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Matsuo, Kojiro, Kosuke Miyazaki y Nao Sugiki. "A Method for Locational Risk Estimation of Vehicle–Children Accidents Considering Children’s Travel Purposes". International Journal of Environmental Research and Public Health 19, n.º 21 (29 de octubre de 2022): 14123. http://dx.doi.org/10.3390/ijerph192114123.
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The reduction in locational traffic accident risks through appropriate traffic safety management is important to support, maintain, and improve children’s safe and independent mobility. This study proposes and verifies a method to evaluate the risk of elementary school students-vehicle accidents (ESSVAs) at individual intersections on residential roads in Toyohashi city, Japan, considering the difference in travel purposes (i.e., school commuting purpose; SCP or non-school commuting purpose: NSCP), based on a statistical regression model and Empirical Bayes (EB) estimation. The results showed that the ESSVA risk of children’s travel in SCP is lower than that in NSCP, and not only ESSVAs in SCP but also most ESSVAs in NSCP occurred on or near the designated school routes. Therefore, it would make sense to implement traffic safety management and measures focusing on school routes. It was also found that the locational ESSVA risk structure is different depending on whether the purpose of the children’s travels is SCP or NSCP in the statistical model. Finally, it was suggested that evaluation of locational ESSVA risks based on the EB estimation is useful for efficiently extracting locations where traffic safety measures should be implemented compared to that only based on the number of accidents in the past.
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Charreire, H., C. Roda, T. Feuillet, A. Piombini, H. Bardos, H. Rutter, S. Compernolle, J. D. Mackenbach, J. Lakerveld y J. M. Oppert. "Walking, cycling, and public transport for commuting and non-commuting travels across 5 European urban regions: Modal choice correlates and motivations". Journal of Transport Geography 96 (octubre de 2021): 103196. http://dx.doi.org/10.1016/j.jtrangeo.2021.103196.
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Sprumont, François, Ariane Scheffer, Geoffrey Caruso, Eric Cornelis y Francesco Viti. "Quantifying the Relation between Activity Pattern Complexity and Car Use Using a Partial Least Square Structural Equation Model". Sustainability 14, n.º 19 (24 de septiembre de 2022): 12101. http://dx.doi.org/10.3390/su141912101.
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This paper studies the relationship between activity pattern complexity and car use using two multi-day surveys involving the same participants but collected just before and about one year after they relocated their workplace. Measurable characteristics related to two latent variables, namely activity pattern complexity, or trip chaining (e.g., number of activities done within and outside the home–work tour), and to car use (e.g., usage rate, distance travelled by car) were selected. The study shows that the methodology adopted, partial least square structural equation modelling, quantifies the relation between the two variables, and is robust towards changes in important contextual characteristics of the individuals, namely workplace location. The findings indicate that the number of activities chained to commuting travels strongly impact mode choice and, in particular, car use. The paper also shows that chaining non-work-related activities has a stronger impact on car use. The results of this study suggest that planning and management solutions aimed at reducing car use, but focusing only on the commuting trip while neglecting the impact of other daily activities, may be less effective than expected.
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Barbieri, Diego Maria, Baowen Lou, Marco Passavanti, Cang Hui, Inge Hoff, Daniela Antunes Lessa, Gaurav Sikka et al. "Impact of COVID-19 pandemic on mobility in ten countries and associated perceived risk for all transport modes". PLOS ONE 16, n.º 2 (1 de febrero de 2021): e0245886. http://dx.doi.org/10.1371/journal.pone.0245886.
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The restrictive measures implemented in response to the COVID-19 pandemic have triggered sudden massive changes to travel behaviors of people all around the world. This study examines the individual mobility patterns for all transport modes (walk, bicycle, motorcycle, car driven alone, car driven in company, bus, subway, tram, train, airplane) before and during the restrictions adopted in ten countries on six continents: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. This cross-country study also aims at understanding the predictors of protective behaviors related to the transport sector and COVID-19. Findings hinge upon an online survey conducted in May 2020 (N = 9,394). The empirical results quantify tremendous disruptions for both commuting and non-commuting travels, highlighting substantial reductions in the frequency of all types of trips and use of all modes. In terms of potential virus spread, airplanes and buses are perceived to be the riskiest transport modes, while avoidance of public transport is consistently found across the countries. According to the Protection Motivation Theory, the study sheds new light on the fact that two indicators, namely income inequality, expressed as Gini index, and the reported number of deaths due to COVID-19 per 100,000 inhabitants, aggravate respondents’ perceptions. This research indicates that socio-economic inequality and morbidity are not only related to actual health risks, as well documented in the relevant literature, but also to the perceived risks. These findings document the global impact of the COVID-19 crisis as well as provide guidance for transportation practitioners in developing future strategies.
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Macedo, Mariana, Laura Lotero, Alessio Cardillo, Ronaldo Menezes y Hugo Barbosa. "Differences in the spatial landscape of urban mobility: Gender and socioeconomic perspectives". PLOS ONE 17, n.º 3 (2 de marzo de 2022): e0260874. http://dx.doi.org/10.1371/journal.pone.0260874.
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Many of our routines and activities are linked to our ability to move; be it commuting to work, shopping for groceries, or meeting friends. Yet, factors that limit the individuals’ ability to fully realise their mobility needs will ultimately affect the opportunities they can have access to (e.g. cultural activities, professional interactions). One important aspect frequently overlooked in human mobility studies is how gender-centred issues can amplify other sources of mobility disadvantages (e.g. socioeconomic inequalities), unevenly affecting the pool of opportunities men and women have access to. In this work, we leverage on a combination of computational, statistical, and information-theoretical approaches to investigate the existence of systematic discrepancies in the mobility diversity (i.e. the diversity of travel destinations) of (1) men and women from different socioeconomic backgrounds, and (2) work and non-work travels. Our analysis is based on datasets containing multiple instances of large-scale, official, travel surveys carried out in three major metropolitan areas in South America: Medellín and Bogotá in Colombia, and São Paulo in Brazil. Our results indicate the presence of general discrepancies in the urban mobility diversities related to the gender and socioeconomic characteristics of the individuals. Lastly, this paper sheds new light on the possible origins of gender-level human mobility inequalities, contributing to the general understanding of disaggregated patterns in human mobility.
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Kang, Jing, Changcheng Kan y Zhongjie Lin. "Are Electric Vehicles Reshaping the City? An Investigation of the Clustering of Electric Vehicle Owners’ Dwellings and Their Interaction with Urban Spaces". ISPRS International Journal of Geo-Information 10, n.º 5 (10 de mayo de 2021): 320. http://dx.doi.org/10.3390/ijgi10050320.
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With the rapid development of electric vehicles (EVs) around the world, debates have arisen with regard to their impacts on people’s lifestyles and urban space. Mining spatio-temporal patterns from increasingly smart city sensors and personal mobile devices have become an important approach in understanding the interaction between human activity and urban space. In this study, we used location-based service data to identify EV owners and capture the distribution of home and charging stations. The research goal was to investigate that how the urban form in regions under rapid urbanization is driven by EV use, from a geographical perspective. Using a case study of the expanding metropolis of Beijing, GIS-based spatial statistical analysis was conducted to characterize the spatial-pattern of the homes of EV owners as well as their charging preferences. Our results indicate that the spatial clustering of the homes of EV owners in non-urban central areas—suburban areas—is significantly higher than that in urban central areas. According to the records of visits to charging stations, the spatial interaction distance between the dwellings of EV owners and their visits to charging stations exhibits significant distance attenuation characteristics. 88% of EV owners in this research travels within 40 km (Euclidean distance) between housing and charging stations. At the same time, there were significant differences in the spatial patterns between working days and non-working days which are affected by commuting activities. The three types of urban spatial interaction patterns were identified and categorized by visualization. This transformation to EV use in the city influences several aspects of people’s decisions and behaviors in life. Understanding the impacts will provide valuable information for the development of EVs and their implications in the electrification of transportation, smart planning, and sustainable urbanization.
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Cao, Min y Mengxue Huang. "Analysis on the Riding Characteristics of Mobike Sharing Bicycle in Beijing City, China". Abstracts of the ICA 1 (15 de julio de 2019): 1–2. http://dx.doi.org/10.5194/ica-abs-1-37-2019.
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<p><strong>Abstract.</strong> The development of the sharing economy has provided an important realization path for urban’s green and healthy development, and has also accelerated the speed of urban development. With the constant capital pouring into the public transport field, dock-less shared bicycle is a relatively new form of transport in urban areas, and it provides a bikesharing service to fulfil urban short trips. Dock-less shared bicycle, with a characteristic of riding and stopping anywhere, has successfully solved the last mile travel problem. Recently, studies focus on the on the temporal spatial characteristics of public bicycle based on public bicycle operation data. However, there are few studies on the identification of riding patterns based on the characteristics of temporal and spatial behavior of residents. In addition, researches have been conducted on public bicycles administered by the government, and the dock-less shared bicycle have different characteristics from public bicycles in terms of scale of use and mode of use. This paper aims to analyze the temporal and spatial characteristics of residents using shared bicycles, and attempts to explore the characteristics of the riding modes of the dock-less shared bicycles.</p><p>Mobike sharing bicycle dataset of Beijing city were obtained for the research and this dataset contains a wealth of attributes with cover of 396600 shared bicycle users and 485500 riding records from May 10 to May 25 in 2017. Additionally, 19 types of POI (Point of Interest) data were also obtained through the API of Baidu Maps. To examine the patterns of shared bicycle trips, these POI data are categorized into five types including residential, commercial, institution, recreation and transport. Spatiotemporal analysis method, correlation analysis methods and kernel density methods were used to analyse the temporal and spatial characteristics of shared bicycle trips, revealing the time curve and spatial hotspot distribution area of shared bikes. Furthermore, a new matrix of riding pattern based on POI was proposed to identify the riding patterns during massive sharing bicycle dataset.</p><p>This paper aims to explore the riding behaviour of shared bicycles, and the research results are as follows:</p><p>(1) Temporal characteristics of riding behaviour</p><p>The use of the Mobike bicycles is significantly different on weekdays and weekends (Figure1). Figure 2 clearly shows a morning peak (7&ndash;9&thinsp;h) and evening peak (17&ndash;19&thinsp;h), corresponding with typical commute time. At noon, some users' dining activities triggered a certain close-distance riding behavior, which formed a noon peak. Different from the riding characteristics of the working days, there are many recreational and leisure riding behaviors on the weekends. The distribution of riding time is more balanced, and there is no obvious morning and evening peak phenomenon.</p><p>(2) Spatial characteristics of riding behavior</p><p> The spatial distribution of riding behaviour varies with different roads (Figure 2) and people prefer to choose trunk roads for cycling trips. Spatial hotpot detecting method based on the kernel density is applied to identify the active degree of bike sharing trip during a whole weekday (Figure 3). The red colour represents a high active degree and the green and blue colour means the low degree. Note that almost no riding occurred in the early hours of the morning and late at night. The characteristics of three riding peaks are obvious in the figure. A large number of travels occurred in Second Ring to Fourth Ring Road, and some travel activities were concentrated near traffic sites.</p><p>(3) Patterns of riding behavior</p><p> Different riding patterns happens in different space and change over the time at two scales of day and hour. During morning peak and evening peak on weekdays, more than 60 percent of riding trips are corresponding with typical commuting activities. The observed commuting pattern of morning peak (Figure 4(a) and (b)) implies that the majority of shared bicycle trips might relate to home, transports, commercial area and some institution. For example, students choose shared bicycles to do some school activities, people prefer to use shared bicycles as a connection tool to bus station and metro stops and people handle daily affairs in some government agencies. However, a large part of the shared bicycle trips on weekends shows the characteristics of non-commuting riding pattern, which means more leisure activities take place at weekends (Figure 4(c) and (d)). Non-commuting pattern of riding behavior mainly occurs among residential areas, metro stops, bus stations and recreational facilities, such as parks, playgrounds, etc.</p>
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He, Mingwei, Na Chen, Yueren He, Jianbo Li y Yang Liu. "Exploring the Activity-Travel Patterns of Multi-Purpose Commuters on Workdays Based on Activity Chains and Time Allocation: Evidence from Kunming, China". ISPRS International Journal of Geo-Information 13, n.º 12 (10 de diciembre de 2024): 446. https://doi.org/10.3390/ijgi13120446.
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Understanding activity-travel patterns and their determinants with regard to multi-purpose commuters is essential for enhancing commuting efficiency and ensuring equal participation in activities. This study applies sequence analysis and hierarchical clustering to identify distinct activity-travel patterns of Kunming commuters using 2016 Household Travel Survey data. Subsequently, a multinomial logistic regression model (MNL) examines the factors influencing these patterns. The results reveal significant heterogeneity across four activity-travel patterns: the fixed commuter pattern (FCP), characterized by pronounced morning and evening peaks with minimal non-commuting activities; the balanced commuter pattern (BCP), where commuters participate in non-commuting activities after afternoon work; the restricted commuter pattern (RCP), with non-commuting activities occurring after midday work; and the flexible commuter pattern (FLCP), featuring a late-start work pattern where some commuters go to work after 5 pm. Additionally, the study finds that female commuters and those with longer commuting and working hours tend to have simpler time allocation. Conversely, male commuters, those from complex family structures, car-owning households, and residents in areas with abundant activity opportunities actively engage in non-commuting activities. These findings can help policymakers optimize travel services and develop heterogeneous commuting and transportation policies.
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Guo, Liang, Shuo Yang, Qinghao Zhang, Leyu Zhou y Hui He. "Examining the Nonlinear and Synergistic Effects of Multidimensional Elements on Commuting Carbon Emissions: A Case Study in Wuhan, China". International Journal of Environmental Research and Public Health 20, n.º 2 (16 de enero de 2023): 1616. http://dx.doi.org/10.3390/ijerph20021616.
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Understanding the specific effects of multidimensional elements of a built environment, transportation management policies, and the socio-demographics of travelers associated with commuting carbon emissions is significant for planners in promoting low-carbon and healthy urban development through transportation and land use and urban management policies. Most of the existing studies focus on the complex mechanisms affecting commuting behavior, but the relevant elements and specific mechanisms affecting commuting carbon emissions have not received sufficient attention. This study uses a random forest approach to analyze residential travel data from Wuhan, China. The results show that built environment and transportation demand management policies are critical to commuting carbon emissions, and that there is a non-linear association between multidimensional factors and commuting carbon emissions in Chinese cities. In addition, the study examines the synergistic effects of built environment and transportation management policies on commuting carbon emissions among different built environment elements. The results of the study provide valuable insights for planners in formulating low-carbon city and transportation development policies.
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Liu, Jixiang, Jiangping Zhou y Longzhu Xiao. "Built environment correlates of walking for transportation: Differences between commuting and non-commuting trips". Journal of Transport and Land Use 14, n.º 1 (19 de octubre de 2021): 1129–48. http://dx.doi.org/10.5198/jtlu.2021.1933.
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As a sustainable mode of travel, walking for transportation has multiple environmental, social, and health-related benefits. In existing studies, however, such walking has rarely been differentiated between commuting and non-commuting trips. Using multilevel zero-inflated negative binomial regression and multilevel Tobit regression models, this study empirically examines the frequency and duration of commuting and non-commuting walking and their correlates in Xiamen, China. It finds that (1) non-commuting walking, on average, has a higher frequency and longer duration than commuting walking; (2) most socio-demographic variables are significant predictors, and age, occupation, and family size have opposite-direction effects on commuting and non-commuting walking; and (3) different sets of built environment variables are correlated with commuting and non-commuting walking, and the built environment collectively influences the latter more significantly than the former. The findings provide useful references for customized interventions concerning promoting commuting and non-commuting walking.
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Rosenblum, Andrew, Charles M. Cleland, Chunki Fong, Deborah J. Kayman, Barbara Tempalski y Mark Parrino. "Distance Traveled and Cross-State Commuting to Opioid Treatment Programs in the United States". Journal of Environmental and Public Health 2011 (2011): 1–10. http://dx.doi.org/10.1155/2011/948789.
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This study examined commuting patterns among 23,141 methadone patients enrolling in 84 opioid treatment programs (OTPs) in the United States. Patients completed an anonymous one-page survey. A linear mixed model analysis was used to predict distance traveled to the OTP. More than half (60%) the patients traveled <10 miles and 6% travelled between 50 and 200 miles to attend an OTP; 8% travelled across a state border to attend an OTP. In the multivariate model (n=17,792), factors significantly (P<.05) associated with distance were, residing in the Southeast or Midwest, low urbanicity, area of the patient's ZIP code, younger age, non-Hispanic white race/ethnicity, prescription opioid abuse, and no heroin use. A significant number of OTP patients travel considerable distances to access treatment. To reduce obstacles to OTP access, policy makers and treatment providers should be alert to patients' commuting patterns and to factors associated with them.
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Yang, Huajie, Jiali Lin, Jiahao Shi y Xiaobo Ma. "Application of Historical Comprehensive Multimodal Transportation Data for Testing the Commuting Time Paradox: Evidence from the Portland, OR Region". Applied Sciences 14, n.º 18 (18 de septiembre de 2024): 8369. http://dx.doi.org/10.3390/app14188369.
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There have been numerous theoretical and empirical transportation studies contesting the stability of commuting time over time. The constant commuting time hypothesis posits that people adjust trip durations, shift across modes, and sort through locations, so that their average commuting time remains within a constant budget. There is a discrepancy between studies applying aggregate analysis and those using disaggregate analysis, and differences in data collection may have contributed to the varying conclusions reported in the literature. This study conducts both aggregate and disaggregate analyses with two travel surveys of the Portland region. We employ descriptive analysis and t-tests to compare the aggregate commuting times of two years and use regression models to explore factors affecting the disaggregate commuting time at the individual trip level to examine whether the stability of the commuting time remains after substantial changes in the transportation and land use systems. Our study indicates that the average commuting time, along with the average commuting distance, increased slightly, as the mode share shifted away from driving during the examined period. The growth in shares of non-driving modes, which are slower than driving, coupled with an increased travel distance, contributed to the small increase in the average commuting time. Our analysis also indicates that the average travel speed improved for transit riders as well as drivers, contradicting earlier research that claims that public transit investment has worsened the congestion in Portland.
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Sun, Ye y Xinmiao Yang. "Investigation of commuting and non-commuting travel features for the popularization of public transportation system". International Journal of Computational Intelligence Systems 4, n.º 6 (2011): 1307. http://dx.doi.org/10.2991/ijcis.2011.4.6.23.
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Sun, Ye y Xinmiao Yang. "Investigation of commuting and non-commuting travel features for the popularization of public transportation system". International Journal of Computational Intelligence Systems 4, n.º 6 (diciembre de 2011): 1307–18. http://dx.doi.org/10.1080/18756891.2011.9727880.
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Xu, Chengcheng, Chen Wang, Wei Wang, Jie Bao y Menglin Yang. "Investigating Spatial Interdependence in E-Bike Choice Using Spatially Autoregressive Model". PROMET - Traffic&Transportation 29, n.º 4 (28 de agosto de 2017): 351–62. http://dx.doi.org/10.7307/ptt.v29i4.2144.
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Increased attention has been given to promoting e-bike usage in recent years. However, the research gap still exists in understanding the effects of spatial interdependence on e-bike choice. This study investigated how spatial interdependence affected the e-bike choice. The Moran’s I statistic test showed that spatial interdependence exists in e-bike choice at aggregated level. Bayesian spatial autoregressive logistic analyses were then used to investigate the spatial interdependence at individual level. Separate models were developed for commuting and non-commuting trips. The factors affecting e-bike choice are different between commuting and non-commuting trips. Spatial interdependence exists at both origin and destination sides of commuting and non-commuting trips. Travellers are more likely to choose e-bikes if their neighbours at the trip origin and destination also travel by e-bikes. And the magnitude of this spatial interdependence is different across various traffic analysis zones. The results suggest that, without considering spatial interdependence, the traditional methods may have biased estimation results and make systematic forecasting errors.
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Yao, Xing, Chunhui Jing, Yaoxuan Huang y Jinyi Zhi. "A Comparative Study of Passenger Multitasking Activities on Commuting and Leisure Electrified Intercity Railways". Journal of Advanced Transportation 2022 (21 de enero de 2022): 1–11. http://dx.doi.org/10.1155/2022/3001392.
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The electrification of intercity railways plays a significant role in energy conservation and emission reduction. Research on passenger travel activities to optimize vehicle services can help to understand how best to improve passenger attraction and the use of intercity railways. In this study, we conducted observational research on two electrified intercity railways that were segregated by the attributes, leisure, and commute. The purpose was to determine the influence of line attribute, passenger gender, age, and seat availability on the types of activities performed onboard, with specific attention placed on the use of information and communication technology (ICT). Using structured observations, the travel multitasking activity data of 467 passengers were collected on two intercity railways in real-life situations. Using the chi-square test and binary logistic regression analysis, it was found that line attribute, gender, age, and seat availability have an impact on passenger activities. Differences in factors affecting passenger activities were also found according to the nature of their travel, whether for commute or leisure. Our results suggest that passengers on the leisure line prefer to engage in some social activities. For example, the probability of conversation among passengers on the leisure line was 3.47 times that of the commuting line, and the middle-aged and elderly travelers on this line were more likely to be in a daze and look around. The probability of taking a break for passengers on the commuting line was 3.625 times that of the leisure line, and passengers who were not seated on this line were found to be more likely to be idle. In addition, male travelers and young travelers preferred to engage in ICT immersive activities, such as using mobile phones, while women, middle-aged, and elderly travelers were more likely to engage in non-ICT immersive activities. Seated passengers were more likely to engage in simultaneous multitasking activities, rest, and conversations than passengers without seats.
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Mehriar, Melika, Houshmand Masoumi y Inmaculada Mohino. "Urban Sprawl, Socioeconomic Features, and Travel Patterns in Middle East Countries: A Case Study in Iran". Sustainability 12, n.º 22 (18 de noviembre de 2020): 9620. http://dx.doi.org/10.3390/su12229620.
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The present study aimed to investigate different socioeconomic factors as well as the perceptions and travel behaviors associated with urban sprawl in two cities of different sizes in Iran, as a developing country in the Middle East. Four Weighted Least Squares (WLS) regression models were developed for Hamedan and Nowshahr, as examples of large and small cities in Iran, respectively. The findings showed different correlations related to urban sprawl between Iranian cities and high-income countries in terms of socioeconomic and travel behavior determinants. Urban sprawl around home in Hamedan was positively correlated with the number of cars and driving licenses in households, the use of a private car for trips, and less use of public transport. Urban sprawl around homes in Nowshahr was related to an increased number of cars, the use of private cars for non-commuting trips, less sense of belonging to the neighborhood, and lower income. Additionally, urban sprawl around workplaces was correlated with main daily activity, number of non-commuting trips, mode of choice for non-commuting, and residential location choice in Hamedan a swell as monthly income, daily shopping area, frequency of public transport use, quality of recreational facilities, length of time for living in the current home, and commuting distance in Nowshahr.
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Smith, Michaela A., Jan Rasmus Boehnke, Hilary Graham, Piran C. L. White y Stephanie L. Prady. "Associations between active travel and diet: cross-sectional evidence on healthy, low-carbon behaviours from UK Biobank". BMJ Open 9, n.º 8 (agosto de 2019): e030741. http://dx.doi.org/10.1136/bmjopen-2019-030741.
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ObjectivesTo examine whether there are associations between active travel and markers of a healthy, low-carbon (HLC) diet (increased consumption of fruit and vegetables (FV), reduced consumption of red and processed meat (RPM)).DesignCross-sectional analysis of a cohort study.SettingsPopulation cohort of over 500 000 people recruited from 22 centres across the UK. Participants aged between 40 and 69 years were recruited between 2006 and 2010.Participants412 299 adults with complete data on travel mode use, consumption of FV and RPM, and sociodemographic covariates were included in the analysis.Exposure measuresMutually exclusive mode or mode combinations of travel (car, public transport, walking, cycling) for non-work and commuting journeys.Outcome measuresConsumption of FV measured as portions per day and RPM measured as frequency per week.ResultsEngaging in all types of active travel was positively associated with higher FV consumption and negatively associated with more frequent RPM consumption. Cycling exclusively or in combination with walking was most strongly associated with increased dietary consumption of FV and reduced consumption of RPM for both non-work and commuting journeys. Overall, the strongest associations were between non-work cycling and FV consumption (males: adjusted OR=2.18, 95% CI 2.06 to 2.30; females: adjusted OR=2.50, 95% CI 2.31 to 2.71) and non-work cycling and RPM consumption (males: adjusted OR=0.57, 95% CI 0.54 to 0.60; females: adjusted OR=0.54, 95% CI 0.50 to 0.59). Associations were generally similar for both commuting and non-work travel, and were robust to adjustment with sociodemographic and behavioural factors.ConclusionsThere are strong associations between engaging in active travel, particularly cycling, and HLC dietary consumption, suggesting that these HLC behaviours are related. Further research is needed to better understand the drivers and dynamics between these behaviours within individuals, and whether they share common underlying causes.
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Maheshwari, Richa, Veronique Van Acker, Jonas De Vos y Frank Witlox. "Analyzing the association between satisfaction with commuting time and satisfaction with life domains: A comparison of 32 European countries". Journal of Transport and Land Use 15, n.º 1 (21 de marzo de 2022): 231–48. http://dx.doi.org/10.5198/jtlu.2022.2121.
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Although the majority of literature explains travel satisfaction by examining trip determinants, the interaction between travel satisfaction and satisfaction with other life domains has been analyzed less frequently. Accounting for satisfaction with other life domains is nevertheless important because the effect of trip characteristics on travel satisfaction may be overestimated without considering satisfaction with non-travel-related life domains. Hence, this paper examines the interaction between satisfaction with commuting time, satisfaction with other life domains and overall life satisfaction. An ordered logistic regression has been estimated using a large dataset comprising data from 32 European countries. Results indicate that satisfaction with specific life domains and overall life satisfaction have a significant association with commuting time satisfaction (CTS), while controlling for employment characteristics, and personality (i.e., trust). Of all life domains, job and time-use satisfaction have the strongest associations with CTS. Given the large dataset, we controlled for the contextual differences between the European countries by making a distinction between well- and less-developed countries. The result seems to suggest that all life domains and employment characteristics better explain CTS in well-developed countries than less-developed countries. This paper thus contributes to reporting other innovative ways to obtain high levels of commuting time satisfaction rather than only looking at the interactions with transport mode, travel distance and travel time.
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Wang, Xiaoguang, Joe Grengs y Lidia Kostyniuk. "Visualizing Travel Patterns with a GPS Dataset: How Commuting Routes Influence Non-Work Travel Behavior". Journal of Urban Technology 20, n.º 3 (julio de 2013): 105–25. http://dx.doi.org/10.1080/10630732.2013.811986.
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Rosida, Ismatulloh, Dyah Wulan Sari y Amelia Dertta Irjayanti. "THE MODE CHOICES AND COMMUTING STRESS: EMPIRICAL EVIDENCE FROM JAKARTA AND DENPASAR". Jurnal Pengembangan Kota 7, n.º 1 (21 de noviembre de 2019): 68. http://dx.doi.org/10.14710/jpk.7.1.68-76.
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Jabodetabek and Sarbagita have the highest worker commuter population in Indonesia. However, Jabodetabek has various and larger coverage of public transport than Sarbagita. This study also analyzes the relationship between the usage of specific transport modes and commuting stress. Multiple logistic regression models have been estimated using data of both Jabodetabek Commuter Survey and Sarbagita Commuter Survey. Using logistic regressions, the results show that mode choices, gender, and travel time have a significant effect on commuting stress. The analysis also indicates that both in high impedance and low impedance metropolitans, car commuting is perceived to be more stressful than non-car commuting. In a condition of restricted mode choices, commuters who use cars have a greater probability of commuting stress. Furthermore, the findings of this study imply limitation of car usage and as an evaluation of the policy of opening toll roads as a solution to urban congestion.
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Sahlqvist, Shannon, Yena Song y David Ogilvie. "Is active travel associated with greater physical activity? The contribution of commuting and non-commuting active travel to total physical activity in adults". Preventive Medicine 55, n.º 3 (septiembre de 2012): 206–11. http://dx.doi.org/10.1016/j.ypmed.2012.06.028.
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Mehriar, Melika, Houshmand Masoumi, Atif Bilal Aslam y Syed Mubasher Gillani. "The Neighborhood Effect on Keeping Non-Commuting Journeys within Compact and Sprawled Districts". Land 10, n.º 11 (14 de noviembre de 2021): 1245. http://dx.doi.org/10.3390/land10111245.
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The neighborhood effect on keeping non-commuting trips inside neighborhoods has not yet been investigated in developing countries. The modeling of non-commuting trips inside neighborhoods helps understand how to avoid unnecessary journeys by car into different parts of the city. This paper, therefore, attempts to clarify (1) the similarities and differences in the socioeconomic characteristics and the perceptions of people in sprawled and compact neighborhoods, (2) correlations between, on the one hand, the choice of destinations of non-commuting trips for shopping and entertainment activities and, on the other, the socioeconomic features, travel behavior, and perceptions of residents in the two large Pakistani cities of Lahore and Rawalpindi, (3) the similarities and differences in the determinants of non-commuting destinations inside neighborhoods in compact and sprawled districts. The paper develops four Binary Logistic (BL) regression models, with two models for each type of neighborhood. The findings show that trips to shopping areas inside compact districts are correlated with a sense of belonging to the neighborhood, frequency of public transport use, residential location, and mode choice of non-commuting trips to destinations both inside and outside the neighborhood. On the other hand, the number of non-commuting trips, mode choice for non-commuting trips outside the neighborhood, frequency of public transport use, the attractiveness of shops, and monthly income (please see the Note) are significant determinants for trips to the shopping area in sprawled districts. Age, gender, possession of a driver’s license, income, number of non-commuting trips, mode choice for non-commuting trips outside of the neighborhood, car ownership, and attractiveness of shops in a neighborhood are correlated with trips to entertainment locations inside the neighborhood in compact districts. Finally, the attractiveness of shops, quality of social and recreational facilities, a sense of belonging to a neighborhood, choice of residential location, gender, age, possession of a driver’s license, number of cars in the household, and income are determinants of trips to entertainment locations in sprawled districts. A chi-square test confirms the differences across gender, daily activity, monthly income, frequency of public transport use, residential location choice, and the quality of social and recreational facilities for sprawled and compact districts in Pakistan.
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Zhang, Mei, Jia Tang y Jun Gao. "Examining the Effects of Built Environments and Individual Characteristics on Commuting Time under Spatial Heterogeneity: An Empirical Study in China Using HLM". Land 12, n.º 8 (13 de agosto de 2023): 1596. http://dx.doi.org/10.3390/land12081596.
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A large number of studies have provided evidence regarding the factors that influence commuting time. However, few studies have explored such effects in the context of considering spatial heterogeneity across cities, which limits the generalizability of the findings. This study addresses this gap by utilizing a dataset of 113 cities in China across the years 2014, 2016, 2018, and 2020. A two-level hierarchical linear model (HLM) was developed to explore the combined effects of city-level and individual-level factors on commuting time by constructing a nested “city-individual” relationship. The results show that (1) built environments at the city level significantly impact commuting time; (2) a non-linear association between population density and commuting time (U-shaped relationship) was identified, as well as between the number of buses and commuting time (inverted U-shaped relationship); (3) the urban construction land area and road area per capita exert negative effects on commuting time; (4) the impacts of individuals’ jobs–housing balance, travel allowances, and education on commuting time vary across cities. These findings might contribute to optimizing the design of a built environment, addressing the challenge posed by longer commuting times, and providing a better understanding of the effects of individuals’ characteristics on commuting time while considering the inherent differences across cities.
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Li, Yige, Ying Jiang y Jin Duan. "Quantifying Administrative and Functional Border Effects on Commuting and Non-Commuting Flows: A Case Study of the Shanghai-Suzhou-Jiaxing Area". ISPRS International Journal of Geo-Information 14, n.º 3 (20 de marzo de 2025): 133. https://doi.org/10.3390/ijgi14030133.
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As cities continuously expand and with the advancement of regional integration, the flows of people, goods, and information have spread beyond their original administrative borders. The top-down administrative borders and bottom-up functional borders divide city regions into areas with different attributes and hierarchical structures. Although existing studies have quantified border effects from the perspective of spatial interaction, these have not clarified the differentiated effects between administrative and functional borders on different flows of activities. Without considering the original administrative borders, this study first proposed a fine-grained spatial unit clustering method based on spatial interaction networks of commuting and non-commuting flows to delineate functional borders. Then, the administrative and functional border effects are evaluated through the gravity model, revealing their influence on travel flows of the city region. This study takes the case study of a mega-city region, the Shanghai-Suzhou-Jiaxing (SSJ) area in China, using mobile phone data. The results indicate that the commuting and non-commuting networks in the SSJ area exhibit a cross-border polycentric hierarchical spatial structure. Both administrative and functional borders have significant effects on spatial interactions, but compared to commuting flows, non-commuting flows are more sensitive with functional borders. Provincial borders exert the most prominent positive effect and exhibit spatial heterogeneity. Meanwhile, the results of border effects might be utilized by policymakers to focus more on promoting the spatial integration of cross-border regions within the SSJ area.
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Fu, Mengying, Raoul Rothfeld y Constantinos Antoniou. "Exploring Preferences for Transportation Modes in an Urban Air Mobility Environment: Munich Case Study". Transportation Research Record: Journal of the Transportation Research Board 2673, n.º 10 (21 de mayo de 2019): 427–42. http://dx.doi.org/10.1177/0361198119843858.
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Urban Air Mobility (UAM) is a recent mobility concept with the potential to reduce travel time and change travel patterns. When evaluating the introduction of UAM, understanding the potential users’ choice behavior regarding current available urban transportation modes and autonomous transportation services is essential to demand estimation. This preliminary research intends to gain insight into the travel behavior impacts of autonomous transportation modes, especially UAM, by deriving measures for transportation service attributes and identifying characteristics of potential users who might adopt autonomous transportation services, particularly the services of UAM. Thus, a stated preference questionnaire was designed and distributed in Munich metropolitan region. A main mode choice multinomial logit model and several sub-models, based on market segmentation, were estimated regarding four transportation alternatives: private car, public transportation, autonomous taxi, and autonomous flying taxi. The results indicate that travel time, travel cost, and safety may be critical determinants in autonomous transportation mode adoption. The potential consumers may be willing to pay more for using autonomous transportation modes, especially the service of UAM. Among different market segments, younger individuals, as well as older individuals with high household income, are more likely to adopt UAM. In addition, during the market entry stage, potential travelers may favor UAM particularly for performing non-commuting trips.
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Bajracharya, Ashim Ratna, Sudha Shrestha y Kishan Datta Bhatta. "Gender Differences in Travel Behavior, for Daily Trips in Kathmandu Valley". Journal of Engineering Technology and Planning 3, n.º 1 (24 de noviembre de 2022): 1–9. http://dx.doi.org/10.3126/joetp.v3i1.49559.
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Kathmandu valley is the main center for economic activities and with it travel demand has increased drastically in the Valley in the recent years, along with rapid growth in population. This paper brings into highlight, the role of gender on urban mobility, for daily trips, by assessing the gender differences in travel behavior of workers and students, in commuting their work and educational trips respectively. Household survey was carried out in different parts of the study area, using random sampling. Data was analyzed to associate gender with travel mode choice and trip length. The statistical analysis of the travel data shows that there is a significant level of association between gender and the way, they travel. The modal share and trip length varies significantly between men and women, more prominently for work trips. For educational trips, the variation is observed comparatively, to a lesser extent. For work trips, men are using more of the private vehicles and relying less on public transport and non-motorized means of travel, as compared to women. It is also revealed that that males are commuting longer trip distances as compared to females. From the findings, recommendations for gender equality in urban transport and promotion of sustainable urban mobility, emphasizing the use of public transport and non-motorized modes of transport.
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Wang, Zijia, Hao Tang, Wenjuan Wang y Yang Xi. "The Pattern of Non-Roundtrip Travel on Urban Rail and Its Application in Transit Improvement". Sustainability 12, n.º 9 (25 de abril de 2020): 3525. http://dx.doi.org/10.3390/su12093525.
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Transit smart card records detail travel information of passengers, which provides abundant data for analyzing public travel patterns. Regular travelers’ information extracted from smart card data (SCD) have been extensively analyzed. However, rare studies have been devoted to non-roundtrips, which account for a relatively large portion of the overall transit ridership, especially in metropolises such as Beijing. This study aimed to reveal the non-roundtrip pattern using the passenger travel data obtained from SCD. Weekly non-roundtrip SCD were used to analyze the spatiotemporal distribution patterns of overall and typical non-roundtrips’ origins and destinations (ODs). Also, subway data and bus data were combined and visualized in geographic information system (GIS). The reasons for frequent non-roundtrips generated in the metropolitan city were inferred. The results demonstrate some detected spatiotemporal patterns of non-roundtrips. It is not surprising that a large proportion of non-roundtrips serve as a rail access to intercity, but there are still many trips of this kind showing a commuting pattern. Merging SCD with bus data, the results also reveal that passengers may choose other modes as a substitute return transportation option due to rail fare or overcrowding problem. This study focused on irregular trips normally neglected in the literature and found that the number of these trips is too large to be ignored in a diversified city like Beijing. Meanwhile, the travel patterns of non-roundtrips extracted can be used to direct the operation strategies for both rail and bus. The research framework raised here could be applied in other cities and comparative analysis could be done in the future.
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Lu, Haiyan, Jiaoju Ge y Ling Yu. "Nudging through persuasive technology in social media to promote low carbon travel behavior in commuting and non-commuting situations". Cities 162 (julio de 2025): 105974. https://doi.org/10.1016/j.cities.2025.105974.
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Sprumont, François, Ali Shateri Benam y Francesco Viti. "Short- and Long-Term Impacts of Workplace Relocation: A Survey and Experience from the University of Luxembourg Relocation". Sustainability 12, n.º 18 (11 de septiembre de 2020): 7506. http://dx.doi.org/10.3390/su12187506.
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Workplace relocation can have a significant impact on commuting trips as well as on the location and number of activities scheduled within the home-work tour. This often exogenous, non-voluntary event affects the entire activity-travel behavior of the employees. As response, employees can adopt several short- and long-term adaptation strategies to cope with such change, the most obvious being commuting mode shifting, acquire new mobility resources (e.g., buying a car) or changing residential location. As workplace relocation can be consequence of national policies aimed at decongesting the city centers or to favor the development of new business areas, undesired macroscopic changes in modal shares and in land developments may be observed. While a decrease in the commuting time after a workplace relocation is, in some cases, observed, an increase in car use for the commuting trip may be observed as well. This paper aims at providing an in-depth understanding of the effect of workplace relocation on travel behavior by reviewing and selecting the relevant scientific literature on the topic, which has in the last years gained popularity. The findings and observations summarized by the literature review are then complemented with the specific example of the relocation of the University of Luxembourg employees. Finally, we indicate potential directions for research, which are currently underexplored.
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Lachapelle, Ugo, Georges A. Tanguay y Léa Neumark-Gaudet. "Telecommuting and sustainable travel: Reduction of overall travel time, increases in non-motorised travel and congestion relief?" Urban Studies 55, n.º 10 (13 de junio de 2017): 2226–44. http://dx.doi.org/10.1177/0042098017708985.
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Existing research has concluded that shares of telecommuting are low but stable, increase with distance from the workplace and that telecommuting may reduce commuting-related travel. Its effect on work and non-work travel are subject to rebound effects and, thus, still debated. Additionally, telecommuting does not necessarily occur entirely at home. The paper studies telecommuting’s potential as a sustainable mobility tool in Canada to reduce overall travel time and peak hour travel, and to increase non-motorised travel. Do types of telecommuting arrangements have varying relationships with these studied travel patterns? Using time use data from the 2005 Canadian General Social Survey, studied outcomes are regressed on telecommuting arrangements (all day home working, part-day home working and a combination of other locations and home and/or workplace) and other personal characteristics. Depending on telecommuting arrangements and travel outcomes, results vary. Working from home is associated with decreases in overall travel time by 14 minutes and increases in odds of non-motorised travel by 77%. Other forms of telecommuting yield different results. Telecommuters may be more likely to avoid peak hours when they do take trips. Types of telecommuting arrangements have different impacts on sustainable travel outcomes that should be considered depending on policy priorities.
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Indurlal, Puneeth, Divya Deepak, David Hakimian, Rajini Manjunath, Rajat Malhotra y Irfan Ahmed Mirza. "Closing the distance gap: Evaluating patient travel distances in a community oncology practice." JCO Oncology Practice 20, n.º 10_suppl (octubre de 2024): 157. http://dx.doi.org/10.1200/op.2024.20.10_suppl.157.
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157 Background: Patient travel distance is an important factor influencing healthcare access, health equity and outcomes. The Rural-Urban Commuting Area (RUCA) classification system categorizes geographic areas based on urbanization and commuting patterns to measure accessibility to healthcare. We study the relationship between RUCA and patient travel distance for a multi-site community-based, medical oncology practice in north-west Chicagoland area. Methods: Using patient ZIP code data and practice locations (clinics) from April 2023 to March 2024, we calculated and compared the straight-line, one-way, patient-clinic travel distance (travel distance) for about 20,000 patients at 5 clinics, using geospatial analysis techniques. We grouped clinics based on location and population characteristics, applied the RUCA classification to patient ZIP codes, and compared travel distances by RUCA categories. Results: The median travel distance for patients was 5.0 miles, with 82% of patients traveling 10 miles or less, and 89% traveling 15 miles or less. Table 1 shows % of patients traveling and travel distance by RUCA categories. Median travel distances for urban metro, suburban metro, and suburban small-town clinics were 4.8mi, 10.8mi and 20.6mi (Kruskal Wallis H-test, p <0.001). Within 50 miles of each clinic, median travel distance for patients from urban ZIP codes (4.8 mi) was lower compared to metropolitan, micropolitan, small town and all other RUCA categories. Conclusions: Preliminary findings indicate a significant association between RUCA and travel distance, with longer travel distances for patients in non-urban locales. Proximity of cancer care sites to the patient’s home reduces distance traveled, minimizing the burden on the patients and their families. Interventions addressing transportation needs (such as improving infrastructure, increasing transportation options, subsidizing healthcare travel, etc.) can be augmented with efforts to strengthen access to community-based sites (expansion of telehealth, incentivizing providers serving non-urban areas, etc.) to reduce patient and caregiver burden. Clinic Site Category % of patients traveling <5 mi <10mi <15mi <50mi >50mi A Suburban Metro 53.8% 30.7% 5.2% 9.1% 0.9% B Suburban Small Town 24.1% 40.6% 21.9% 12.3% 0.4% C Suburban Metro 45.7% 34.3% 5.01% 13.8% 1.0% D Suburban Metro 60.1% 23.9% 6.8% 7.9% 1.2% E Urban Metro 80.3% 9.7% 3.5% 5.2% 1.0% ALL SITES 54.7% 27.1% 7.2% 9.8% 0.9% Clinic Median travel distance in miles (% of patients) by patient RUCA within 50 miles of clinics Urban Metropolitan – High Commute Micropolitan – Flow to Large Urban Cluster Small Town – Flow to Small Urban Cluster All Other A 4.8 (98.2%) 27.5 (1.7%) 48.7 49.4 B 4.0 (42.3%) 8.6 (54.2%) 25.0 20.6 (3.2%) C 5.9 (95.2%) 17.7 (4.5%) 36.7 27.7 D 4.8 (97.1%) 23.7 (2.8%) 48.4 40.1 E 2.7 (98.9%) 32.3 (1.0%) 4.5 ALL 4.8 (91.2%) 10.8 (8.3%) 36.7 (0.1%) 20.6 (0.4%) 4.5
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Panter, Jenna, Oliver Mytton, Stephen Sharp, Søren Brage, Steven Cummins, Anthony A. Laverty, Katrien Wijndaele y David Ogilvie. "Using alternatives to the car and risk of all-cause, cardiovascular and cancer mortality". Heart 104, n.º 21 (21 de mayo de 2018): 1749–55. http://dx.doi.org/10.1136/heartjnl-2017-312699.
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ObjectiveTo investigate the associations between using alternatives to the car which are more active for commuting and non-commuting purposes, and morbidity and mortality.MethodsWe conducted a prospective study using data from 3 58 799 participants, aged 37–73 years, from UK Biobank. Commute and non-commute travel were assessed at baseline in 2006–2010. We classified participants according to whether they relied exclusively on the car or used alternative modes of transport that were more active at least some of the time. The main outcome measures were incident cardiovascular disease (CVD) and cancer, and CVD, cancer and all-cause mortality. We excluded events in the first 2 years and conducted analyses separately for those who regularly commuted and those who did not.ResultsIn maximally adjusted models, regular commuters with more active patterns of travel on the commute had a lower risk of incident (HR 0.89, 95% CI 0.79 to 1.00) and fatal (HR 0.70, 95% CI 0.51 to 0.95) CVD. Those regular commuters who also had more active patterns of non-commute travel had an even lower risk of fatal CVD (HR 0.57, 95% CI 0.39 to 0.85). Among those who were not regular commuters, more active patterns of travel were associated with a lower risk of all-cause mortality (HR 0.92, 95% CI 0.86 to 0.99).ConclusionsMore active patterns of travel were associated with a reduced risk of incident and fatal CVD and all-cause mortality in adults. This is an important message for clinicians advising people about how to be physically active and reduce their risk of disease.
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Haryadi, B., A. Narendra, M. Purnomo y A. Purnomo. "Modelling student travel mode choice: a case study in Semarang, Indonesia". IOP Conference Series: Earth and Environmental Science 969, n.º 1 (1 de enero de 2022): 012077. http://dx.doi.org/10.1088/1755-1315/969/1/012077.
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Abstract The paper presents an investigation of university students’ travel mode choice behaviour for commuting to campus. It uses a dataset collected through a survey among students of four universities in Semarang, i.e., Unnes, UINW, Udinus, and Unissula. Eight hundred and thirty-seven respondents completed the questionnaires. Multinomial logit (MNL) models are used for investigating four transport mode choices, i.e., walk, motorcycle, car, and bus. The independent variables are schools, genders, origin, residential types, vehicle ownership, driving license ownership, monthly allowance, transportation budget, and commuting distance. The model shows that all independent variables, except monthly allowance, are significant predictors. Overall, the model prediction accuracy is about 90 percent. A motorcycle was the foremost prevalent transport for school trips. Empirical models reveal that the mode of choice behaviour of non-native students differs significantly from those that originate in Semarang. The log odds of driving a car, riding a motorcycle, and walking versus riding a bus are higher when students’ origin is not from Semarang compared to Semarang.
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Molina, José Alberto, J. Ignacio Giménez-Nadal y Jorge Velilla. "Sustainable Commuting: Results from a Social Approach and International Evidence on Carpooling". Sustainability 12, n.º 22 (17 de noviembre de 2020): 9587. http://dx.doi.org/10.3390/su12229587.
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Sustainable commuting (SC) usually refers to environmentally friendly travel modes, such as public transport (bus, tram, subway, light rail), walking, cycling, and carpooling. The double aim of the paper is to summarize relevant prior results in commuting from a social approach, and to provide new, international empirical evidence on carpooling as a specific mode of sustainable commuting. The literature shows that certain socio-demographic characteristics clearly affect the use of non-motorized alternatives, and compared to driving, well-being is greater for those using active travel or public transport. Additionally, this paper analyzes the behavior of carpooling for commuting, using ordinary least squares (OLS) models, which have been estimated from the Multinational Time Use Study (MTUS) for the following countries: Bulgaria, Canada, Spain, Finland, France, Hungary, Italy, South Korea, the United Kingdom, and the United States. Results indicate that carpooling for commuting is not habitual for workers, as less than 25% of the total time from/to work by car is done with others on board. With respect to the role of the socio-demographic characteristics of individuals, our evidence indicates that age, gender, education, being native, and household composition may have a cross-country, consistent relationship with carpooling participation. Given that socializing is the main reason for carpooling, in the current COVID-19 pandemic, carpooling may be decreasing and, consequently, initiatives have been launched to show that carpooling is a necessary way to avoid crowded modes of transport. Thus, the development of high-occupancy-vehicle (HOV) lanes by local authorities can increase carpooling, and draw attention to the economic and environmental benefits of carpooling for potential users.
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McAuliffe Wells, Emily, Mitchell Small, C. Anna Spurlock y Gabrielle Wong-Parodi. "Factors associated with emerging multimodal transportation behavior in the San Francisco Bay Area". Environmental Research: Infrastructure and Sustainability 1, n.º 3 (1 de diciembre de 2021): 031004. http://dx.doi.org/10.1088/2634-4505/ac392f.
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Abstract This paper identifies the influence of demographic, local transportation environment, and individual preferences for transportation attributes on multimodal transportation behavior in an urban environment with emergent transportation mode availability. Multimodality is the use of more than one mode of transportation during a given timeframe. Multimodality has been considered a key component of sustainable and efficient transportation systems, as this travel behavior can represent a shift away from personal vehicle use to more sustainable transportation modes, especially in urban environments with diverse transportation systems and emergent shared transportation alternatives (e.g., carsharing, ridehailing, bike sharing). However, it is unclear what factors contribute towards people being more likely to exhibit multimodal transportation behavior in modern urban environments. We assessed commuting behavior based on a survey administered in the San Francisco Bay Area according to whether residents commuted (i) exclusively by vehicle, (ii) by a mix of vehicle and non-vehicle modes, or (iii) exclusively by non-vehicle modes. A classification tree approach identified correlations between commuting classes and demographic variables, preferences for transportation attributes, and location-based information. The characterization of commuting styles could inform regional transportation policy and design that aims to reduce vehicle use by identifying the demographic, preference, and location-based considerations correlated with each commuting style.
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Parra-Saldías, Maribel, Jose Castro-Piñero, Antonio Castillo Paredes, Ximena Palma Leal, Ximena Díaz Martínez y Fernando Rodríguez-Rodríguez. "Active Commuting Behaviours from High School to University in Chile: A Retrospective Study". International Journal of Environmental Research and Public Health 16, n.º 1 (26 de diciembre de 2018): 53. http://dx.doi.org/10.3390/ijerph16010053.
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Objective: To compare the differences in the modes and distance of the displacements in high school and university stage in the same sample. Methods: A total of 1288 volunteer university students (614 males and 674 females) participated, with an average age of 22.7 ± 5.8 years, belonging to four private and public universities in Chile where a validated self-report questionnaire was applied to the study, which included the modes, travel time, and distance at school and university. Results: The active commuting decreases from school to university when leaving home (males: 39.6% to 34.0%; p = 0.033 and females: 32.9% to 18.5%, p < 0.001), as well as when returning (males: 44.1% to 33.7%; p < 0.001 and females: 38.6% to 17.6%, p < 0.001). Conversely, non-active modes of transport increase, especially in females (go: 67.1% to 81.4%, return: 61.5% to 82.6%), affected by the increase in the use of public transportation in university. It was also defined that at both school and at university, the active commuting decreases the greater the distance travelled. Conclusion: The active modes of commuting decreased between high school and university and the non-active mode of commuting was the most frequent form of mobility to high school and university, observing that the active trips decreased when the distance from the home to high school or university increased. Public and private intervention policies and strategies are required to maintain or increase the modes of active commuting in the university stage for an active life in adulthood.
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Mehriar, Melika, Houshmand Masoumi, Atif Bilal Aslam, Syed Mubasher Gillani, Tuba Suhail y Ayesha Zulfiqar. "The Relations between Street Network Configuration and Travel Behavior in Pakistan; the Optimal Level of Street Connectivity for a More Active Mobility". Applied Sciences 11, n.º 22 (20 de noviembre de 2021): 11015. http://dx.doi.org/10.3390/app112211015.
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Urban sprawl is a particular pattern of the street network and land use. The relationship between street networks and sprawl has been discussed by urban scholars in developed and high-income countries. Nevertheless, there is a lack of research on the relationships between street connectivity and urban travel behavior, particularly among emerging markets. This paper aims to study correlations between urban mobility and street-length density as an indicator for assessing the compactness of an area by developing two hierarchical regression models and controlling for socioeconomic variables in two large Pakistani cities: Lahore and Rawalpindi. Moreover, this paper defines optimal cutoff values for street-length density and active transport. Finally, three chi-square tests were conducted to assess the differences between using different mode choices by people living in sprawled neighborhoods versus compact neighborhoods. Our findings confirm the use of different transport modes depending on the purpose of the trip (commuting or non-commuting), length of trip (within or outside the neighborhood), and starting point (sprawled neighborhood or compact area). We also find a positive correlation between street-length density around homes and commuting distance, the frequency of public transport use, and the use of private motor vehicles in commuting trips in the two cities. Street-length density around workplaces is correlated with commuting distance, the frequency of public transport use, and the use of private motor vehicles when socioeconomic variables (including age, daily activity, and monthly income) are controlled for in the two models. The behavior of Pakistani residents changes with a street-length density of 137 and 144.7 m/m2 for homes and workplaces, respectively, in terms of using active mobility.
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Lee, David Jung-Hwi y Jean-Michel Guldmann. "Optimal Regional Allocation of Future Population and Employment under Urban Boundary and Density Constraints: A Spatial Interaction Modeling Approach". Land 12, n.º 2 (7 de febrero de 2023): 433. http://dx.doi.org/10.3390/land12020433.
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This paper develops an optimization modeling framework to select strategies of land development and population and employment densities for a growing metropolitan area. The modeling core involves a non-linear commuting model, which accounts for spatial structure variables and is empirically estimated by Tobit regression. This commuting model is then embedded into a non-linear optimization model that allocates increments in the population and employment (activities) to available land, while minimizing the total future commuting costs under various combinations of land expansion boundaries and population and employment densities. The resulting minimum cost surface is approximated via polynomial regression and combined with land development and congestion cost functions to derive the overall optimal strategy. These models are estimated and calibrated with data from the Census Transportation Planning Package (CTPP) and Auditor’s property database, and are applied to the Fredericksburg metropolitan area, Virginia. The results demonstrate that the optimal development densities are very sensitive to the congestion cost function. A land development strategy that allows for limited sprawl might be a smart policy to reduce both regional vehicle mile travel (VMT) and related congestion and pollution.
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Sick Nielsen, Thomas A. "The Role of Subcentres for Commuting and Non-Work Travel Distances and Modes in the Copenhagen Metropolitan Region". Built Environment 45, n.º 4 (1 de diciembre de 2019): 462–75. http://dx.doi.org/10.2148/benv.45.4.462.
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Understanding the functional geography of the metropolitan region, and developing location criteria for smart growth, requires analysis of subcentres and their effects. Subcentres were identified in the Copenhagen area based on spatial analysis of micro-level employment and retail data. Subcentres' effects on transport in addition to regional centrality were studied with regression analysis of work and nonwork travel behaviour data. Distance to employment subcentres with a minimum of 10,000 jobs and distance to subcentres identi fied from retail data and having a minimum of 400 retail jobs affects residents' daily travel distance and/or transport modes. A short distance to a subcentre allows for shorter daily travel distances and, in the case of retail subcentres, for a higher probability of using public transport or walking/cycling. However, the effects of subcentres are well below the still strong and significant effect of regional centrality upon travel distances as well as mode choice.
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Ding, Chuan, Chao Liu, Yi Zhang, Jiawen Yang y Yunpeng Wang. "Investigating the impacts of built environment on vehicle miles traveled and energy consumption: Differences between commuting and non-commuting trips". Cities 68 (agosto de 2017): 25–36. http://dx.doi.org/10.1016/j.cities.2017.05.005.
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Grigore, Elena, Norman Garrick, Raphael Fuhrer y Ing Kay W. Axhausen. "Bikeability in Basel". Transportation Research Record: Journal of the Transportation Research Board 2673, n.º 6 (12 de abril de 2019): 607–17. http://dx.doi.org/10.1177/0361198119839982.
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“Bikeability” is becoming increasingly relevant in the field of transport- and urban planning. However, it is often unclear how bikeability is defined, let alone how it can be modeled. The goal of this project was to develop a quantitative method to model bikeability. A case study area in the city of Basel, Switzerland was selected for assessing the model. Here “bikeability” is understood as a measure of the ability and convenience in reaching important destinations by bike, based on the travel distance weighted by the perceived safety, -comfort, and -attractiveness of the streets and intersections along the routes. The underlying assumption was that cyclists try to minimize the distance traveled and maximize the perceived safety, -comfort, and -attractiveness of their route of choice. Unlike most of the previous bikeability assessments we reviewed, our method used existing route choice studies to identify attributes for quantifying cycling quality, which presumably results in a model that more accurately reflects real-life behavior. Many relevant attributes that have not been captured by previous models are included in this work, such as the high curbs of tram stops, tram tracks, and the turn direction at intersections. The method is suitable for several applications in urban planning, such as the identification of locations that need improvement and the comparison of planning measures. The current model covers conventional bikes used by commuting cyclists. However, the method could be used for E-bikes and non-commuting cyclists by applying the appropriate input values.
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Vachuska, Karl. "Racial Segregation in Everyday Mobility Patterns: Disentangling the Effect of Travel Time". Socius: Sociological Research for a Dynamic World 9 (enero de 2023): 237802312311692. http://dx.doi.org/10.1177/23780231231169261.
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Nascent research documents that U.S. racial segregation is not merely a residential phenomenon but is present in everyday mobility patterns. Better understanding the causes of mobility-based segregation requires disentangling the spatial macrosegregation, which constitutes an obvious confounding factor. In this work, the author analyzes big data on everyday visits between 270 million neighborhood dyads to estimate the effect of neighborhood racial composition on mobility patterns, net of driving, walking, and public transportation travel time. Matching on these travel times, the author finds that residents of Black and Hispanic neighborhoods visit White neighborhoods only slightly less than they visit other Black and Hispanic neighborhoods. Distinctly, residents of White neighborhoods are far less likely to visit non-White neighborhoods than other White neighborhoods, even net of travel time. The author finds that this travel time–adjusted visit homophily among White neighborhoods is greater in commuting zones where White neighborhoods are situated closer to non-White neighborhoods.
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Pan, Shuangli, Guijun Zheng y Qun Chen. "The psychological decision-making process model of non-commuting travel mode choice under parking constraints". Transportation Research Interdisciplinary Perspectives 11 (septiembre de 2021): 100410. http://dx.doi.org/10.1016/j.trip.2021.100410.
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Convery, Sheila y Brendan Williams. "Determinants of Transport Mode Choice for Non-Commuting Trips: The Roles of Transport, Land Use and Socio-Demographic Characteristics". Urban Science 3, n.º 3 (29 de julio de 2019): 82. http://dx.doi.org/10.3390/urbansci3030082.
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Despite rapid changes in vehicle technology and the expansion of IT-based mobility solutions, travel habits must be changed to address the environmental and health implications of increasing car dependency. A significant amount of research focuses on commuting, which comprises the largest share of annual vehicle miles travelled. However, non-work trips are also significant, especially when considering trip frequency. Using empirical data (N = 1298) from an urban-rural region and bivariate statistical analysis, the relationship between the land use–transport configuration (6 types) and travel behaviour patterns is examined for 14 non-work destinations. The land use characterisation used in this research includes an updated means of representing a land use mix. By defining the typologies of land use and transport for use in the analysis, the findings can be directed towards contrasting area types in the region. A strong statistically significant association between the land use–transport configuration and mode-share for 14 non-work journey purposes is found. Using regression modelling, income and car ownership are identified as key influences on travel behaviour patterns. The results of both analyses show that, for non-work trips, the transport–land use relationship is as important as key socio-demographic indicators. However, the results for reductions in car travel are relatively small for the area typologies outside the inner-city core. This indicates that efforts to provide alternatives to car travel in order to mitigate car dependency should be prioritised in these outer urban areas. Appropriate management of spatial structure for non-work activity types such that active mode use is possible is essential. This will resolve some of the important environmental and health impacts of car dependency.
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Malokin, Aliaksandr, Giovanni Circella y Patricia L. Mokhtarian. "Do millennials value travel time differently because of productive multitasking? A revealed-preference study of Northern California commuters". Transportation 48, n.º 5 (12 de febrero de 2021): 2787–823. http://dx.doi.org/10.1007/s11116-020-10148-2.
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AbstractMillennials, the demographic cohort born in the last two decades of the twentieth century, are reported to adopt information and communication technologies (ICTs) in their everyday lives, including travel, to a greater extent than older generations. As ICT-driven travel-based multitasking influences travelers’ experience and satisfaction in various ways, millennials are expected to be affected at a greater scale. Still, to our knowledge, no previous studies have specifically focused on the impact of travel multitasking on travel behavior and the value of travel time (VOTT) of young adults. To address this gap, we use an original dataset collected among Northern California commuters (N = 2216) to analyze the magnitude and significance of individual and household-level factors affecting commute mode choice. We estimate a revealed-preference mode choice model and investigate the differences between millennials and older adults in the sample. Additionally, we conduct a sensitivity analysis to explore how incorporation of explanatory factors such as attitudes and propensity to multitask while traveling in mode choice models affects coefficient estimates, VOTT, and willingness to pay to use a laptop on the commute. Compared to non-millennials, the mode choice of millennials is found to be less affected by socio-economic characteristics and more strongly influenced by the activities performed while traveling. Young adults are found to have lower VOTT than older adults for both in-vehicle (15.0% less) and out-of-vehicle travel time (15.7% less), and higher willingness to pay (in time or money) to use a laptop, even after controlling for demographic traits, personal attitudes, and the propensity to multitask. This study contributes to better understanding the commuting behavior of millennials, and the factors affecting it, a topic of interest to transportation researchers, planners, and practitioners.
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Friel, Catherine, David Walsh, Bruce Whyte, Chris Dibben, Zhiqiang Feng, Graham Baker, Paul Kelly, Evangelia Demou y Ruth Dundas. "Health benefits of pedestrian and cyclist commuting: evidence from the Scottish Longitudinal Study". BMJ Public Health 2, n.º 1 (mayo de 2024): e001295. http://dx.doi.org/10.1136/bmjph-2024-001295.
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BackgroundDespite active travel investment increasing, evidence of benefit is often limited to selected health outcomes and a short follow-up period, and cyclists and pedestrians are often analysed together. We aimed to examine prospective associations with multiple health outcomes over 18 years for pedestrians and cyclists separately.MethodsThe Scottish Longitudinal Study is based on census data, from which we selected 82 297 individuals aged 16–74 years. Individuals were followed-up between 2001 and 2018 through linkage to hospitalisation, death and prescription records. Cox proportional hazard models were used to compare cyclist and pedestrian commuters with non-active commuters for a range of health outcomes, controlling for pre-existing health conditions, and demographic and socioeconomic characteristics.ResultsCompared with non-active commuting, cyclist commuting was associated with lower all-cause mortality risk (HR 0.53, 95% CI 0.38 to 0.73), lower risk of any hospitalisation (HR 0.90, 95% CI 0.84 to 0.97), lower risk of cardiovascular disease (CVD) hospitalisation (HR 0.76, 95% CI 0.64 to 0.91) and of having a CVD prescription (HR 0.70, 95% CI 0.63 to 0.78), lower risk of cancer mortality (HR 0.49, 95% CI 0.30 to 0.82) and cancer hospitalisation (HR 0.76, 95% CI 0.59 to 0.98), and lower risk of having a prescription for mental health problems (HR 0.80, 95% CI 0.73 to 0.89). Pedestrian commuting was associated with lower risk of any hospitalisation (HR 0.91, 95% CI 0.88 to 0.93), lower risk of CVD hospitalisation (HR 0.90, 95% CI 0.84 to 0.96) and of having a CVD prescription (HR 0.90, 95% CI 0.87 to 0.93), and lower risk of a mental health prescription (HR 0.93, 95% CI 0.90 to 0.97).ConclusionActive commuters were less likely to suffer from a range of negative physical and mental health outcomes than non-active commuters. These findings strengthen the evidence for the health benefits of active commuting.
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Oviedo, Daniel y Luis A. Guzman. "Revisiting Accessibility in a Context of Sustainable Transport: Capabilities and Inequalities in Bogotá". Sustainability 12, n.º 11 (1 de junio de 2020): 4464. http://dx.doi.org/10.3390/su12114464.
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This research sets out to examine the interaction between accessibility, social inequalities and sustainability by revisiting a well-documented case of inequalities in access in Global South cities: Bogotá. Our analysis builds on the concept of accessibility, focusing on the role of transport as an enabler of opportunities for social interactions, healthcare and leisure, which are essential to the full participation in society. The research applies a methodological framework for accessibility developed and tested in the Latin American context, though it has not been previously applied to non-commuting travel. Our paper contributes to the existing evidence base showing the relevance of non-commuting travel to sustainable transport assessment in contexts of high inequality, which can be scaled up and applied in other contexts with various levels of social and environmental inequalities. The empirical analysis is based on data from Bogotá’s household travel survey. Using this dataset, we measure accessibility using a gravitational type of metric that is calibrated based on observed travel behavior. Accessibility levels were estimated by car and public transport for every zonal planning unit in the Bogotá Region. Accessibility indices are analyzed from an equity perspective using metrics such as the Palma ratio for differences of income and socioeconomic positions. Results show that on average, low- and middle-income areas have higher accessibility than high-income areas by both private and public transport. Accessibility conditions are discussed considering a framework of transitions to sustainable urban mobility, reflecting on various drivers and consequences of barriers to access in different areas and social groups. Our findings provide insights to support actions that redistribute accessibility of opportunities beyond the job market, questioning the applicability of accessibility measures to discuss equity and sustainability in cities such as Bogotá.
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Hermaputi, Roosmayri Lovina y Chen Hua. "Decoding Jakarta Women’s Non-Working Travel-Mode Choice: Insights from Interpretable Machine-Learning Models". Sustainability 16, n.º 19 (28 de septiembre de 2024): 8454. http://dx.doi.org/10.3390/su16198454.
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Using survey data from three dwelling types in Jakarta, we examine how dwelling type, socioeconomic identity, and commuting distance affect women’s travel-mode choices and motivations behind women’s choices for nearby and distant non-working trips. We compared the performance of the multinomial logit (MNL) model with two machine-learning classifiers, random forest (RF) and XGBoost, using Shapley additive explanations (SHAP) for interpretation. The models’ efficacy varies across different datasets, with XGBoost mostly outperforming other models. The women’s preferred commuting modes varied by dwelling type and trip purpose, but their motives for choosing the nearest activity were similar. Over half of the women rely on private motorized vehicles, with women living in the gated community heavily relying on private cars. For nearby shopping trips, low income and young age discourage women in urban villages (kampungs) and apartment complexes from walking. Women living in gated communities often choose private cars to fulfill household responsibilities, enabling them to access distant options. For nearby leisure, longer commutes discourage walking except for residents of apartment complexes. Car ownership and household responsibilities increase private car use for distant options. SHAP analysis offers practitioners insights into identifying key variables affecting travel-mode choice to design effective targeted interventions that address women’s mobility needs.
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Wan, Li, Junqing Tang, Lihua Wang y Jennifer Schooling. "Understanding non-commuting travel demand of car commuters – Insights from ANPR trip chain data in Cambridge". Transport Policy 106 (junio de 2021): 76–87. http://dx.doi.org/10.1016/j.tranpol.2021.03.021.
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