Travel Behaviour and Society最新文献

{"title":"Inferring in-home/out-of-home situations unreported in time-use surveys using supervised machine learning","authors":"Shunsuke Arao,&nbsp;Takuya Maruyama","doi":"10.1016/j.tbs.2024.100928","DOIUrl":"10.1016/j.tbs.2024.100928","url":null,"abstract":"<div><div>Time-use surveys provide useful data for travel analyses. However, the survey on time use and leisure activities (TULA) Questionnaire A, a representative time-use survey in Japan, does not include questions related to the locations of activities, thus making it difficult to use for travel analyses. This study proposes machine-learning methods to determine the in-home/out-of-home situations of TULA Questionnaire A using TULA Questionnaire B with activity locations as the training data. Random forest performs better than logistic regression and decision trees in the inference. The activity was the most important factor in determining the in-home/out-of-home situations, followed by the accompanying person and time of day. The inferred outputs in the TULA Questionnaire A included the individual-based out-of-home rate profiles and the proportions of mobile persons from 1996 to 2016. Using these outputs, we analyzed trip misreporting in household travel surveys. Comparisons with nationwide and Tokyo person trip (PT) surveys implied soft refusals and trip misreporting in travel surveys. The comparison with the nationwide PT surveys suggested higher soft refusals on weekends than on weekdays. The comparison with the 1998, 2008, and 2018 Tokyo PT surveys implied the increased soft refusal in PT surveys, particularly among the male group aged between 20 and 39 and the female group aged between 35 and 49 during 1998–2018. These results suggest that careful handling of recent household travel survey data may be required. In addition, the proposed machine-learning-based method enables us to utilize the rich sample of Questionnaire A for activity-based travel analysis in future studies.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100928"},"PeriodicalIF":5.1,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Free interchange for better transit? Assessing the multi-dimensional impacts on metro to bus interchange behavior − insights from an explainable machine learning method","authors":"Tianqi Gu ,&nbsp;Kaihan Zhang ,&nbsp;Weiping Xu ,&nbsp;Chutian Zhuang ,&nbsp;Zhonghui Jiang ,&nbsp;Inhi Kim ,&nbsp;Hyungchul Chung","doi":"10.1016/j.tbs.2024.100923","DOIUrl":"10.1016/j.tbs.2024.100923","url":null,"abstract":"<div><div>This study investigates the impact of a newly implemented public transport interchange discount policy in Suzhou, China, focusing on its effects on metro-to-bus interchange behaviors across various spatial and temporal dimensions. Utilizing two distinct datasets spanning periods before and after the policy’s implementation, a comprehensive spatial–temporal analysis was conducted, covering weekdays, weekends, and holidays. A novel, real-time, distance-weighted methodology was developed to more accurately identify metro-to-bus interchange catchments, thereby refining the modeling scope. The study examines the interplay between land use, socio-demographic factors, and bus-related attributes—including a newly proposed operation-opportunity combined bus accessibility metric—using an explainable machine learning approach. Results indicate that the interchange discount policy has had an overall positive, though varied, impact on interchange behaviors, with the most pronounced effects observed during weekdays in central urban areas and at metro line bends. Specifically, 76.1 % of metro stations saw an increase in metro-to-bus interchange ratios on weekdays following the policy’s implementation, with increases observed at 66.4 % and 67.3 % of stations during weekends and holidays, respectively. Overall, the interchange ratio increased by 12.49 %, with a 17.45 % increase on weekdays. The analysis also reveals that factors such as bus accessibility, bus-to-bus interchange, and population density exhibit different effects depending on the time of week, with non-linear patterns emerging. The policy’s introduction shifted the impact thresholds for certain factors, initially triggering competition between bus and metro services but eventually leading to a synergistic rise in metro-to-bus transfers as bus-to-bus interchange ratios increased. Additionally, the policy altered the significance of population density, enhancing the attractiveness of multimodal interchange for users who previously favored other modes of transport.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100923"},"PeriodicalIF":5.1,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of weather-driven travel behavior on a small-scale docked bike-sharing system usage","authors":"Dila Guzel ,&nbsp;Oruc Altintasi ,&nbsp;Sila Ovgu Korkut","doi":"10.1016/j.tbs.2024.100927","DOIUrl":"10.1016/j.tbs.2024.100927","url":null,"abstract":"<div><div>Bike-sharing systems play a crucial role in encouraging sustainable transportation, and understanding their usage characteristics is essential for enhancing their contribution to urban mobility. This research seeks to investigate how weather conditions impact the utilization of a small-scale docked bike-sharing system. The study employed Generalized Linear Mixed Effects (GLME) models to analyze interactive events, using categorized weather parameters to represent various weather conditions. Several models were developed to comprehensively understand distinct travel behaviors and identify significant weather variables affecting the frequency of bike trips for transportation and leisure purposes. The findings reveal that rain had a significant deterrent effect on leisure cycling, particularly on weekdays. Cold and hot weather conditions exhibited a more pronounced impact on weekday bike trips, while weekend bike trips appeared to be less influenced by weather variables. The fall season was found to be the least favorable for leisure trips, while winter was determined to be the most unfavorable for transportation trips. Furthermore, hot days in the summer season negatively impacted bike usage only on weekdays. These insights have important implications for the development of a more resilient bike-sharing system, particularly in small-scale contexts. They provide valuable recommendations for tailored strategies to mitigate the impact of adverse weather conditions, thereby fostering an increase in usage of bike-sharing systems for both leisure and transportation purposes.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100927"},"PeriodicalIF":5.1,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Collecting population-representative bike-riding GPS data to understand bike-riding activity and patterns using smartphones and Bluetooth beacons","authors":"Debjit Bhowmick ,&nbsp;Danyang Dai ,&nbsp;Meead Saberi ,&nbsp;Trisalyn Nelson ,&nbsp;Mark Stevenson ,&nbsp;Sachith Seneviratne ,&nbsp;Kerry Nice ,&nbsp;Christopher Pettit ,&nbsp;Hai L. Vu ,&nbsp;Ben Beck","doi":"10.1016/j.tbs.2024.100919","DOIUrl":"10.1016/j.tbs.2024.100919","url":null,"abstract":"<div><div>Bike-riding GPS data offers detailed insights and individual-level mobility information which are critical for understanding bike-riding travel behaviour, enhancing transportation safety and equity, and developing models to estimate bike route choice and volumes at high spatio-temporal resolution. Yet, large-scale bicycling-specific GPS data collection studies are infrequent, with many existing studies lacking robust spatial and/or temporal coverage, or have been influenced by sampling biases leading to these data lacking representativeness. Additionally, accurately detecting bike-riding trips from continuously collected raw GPS data without human intervention remains a challenge. This study presents a novel GPS data collection approach by leveraging the combination of a smartphone application with a Bluetooth beacon attached to a participant’s bike. Aided by minimal heuristic post-processing, our method limits data collection to trips taken by bike without the need for participant intervention, carefully optimising between survey participation, privacy challenges, participant workload, and robust bike-riding trip detection. Our method is applied to collect 19,782 bike trips from 673 adults spanning eight months and three seasons in Greater Melbourne, Australia. The collected dataset is shown to represent the underlying adult bike-riding population in terms of demographics (sex, occupation and employment type), temporal and spatial patterns. The average trip length (median = 4.8 km), duration (median = 20.9 min), and frequency of bicycling trips (median = 2.7 trips/week) were greater among men, middle-aged and older adults. The ‘Interested but Concerned’ riders (classified using Geller typology) rode more frequently, while the ‘Strong and Fearless’ and ‘Enthused and Confident’ groups rode greater distances and for longer. Participants rode on roads/streets without bike infrastructure for more than half of their trips by distance, while spending 24% and 17% on off-road paths and bike lanes respectively. This population-representative dataset will be key in the context of urban planning and policymaking.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100919"},"PeriodicalIF":5.1,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The emergency accessibility analysis based on traffic big data and flood scenario simulation in the context of Shanghai hotel industry","authors":"Qian Yao ,&nbsp;Yong Shi ,&nbsp;Peng Yang ,&nbsp;Hai Li ,&nbsp;Jiahong Wen","doi":"10.1016/j.tbs.2024.100900","DOIUrl":"10.1016/j.tbs.2024.100900","url":null,"abstract":"<div><div>This paper presents a novel methodology for assessing emergency response capabilities in coastal cities in China amidst the challenges posed by global warming, rapid tourism industry growth, and increasing flood occurrences. Our approach integrates flood simulation, traffic big data, and web-based path navigation to evaluate the emergency response of the Fire &amp; Rescue Service (FRS) to tourist hotels in Shanghai. The empirical study highlights the significant impact of transportation conditions, hotel locations, flood inundation intensity, and urban FRS distribution on emergency response effectiveness. It further demonstrates that existing traffic conditions heavily influence flood-induced emergency accessibility, with severe congestion adversely affecting spatial accessibility. The study also reveals that flooding events and real-time traffic can cause delays in emergency responses by altering optimal routes. Consequently, selecting the most efficient routes becomes crucial for enhancing a city’s emergency response capabilities. The results validate the efficacy of our proposed approach, which holds significant promise for improving emergency response capabilities in urban tourism settings when faced with disasters.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100900"},"PeriodicalIF":5.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring collective activity space and its spatial heterogeneity using mobile phone signaling Data: A case of Shenzhen, China","authors":"Juan Li ,&nbsp;Pengjun Zhao ,&nbsp;Mengzhu Zhang ,&nbsp;Yiling Deng ,&nbsp;Qiyang Liu ,&nbsp;Yanzhe Cui ,&nbsp;Zhaoya Gong ,&nbsp;Juan Liu ,&nbsp;Wenchang Tan","doi":"10.1016/j.tbs.2024.100920","DOIUrl":"10.1016/j.tbs.2024.100920","url":null,"abstract":"<div><div>The planning ethos of providing proximity-based services to all inhabitants has been prevailing recently, and underlines the importance of knowing areal differences in collective activity space (AS) of populations. Mobile phone signaling data (MSD) has great potentials for this end, especially in mega-cities with fast changing and spatially varying demographic composition. However, two problems need to be addressed when applying MSD-based AS measurement for planning practices, including the identification of regularly visited locations and the selection of measure indices. This paper proposes a three-step workflow to apply the MSD to measure local collective AS with considering addressing the problems. This three-step workflow aims to illustrate the procedure of using MSD to measure collective AS for supporting planning practice in urban China, with clarifying some key concerns when doing so. We apply the workflow to examine the spatial heterogeneity of the collective AS in Shenzhen City and discuss the transferability of the workflow in different social and institutional contexts.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100920"},"PeriodicalIF":5.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Moderating effects of policy measures on intention to adopt autonomous vehicles: Evidence from China","authors":"Tianpei Tang ,&nbsp;Yuntao Guo ,&nbsp;Dustin J. Souders ,&nbsp;Xinghua Li ,&nbsp;Miaomiao Yang ,&nbsp;Xunqian Xu ,&nbsp;Xinwu Qian","doi":"10.1016/j.tbs.2024.100921","DOIUrl":"10.1016/j.tbs.2024.100921","url":null,"abstract":"<div><div>Autonomous vehicles (AVs) can potentially revolutionize the transportation system, but the extent of their impact may depend on users’ attitude and AV-related policies. This paper seeks to provide a holistic view of the impacts of policy, attitudinal, and sociodemographic factors on AV adoption intention. An extension to the original Technology Acceptance Model is proposed by incorporating perceived enjoyment (i.e., how enjoyable respondents think using an AV will be) and policy factors. Four policy factors include the availability of financial incentives, awareness campaigns, traffic policies, and legislative measures. Using 1,831 survey responses in China, multiple linear regression models were estimated to quantify the direct impacts of the proposed policy and attitudinal factors on AV adoption intention. They also illustrate the moderating effects of these policies on the relationships between attitudinal factors and AV adoption intention. The study findings may be used to design future policy measures to facilitate a smooth transition to an era of AVs.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100921"},"PeriodicalIF":5.1,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Examining senior citizens in public transport: The role of digitalization, environmental concern, and traveler satisfaction","authors":"Jonas Nilsson ,&nbsp;Johan Jansson ,&nbsp;Kimberly Nicholas ,&nbsp;Chunli Zhao","doi":"10.1016/j.tbs.2024.100924","DOIUrl":"10.1016/j.tbs.2024.100924","url":null,"abstract":"<div><div>Increasing the share of travelers using public transport is one way to address environmental problems such as carbon dioxide emissions. Senior citizens represent an increasingly important group in this transition, as they are increasingly mobile and make up a large share of the population. In this paper, we investigate senior citizen’s mobility decision-making, focusing on public transport. Through a survey of 5,000 people in three metropolitan areas in Sweden, we find that while senior citizens desire to live in harmony with nature, they are less likely to see car traffic as a cause of environmental problems. They also struggle with the development of digital service delivery options of public transport. For instance, they use apps less, and like using timetables on paper and signs at bus stops more than younger public transport users. Even so, they are more satisfied with public transport than younger travelers, indicating that many seniors like using public transport, despite lacking the environmental motivations to do so.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100924"},"PeriodicalIF":5.1,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of attitude, behaviour and opinion of e-scooter and e-bike riders on collision risk in Singapore","authors":"Raunaq Nayar ,&nbsp;Milan Paudel ,&nbsp;Fook Fah Yap ,&nbsp;Hong Xu ,&nbsp;Yiik Diew Wong ,&nbsp;Feng Zhu","doi":"10.1016/j.tbs.2024.100918","DOIUrl":"10.1016/j.tbs.2024.100918","url":null,"abstract":"<div><div>Active Mobility Devices (AMDs) such as electric scooters (e-scooters) and electric bikes (e-bikes) are increasingly used on shared paths and Park Connector Networks (PCNs) in Singapore, leading to frequent interactions between AMD riders, pedestrians, and cyclists. To ensure safety, it is crucial to understand the factors associated with collision risk related to these AMDs. To gain insights into the riders’ perspectives on the risk-taking behaviours and attitudes towards safety and sharing paths, a survey was conducted with 369 e-bike and 133 e-scooter riders across Singapore. The collected data was analysed to identify critical features of behaviour, attitudes, and opinions of e-scooters/e-bikes riders and their impact on perceived collision risk. Logistic Regression was used to select the most important behavioural features linked to collision risk, and significance of each was quantified by using the odds ratios in the chosen model. The results reveal that e-bike riders who regularly brake hard to avoid obstacles and highly value capacity of e-bike to carry goods face an increase in collision risk by 49.1% and 43.48% respectively. Those preferring quieter AMDs face 33.31% lower collision risk. Additionally, e-bike riders advocating for more traffic enforcement or the importance of slowing down when overtaking pedestrians face 20.69% and 38.84% lower collision risk respectively. E-scooter riders who manoeuvre quickly to dodge collisions or prioritize passenger-carrying capacity encounter a 142.25% and 67.43% higher collision risk, respectively. Furthermore, e-scooter riders willing to bend rules when not causing inconvenience to others face an increase in collision risk by 123.00%. These outcomes offer significant insights for the design and regulation of active mobility to safeguard all road users in a multi-modal transport environment.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100918"},"PeriodicalIF":5.1,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A copula-based approach for multi-modal demand dependence modeling: Temporal correlation between demand of subway and bike-sharing","authors":"Yining Di ,&nbsp;Meng Xu ,&nbsp;Zheng Zhu ,&nbsp;Hai Yang","doi":"10.1016/j.tbs.2024.100908","DOIUrl":"10.1016/j.tbs.2024.100908","url":null,"abstract":"<div><div>As a representative mode of shared mobility, bike-sharing serves not only as a convenient way to conduct short-distance trips in urban areas, but also as a feeder mode to public transit, forming the Bike and Ride (BnR) system. Conducting management for such a hybrid multi-modal system faces various challenges, including the complex interactions between bike-sharing and other modes, highly dynamic passenger demand, and the difficulty of accessing direct transfer data. To overcome such difficulties, our study proposes a framework for assessing the dependency between the two usage modes. Firstly, a Dynamic-Time-Warping-based (DTW) method is utilized to determine the catchment area (CA) between the two modes, allowing the BnR-related tendency similarity under a given time scale to be considered. Then, the patterns of probabilistic dependence between travel demand of the two modes are obtained by a copula-based approach, which separates correlations under specific usage levels from single modal demands. A case study on the multi-modal system formed by docked bike-sharing and subway in New York is conducted to validate the proposed framework. The tendency similarity is found to be most pronounced within 500 m on average under a 4-hour interval. For each formed station group (SG), the best-fitted copula type is selected, capturing the strong tail correlations present only at specific usage levels. The results show a variety of different correlation patterns within SGs, despite the close geographic locations they may share. Areas of potential transfer resistance between the two modes are identified, which is more evident in first-mile-related (FMR) activities. In contrast, the two modes display more weak connections in last-mile-related (LMR) activities. The obtained results can be utilized by bike-sharing service providers to analyze demand distributions and conduct efficient station-level rebalancing. Compared to previous methods, our proposed framework is computationally inexpensive since no direct transfer of data or complex inference network is required. It incorporates statistically significant spatial–temporal information, allowing for a more accurate determination of the bi-modal assessment range. Moreover, considering that single-mode influences are mathematically removed, the resulting correlation in principle links to the strength of the connections between the two modes. Therefore, it can be assessed as an indicator of the reliability of the multi-modal system.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100908"},"PeriodicalIF":5.1,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}