Travel Behaviour and Society最新文献

{"title":"Latent class approach to classify e-scooter non-users: A comparative study of Helsinki and Tokyo","authors":"Samira Dibaj ,&nbsp;Hizaki Keiichi ,&nbsp;Rie Goto ,&nbsp;Ayako Taniguchi ,&nbsp;Miloš N. Mladenović","doi":"10.1016/j.tbs.2024.100941","DOIUrl":"10.1016/j.tbs.2024.100941","url":null,"abstract":"<div><div>Recent years have seen a rapid deployment of shared electric scooters (e-scooters), across hundreds of cities worldwide. Despite the global diffusion, most urban residents are still not using e-scooters, and they often bear the negative consequences of e- scooter deployment. This comparative study investigates the attitudes and characteristics of the e-scooter non-users in Helsinki, Finland and Tokyo, Japan using latent class clustering analysis. Our findings reveal five classes of e-scooter non-users, ranging from very negative perspectives to the least negative perspectives towards e-scooter deployment. Non-users also have a diverse set of socio-demographics background, including variation across age, gender, and income. In addition, non-users mostly do not feel the necessity of using an e-scooter as well as lack competences and have safety concerns. Safety concerns are dominant among those with more negative perceptions, while classes with the least negative perceptions and low income tend to not use e-scooters due to high rental costs. Understanding the different categories and perspectives of non-users, alongside with understanding users, has clear smart mobility policy and management implications. On the one hand, it should help with understanding the effectiveness of different interventions stemming from e-scooter operators and public policy actors. On the other hand, this study’s findings contribute to understanding public acceptability of e-scooter technology and associated policy and management actions. The study also opens further pathways for both comparative studies and for understanding different groups of users and non-users of smart mobility technologies.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"39 ","pages":"Article 100941"},"PeriodicalIF":5.1,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586851","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":"Q_EDQ: Efficient path planning in multimodal travel scenarios based on reinforcement learning","authors":"JianQiang Yan ,&nbsp;Yinxiang Li ,&nbsp;Yuan Gao ,&nbsp;BoTing Qu ,&nbsp;Jing Chen","doi":"10.1016/j.tbs.2024.100943","DOIUrl":"10.1016/j.tbs.2024.100943","url":null,"abstract":"<div><div>Recently, Mobility as a Service (MaaS) has garnered increasing attention by integrating various modes of transportation to provide users with a unified travel solution. However, In multimodal transportation planning, we primarily face three challenges: Firstly, a multimodal travel network is constructed that covers multiple travel modes and is highly scalable. Secondly, the routing algorithm fully considers the dynamic and real-time nature of the multimodal travel process. Finally, a generalized travel cost objective function is constructed that considers the psychological burden of transfers on passengers in multimodal travel scenarios. In this study, we firstly constructed an integrated multimodal transport network based on graph theory, which covers four transport modes, namely, the metro, the bus, the car-sharing and the walking. Subsequently, by introducing a double-Q learning mechanism and an optimized dynamic exploration strategy, we propose a new algorithm, Q_EDQ, the algorithm aims to learn the globally optimal path as efficiently as possible, with faster convergence speed and improved stability. Experiments utilizing real bus and metro data from Xi’an, Shaanxi Province, were conducted to compare the Q_EDQ algorithm with traditional genetic algorithms. In the conducted four experiments, compared to the optimal paths planned by traditional genetic algorithms, the improved Q-algorithm achieved a minimum efficiency increase of 12.52% and a maximum of 35%. These results demonstrate the enhanced capability of the improved Q-algorithm to learn globally optimal paths in complex multimodal transportation networks. Compared to the classical Q algorithm, the algorithmic model in this study shows an average performance improvement of 10% to 30% in global optimal path search, as well as convergence performance including loss and reward values.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"39 ","pages":"Article 100943"},"PeriodicalIF":5.1,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586982","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":"Analysis of emotions of online car-hailing drivers under different driving conditions and scenarios","authors":"Yongfeng Ma ,&nbsp;Yaqian Xing ,&nbsp;Ying Wu ,&nbsp;Shuyan Chen ,&nbsp;Fengxiang Qiao ,&nbsp;Xiaojian Hu ,&nbsp;Jian Lu","doi":"10.1016/j.tbs.2024.100937","DOIUrl":"10.1016/j.tbs.2024.100937","url":null,"abstract":"<div><div>Emotion is an important factor that affects driving behavior, and thus, drivers’ emotions are closely related to overall traffic safety. We investigated the emotional expressions of online car-hailing drivers under two driving conditions: with passenger(s) and without passenger(s). We recruited 16 male car-hailing drivers and collected a total of 91.5 h of data using non-contact equipment. We employed FaceReader 8.0 software to analyze the collected video data and extract the drivers’ facial expression information, thereby identifying six emotions expressed by the drivers. We then compared the frequency of the occurrence of the six emotions between the two conditions. The frequency rates indicate that the drivers exhibited more emotions when no passengers were in the vehicle. The chi-square test results indicate significant differences in the drivers’ emotions under the two conditions. For example, happiness is related to chatting with passengers. Also, the drivers exhibited more aggressive driving behavior during trips without passengers, and such behavior often was accompanied by negative emotions, such as anger. We also investigated drivers’ emotions under three scenarios that often occur while online car-hailing drivers are working: driver distractions, passenger interaction, and the traffic environment. The understanding of drivers’ emotions and the relationships between those emotions and scenarios that take place under different driving conditions can facilitate the identification of drivers’ intentions and provide guidance for the development of safe driving assistance warning systems. Dangerous driving behavior can be reduced through intervention and the monitoring of drivers’ emotions for the enhanced overall safety of roadway travel.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100937"},"PeriodicalIF":5.1,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571605","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":"Augmenting last-mile connectivity with multimodal transport: Do choice riders favor integrated bike taxi-bus service in metro cities?","authors":"Munavar Fairooz Cheranchery ,&nbsp;M.G. Karthika ,&nbsp;N. Firoz","doi":"10.1016/j.tbs.2024.100938","DOIUrl":"10.1016/j.tbs.2024.100938","url":null,"abstract":"<div><div>While the pursuit of sustainable measures to arrest private vehicle usage and externalities continues, poor last-mile connectivity remains a major deterrent for choice riders (car owners) considering the use of public transport. The present study proposes an integrated Bike Taxi-Bus Service (BTBS) system as a solution to last-mile connectivity concerns and investigates the perception of choice riders towards BTBS. The research was carried out in two Indian metro cities, tier 1 (Bangalore) and tier 2 (Kochi), where bike taxi and bus services operate independently, albeit without integration. The study investigates the perception of choice riders in two stages. Firstly, to identify key intervention areas for the development of an integrated BTBS system. Secondly, to develop econometric models for the estimation of choice riders’ Willingness to Pay (WTP) for BTBS attributes and their potential shift in demand towards BTBS. Additionally, a sensitivity analysis was conducted to explore the influence of various attributes on demand shift and to establish appropriate attribute levels to attract choice riders. While intervention areas are identified using Revised Importance Satisfaction Analysis (Revised ISA), Mixed Logit (ML) models are developed to estimate demand and WTP values. Unlike previous studies, intervention areas are identified using factor structure and management schemes. The study demonstrates the application of Revised ISA in attribute selection for econometric modelling. The work identified 50% of the listed attributes as intervention areas and notably higher WTP values of choice riders for BTBS attributes. This indicates the promise of BTBS while emphasizing the need for urgent attention.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100938"},"PeriodicalIF":5.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571604","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":"New insights into factors affecting the severity of autonomous vehicle crashes from two sources of AV incident records","authors":"Hanlong Fu ,&nbsp;Shi Ye ,&nbsp;Xiaowen Fu ,&nbsp;Tiantian Chen ,&nbsp;Jinhua Zhao","doi":"10.1016/j.tbs.2024.100934","DOIUrl":"10.1016/j.tbs.2024.100934","url":null,"abstract":"<div><div>Superior safety is the main banner value of promoting autonomous vehicle (AV) technology, but it is difficult to responsibly claim it. The potential for AVs to reduce crash and injury risks would be overshadowed by technological limitations, regardless of their ability to mitigate or eliminate human error. This study aims to identify the key factors affecting crash severity by analyzing real-world AV crash data from the U.S. between 2015 and 2022. We integrated two open data sources from the California DMV and NHTSA. Mixed multinomial logit models incorporating the interaction effects were estimated using the crash severity level, addressing the observed and unobserved heterogeneities. Our results show that Advanced Driver Assistance System (ADAS) engagement is associated with a higher likelihood of slight injury crashes, whereas Automated Driving System (ADS) engagements show the opposite effect. In addition, we found that various environmental and road factors, including lighting conditions, weather, road type, and road surface conditions, significantly affect the severity of AV crashes. For instance, daylight conditions contribute to a lower likelihood of slight-injury crashes. On the other hand, driving under unfavorable weather conditions (cloudy, foggy, rainy, or snowy), on the highway, and on non-dry road surfaces are associated with an increase in the likelihood of severe injury crashes. Furthermore, several significant interaction effects were revealed. First, the mitigating effect of ADS engagement on the likelihood of slight injury crashes is reduced by the rear-end collision type. Second, the likelihood of slight injury crashes increases when AV interacts with heavy trucks on highways. Third, the likelihood of severe injuries increases when AVs collide with Vulnerable Road Users (VRUs) on urban streets. Overall, this research is expected to provide policymakers and AV manufacturers with valuable insights into AV safety, stressing that addressing the identified factors will lead to improved AV design and control algorithms.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100934"},"PeriodicalIF":5.1,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554014","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":"Enhancing transport mode classification benchmark by integrating spatial independence with multimodal dataset","authors":"Martina Erdelić ,&nbsp;Tonči Carić ,&nbsp;Tomislav Erdelić ,&nbsp;Ivana Šemanjski","doi":"10.1016/j.tbs.2024.100929","DOIUrl":"10.1016/j.tbs.2024.100929","url":null,"abstract":"<div><div>The transport network is a complex system that benefits from detailed data on user mobility. Analyzing user trajectories through clustering or classification methods can provide valuable insights into mobility patterns. Extracting transport modes from these trajectories using classification methods enhances the understanding of user mobility. The complexity of classification methods varies, with some classifying a few transport modes, such as walking, running, bicycling, and driving. In contrast, others classify up to seven modes or use private, unpublished datasets. A key challenge in transport mode classification is ensuring the comparability of different methods across various contexts. Additionally, comparing results is further complicated by the insufficient use of existing standardized benchmark, which in the case of transport mode classification, must contain a structured testing framework and a dataset on which the testing will be conducted. This research introduces a process for collecting data to develop a new transport mode classification dataset. The goal is to enhance the benchmark by evaluating classification methods across diverse traffic patterns and geographic areas, thereby assessing their spatial independence. Spatial independence is crucial because it ensures that classification methods remain accurate regardless of geographic variations. This improves comparability by enabling consistent evaluation of methods across regions, as the improved benchmark addresses spatial independence and ensures robustness for real-world deployment. The current benchmark in literature examines three types of independence: user, position, and time independence. Our tests employ a multilevel method based on Transition State Matrices (TSMs) and the Random Forest (RF) algorithm for transport mode classification. The results demonstrate that the multilevel method maintains spatial independence and achieves higher accuracy compared to the original benchmark problem.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100929"},"PeriodicalIF":5.1,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539630","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":"Investigating residents’ leisure needs in Japan: A joint analysis of realized and unrealized leisure trips","authors":"Jianbiao Wang ,&nbsp;Tomio Miwa","doi":"10.1016/j.tbs.2024.100931","DOIUrl":"10.1016/j.tbs.2024.100931","url":null,"abstract":"<div><div>Leisure activities are closely associated with individuals’ quality of life. In this paper, we are interested in how many leisure trips the individuals have realized and how many trips they schedule but fail to realize due to the inability to accomplish the activity. The realized and unrealized leisure trips are correlated and together constitute leisure needs. To investigate it, a survey was conducted in seven prefectures in Japan. Then, the copula-based bivariate zero-inflated negative binomial model was adopted to explore the influential factors on realized and unrealized leisure trips as well as their potential correlation. The results indicated that individuals living near bus stations tend to have fewer unrealized leisure trips, and people with driving licenses tend always to satisfy their needs and report no unrealized leisure trips. Further, the result confirmed the potential correlation between realized and unrealized leisure trips, but such correlation decreases for seniors. The population share of individuals whose leisure needs are always completely satisfied or never satisfied was also calculated. The study findings provide the policy implications and are conducive to improving the quality of life.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100931"},"PeriodicalIF":5.1,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142536296","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":"Evaluating multimodal transportation’s impact on city attractiveness: A machine learning approach","authors":"Junmei Cheng ,&nbsp;Zhenhua Chen","doi":"10.1016/j.tbs.2024.100932","DOIUrl":"10.1016/j.tbs.2024.100932","url":null,"abstract":"<div><div>Intercity transportation infrastructure plays a vital role in promoting urban development by enhancing accessibility. Efficient resource allocation for developing various transportation modes is essential for policymakers. The advent of high-speed rail (HSR) has sparked increased interest in comparing multimodal transportation infrastructures, such as railways, highways, and aviation. Previous studies have examined these systems from multiple perspectives, including cost, operation, modal choice, network structure, and socioeconomic impact. However, their influence on city attractiveness remains unclear. This study aims to address this gap by utilizing machine learning models, including Principal Component Analysis (PCA) and Gradient Boosting Decision Tree (GBDT), to compare the impact of railways, highways, and aviation on city attractiveness. The analysis employs data from 286 prefecture-level cities in China from 2002 to 2018. The results indicate that HSR has a relatively higher importance in predicting city attractiveness compared to highways and aviation, particularly during the rapid development period of HSR from 2008 to 2018 in China. The analysis also reveals the threshold effects of transportation infrastructure on city attractiveness. This study offers valuable insights for policymakers to improve city attractiveness. The findings help prioritize different transportation infrastructures and determine the optimal scale of infrastructure deployment.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100932"},"PeriodicalIF":5.1,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142536295","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":"Inclusive intervention design for vulnerable road users: Applying co-design and behaviour change model in Bangladesh","authors":"M. Shaheen Sarker ,&nbsp;Oliver Carsten ,&nbsp;Yue Huang ,&nbsp;Foroogh Hajiseyedjavadi","doi":"10.1016/j.tbs.2024.100935","DOIUrl":"10.1016/j.tbs.2024.100935","url":null,"abstract":"<div><div>In developing countries, it is debatable whether poor design of facilities or violation of traffic rules by road users is the leading cause of pedestrian injuries and deaths. Professionals, pedestrians and drivers tend to blame each other. Shared responsibility for road safety is crucial for protecting vulnerable road users such as commuting students and workers who face higher injury risks while crossing highways. While the Safe System approach emphasises authorities’ responsibility for safe facilities, understanding user needs and promoting behaviour change remain underexplored. This study investigates the current design practices in Bangladesh. It compares the impact of conventional design with co-design on intervention quality and examines the further benefits of integrating a behaviour change model ‘COM-B’.</div><div>Local road agency professionals applied the design process and suggested interventions at four highway sites. Subsequently, four focus group sessions were conducted with students and workers, followed by four design workshops. In each workshop, participants were randomly assigned to two design groups (without and with the application of the behaviour change model), where they designed interventions facilitated by professionals. Lastly, perception ratings of stakeholders and safety assessments by four experts were conducted to evaluate the efficacy of all interventions.</div><div>The findings highlight major usability problems in conventional designs, while co-designed interventions demonstrate clear improvements. Notably, integrating a behaviour change model further enhances effectiveness. Stakeholder interviews reveal that co-design fosters shared responsibility and addresses the blame culture. The co-design approach and application of the behaviour change model can address design flaws and promote the proper use of facilities.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100935"},"PeriodicalIF":5.1,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535855","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":"Modeling evacuation activities amid compound hazards: Insights from hurricane Irma in Southeast Florida","authors":"Yu Han ,&nbsp;Wei Zhai ,&nbsp;Pallab Mozumder ,&nbsp;Cees van Westen ,&nbsp;Changjie Chen","doi":"10.1016/j.tbs.2024.100933","DOIUrl":"10.1016/j.tbs.2024.100933","url":null,"abstract":"<div><div>Given the destructive nature of hurricanes in tropical regions, pre-disaster evacuation has emerged as a critical approach for hurricane preparedness. Nevertheless, the compounding effects of natural hazards and the outbreak of infectious diseases, such as Covid-19, significantly challenge hurricane evacuation management. To investigate emergency responses under compound hazards, this study develops an activity-based model to measure the evacuation behaviors of individuals, using Hurricane Irma as a case study. Four scenarios are designed, including a single hurricane hazard, Hurricane Irma compounded with a pandemic like Covid-19, Hurricane Irma compounded with flood damage to the transportation network, and a combination of all these hazards. The metropolis-hasting algorithm is utilized to generate a population with socioeconomic attributes, which is then allocated to census block groups covering Palm Beach, Broward, Miami-Dade, and Monroe Counties in Florida. Datasets from multiple sources are used to measure evacuation decisions, which are subsequently simulated using MATSim. The results highlight the potential impacts of compound hazards on transportation systems, including increased congestions in scenarios involving compounded hurricanes and floods, especially between 10 a.m. and 7p.m. Moreover, a higher proportion of socially vulnerable populations is observed in scenarios involving compounded hurricanes and pandemics, particularly in the Key West area. The developed model could be further applied to measure the indirect impacts of natural hazards on transportation systems.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100933"},"PeriodicalIF":5.1,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535856","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}