pursuit of sustainable urbanization,Bike-Sharing Services(BSS)emerge as a pivotal instrument for promoting green,low-carbon transit.While BSS is often commended for its environmental benefits,we offer a more nuanced analysis that elucidates previously neglected aspects.Through the Dominant Travel Distance Model(DTDM),we evaluate the potential of BSS to replace other transportation modes for specific journey based on travel distance.Utilizing multiscale geographically weighted regression(MGWR),we illuminate the relationship between BSS’s environmental benefits and built-environment attributes.The life cycle analysis(LCA)quantifies greenhouse gas(GHG)emissions from production to operation,providing a deeper understanding of BSS’s environmental benefits.Notably,our study focuses on Xiamen Island,a Chinese“Type Ⅱ large-sized city”(1–3 million population),contrasting with the predominantly studied“super large-sized cities”(over 10 million population).Our findings highlight:(1)A single BSS trip in Xiamen Island reduces GHG emissions by an average of 19.97 g CO_(2)-eq,accumulating monthly savings of 144.477 t CO_(2)-eq.(2)Areas in the southwest,northeast,and southeast of Xiamen Island,characterized by high population densities,register significant BSS environmental benefits.(3)At a global level,the stepwise regression model identifies five key built environment factors influencing BSS’s GHG mitigation.(4)Regionally,MGWR enhances model precision,indicating that these five factors function at diverse spatial scales,affecting BSS’s environmental benefits variably.

有限数据条件下智能体仿真模型构建方法

与传统的集计评估模型不同,智能体仿真模型能够捕捉个体之间的行为交互,在交通政策精细化评估中具有优势。但智能体仿真模型对数据要求较高,在实践中面临活动计划生成、参数标定和结果验证等难点。基于MATSim建立了在有限数据条件下面向应用研究的可操作、可复现的智能体仿真模型,并且以上海市拥堵收费评估场景为例详细介绍了模型的建模流程和关键技术。重点介绍基于手机轨迹数据的活动计划生成方法以及模型的参数标定和结果验证细节。结果表明,智能体仿真模型能够满足交通政策评估需求,基准场景的上海市域出行方式划分平均相对误差为8%、快速路交通量平均相对误差为17%。进而从集计和个体两个层面对仿真结果进行分析,展示了智能体仿真模型的应用潜力。

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。

考虑出行行为特征的停车供给决策方法

停车泊位有限供给会影响小汽车拥有者自驾车出行的积极性,促使部分小汽车拥有者改变出行方式,从而影响城市动态交通。本文通过梳理停车供给与出行行为的关系,提出考虑出行行为特征的停车供给决策思路和流程。停车供给水平的确定应充分结合停车区的功能定位、人群结构等掌握出行行为规律,通过停车泊位有限供给引导小汽车合理使用、减轻道路交通压力,促进城市交通可持续发展。研究成果以期为城市停车供给规划与管理提供决策参考。

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。

Transportation mobility during COVID-19:a systematic review and bibliometric analysis

The COVID-19 pandemic has significantly affected global transportation mobility,presenting unprecedented challenges to transportation management.Public transit and ride-hailing services saw a drastic reduction in ridership,leading to an increased inclination towards private vehicles.The pandemic also altered travel patterns and individual mobility due to various COVID-19 protocols.This study conducted a comprehensive review of 96 academic papers spanning from January 1,2020,to December 31,2022,focusing on transportation and mobility using the Scopus database.Three major themes were identified:‘Impact on Ride-Hailing Services',‘Impact on Mode Preference',and‘Impact on Trip Purpose',with subdivisions based on keywords and key findings extracted using VOSviewer.The pandemic significantly impacted ride-hailing services,altering demand,usage,and safety measures.Mode preference shifted towards private vehicles due to safety concerns.The present study underscores the long-term implications of the pandemic,emphasizing recovery strategies for ride-hailing services and mode preferences post-pandemic.It highlights the need for sustainable transportation policies,advocating for enhanced public transportation systems,promoting active travel modes,and addressing socioeconomic disparities in mobility patterns.The findings emphasize the need for resilient transportation strategies in the face of future disruptions.

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。

不同感知群体对自动驾驶汽车购买和使用意向的研究

为探讨L4级自动驾驶汽车(AV)的出行体验对受访者购买和使用意向的影响,受访者被分为体验感知较高和较低群体,在体验前和体验后,利用多项Logit模型建立不同体验感知群体AV购买和使用意向模型。研究结果显示,购买和使用AV的想法不确定程度对体验前、后的选择均产生显著影响,对于体验感知较高群体,体验后该变量的影响程度有所下降,而对于体验感知较低群体则有所增加。AV的价格与购买和使用意向之间呈现较强的正相关关系,价格的升高会增加购买和使用想法的不确定性,从而导致受访者放弃购买AV,选择使用社会共享自动驾驶汽车(SAV)。对于体验感知较高群体来说,体验后对AV行驶过程的感知提升会促进其购买并自己使用AV,而通过提高对AV出行感受和出行安全的感知,将促进他们购买AV并有偿共享给他人使用。另外影响体验感知较低群体对AV购买和使用意向的显著因素数量则明显减少。

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。