Nick Van Nijen, M. B. Ulak, Sander Veenstra, K. Geurs
Cycling is one of the main transport modes and cycling infrastructure is strongly embedded in transport infrastructure in the Netherlands. Nonetheless, the bicycle network still undergoes frequent improvements and expansions. One of the critical elements in deciding on improvements and expansions is to understand the route choice of cyclists, which helps identify bottlenecks in bicycle flows and substantiate the need for new bicycle infrastructure. Yet, the factors affecting the route choice of cyclists are still not fully understood. To address this, we develop a varying-contiguity spatially lagged exogenous (VCSLX) model and analyze the probability of a cyclist choosing a certain segment based not only on the characteristics of that segment but also considering the characteristics of its neighbors along a route. Characteristics that are included in this study are the presence of bicycle infrastructure, traffic control installations and artificial lighting, as well as pavement type, bicycle and motorized-vehicle volumes and different land-use zones. The model involves the analysis of the observed routes extracted from cycling trajectories from Fietstelweek data, as well as corresponding hypothetical shortest path routes identified from the origin-destinations of the observed trips and the cycling network. The results of the study can help to understand the factors convincing cyclists to deviate from the shortest possible routes. The study contributes to the current literature by focusing on the underexplored aspect of spatial dependencies between route segments in the route choice of cyclists.
{"title":"Exploring factors affecting route choice of cyclists: A novel varying-contiguity spatially lagged exogenous modeling approach","authors":"Nick Van Nijen, M. B. Ulak, Sander Veenstra, K. Geurs","doi":"10.5198/jtlu.2024.2452","DOIUrl":"https://doi.org/10.5198/jtlu.2024.2452","url":null,"abstract":"Cycling is one of the main transport modes and cycling infrastructure is strongly embedded in transport infrastructure in the Netherlands. Nonetheless, the bicycle network still undergoes frequent improvements and expansions. One of the critical elements in deciding on improvements and expansions is to understand the route choice of cyclists, which helps identify bottlenecks in bicycle flows and substantiate the need for new bicycle infrastructure. Yet, the factors affecting the route choice of cyclists are still not fully understood. To address this, we develop a varying-contiguity spatially lagged exogenous (VCSLX) model and analyze the probability of a cyclist choosing a certain segment based not only on the characteristics of that segment but also considering the characteristics of its neighbors along a route. Characteristics that are included in this study are the presence of bicycle infrastructure, traffic control installations and artificial lighting, as well as pavement type, bicycle and motorized-vehicle volumes and different land-use zones. The model involves the analysis of the observed routes extracted from cycling trajectories from Fietstelweek data, as well as corresponding hypothetical shortest path routes identified from the origin-destinations of the observed trips and the cycling network. The results of the study can help to understand the factors convincing cyclists to deviate from the shortest possible routes. The study contributes to the current literature by focusing on the underexplored aspect of spatial dependencies between route segments in the route choice of cyclists.","PeriodicalId":47271,"journal":{"name":"Journal of Transport and Land Use","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141655037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Car-free development has become popular in recent years due to concerns regarding transport-related health issues in urban areas as well as a growing trend toward sustainability and environmentally friendly living. Although car-free development is regarded as progress to promote active transport modes and healthier cities, the accessibility impacts for its residents remain unclear. To address this knowledge gap, this paper proposes a job accessibility assessment framework that integrates individual and household socio-demographic characteristics into a job accessibility assessment, making it possible to account for commuting preferences of different population groups in accessibility analyses. For this purpose, a stated choice survey was conducted in existing low-car areas in the Netherlands to determine transport use and perception of public transport trip characteristics. Then, the influence of socio-demographic characteristics on trip perceptions was analyzed using a Latent Class Logit (LCL) regression model and Monte Carlo simulations. Finally, a multi-modal transport network combining walking and public transport trips was used to assess potential job accessibility levels of different population groups in a car-free development area. The proposed framework was implemented in a case study in the province of Utrecht (the Netherlands). Results show notable differences between the job accessibility levels within different population groups, reflecting distinct perceptions toward commuting trip characteristics based on socio-demographic characteristics and demonstrating the suitability of the applied approach to assess accessibility levels in car-free development areas. Compared to the sample average distribution, more than 15% lower accessibility levels were observed for starters (age 18-35) in some urban areas, indicating the aversion to longer and more expensive commuting trips. Contrarily, increased accessibility levels for families (>2 persons in household) were observed, demonstrating the acceptance to experience longer commuting travel times and additional costs. No differences were observed between accessibility levels of the sample average and senior adults (age >50).
{"title":"A framework to include socio-demographic characteristics in potential job accessibility levels in low-car and car-free development areas in the Netherlands","authors":"Rutger Meester, M. B. Ulak, K. Geurs","doi":"10.5198/jtlu.2024.2275","DOIUrl":"https://doi.org/10.5198/jtlu.2024.2275","url":null,"abstract":"Car-free development has become popular in recent years due to concerns regarding transport-related health issues in urban areas as well as a growing trend toward sustainability and environmentally friendly living. Although car-free development is regarded as progress to promote active transport modes and healthier cities, the accessibility impacts for its residents remain unclear. To address this knowledge gap, this paper proposes a job accessibility assessment framework that integrates individual and household socio-demographic characteristics into a job accessibility assessment, making it possible to account for commuting preferences of different population groups in accessibility analyses. For this purpose, a stated choice survey was conducted in existing low-car areas in the Netherlands to determine transport use and perception of public transport trip characteristics. Then, the influence of socio-demographic characteristics on trip perceptions was analyzed using a Latent Class Logit (LCL) regression model and Monte Carlo simulations. Finally, a multi-modal transport network combining walking and public transport trips was used to assess potential job accessibility levels of different population groups in a car-free development area. The proposed framework was implemented in a case study in the province of Utrecht (the Netherlands). Results show notable differences between the job accessibility levels within different population groups, reflecting distinct perceptions toward commuting trip characteristics based on socio-demographic characteristics and demonstrating the suitability of the applied approach to assess accessibility levels in car-free development areas. Compared to the sample average distribution, more than 15% lower accessibility levels were observed for starters (age 18-35) in some urban areas, indicating the aversion to longer and more expensive commuting trips. Contrarily, increased accessibility levels for families (>2 persons in household) were observed, demonstrating the acceptance to experience longer commuting travel times and additional costs. No differences were observed between accessibility levels of the sample average and senior adults (age >50).","PeriodicalId":47271,"journal":{"name":"Journal of Transport and Land Use","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141660185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Analyzing the balance of station passenger and passenger flow is essential for understanding jobs-housing balance and built environment in station areas and network-wide range as well as for enhancing the efficiency of urban rail transit operations. Taking the Shanghai rail transit network as a case study, this paper defines the Multiscale Subnetwork (MSSN) based on a specific spatial scope. By extracting the network features and built-environment elements of the stations and the MSSN, this study analyzes the factors affecting the peak-hour station passenger and the imbalance of regional network passenger flow. The research suggests that the small MSSN analysis, within 6-8 km from a station, can provide valuable results from a network-wide perspective, rather than solely focusing on individual station areas or the entire network. The regional attributes of jobs-housing balance and the transportation conditions in the MSSN range have great impact on both station passengers and flow imbalance. This research provides theoretical insights for urban planners and policymakers to formulate effective strategies for urban rail transit networks.
{"title":"Effect of multiscale metro network-wide attributes on peak-hour station passenger and flow balancing","authors":"Haixiao Pan, Miao Hu, Xiyin Deng, Ailing Liu","doi":"10.5198/jtlu.2024.2443","DOIUrl":"https://doi.org/10.5198/jtlu.2024.2443","url":null,"abstract":"Analyzing the balance of station passenger and passenger flow is essential for understanding jobs-housing balance and built environment in station areas and network-wide range as well as for enhancing the efficiency of urban rail transit operations. Taking the Shanghai rail transit network as a case study, this paper defines the Multiscale Subnetwork (MSSN) based on a specific spatial scope. By extracting the network features and built-environment elements of the stations and the MSSN, this study analyzes the factors affecting the peak-hour station passenger and the imbalance of regional network passenger flow. The research suggests that the small MSSN analysis, within 6-8 km from a station, can provide valuable results from a network-wide perspective, rather than solely focusing on individual station areas or the entire network. The regional attributes of jobs-housing balance and the transportation conditions in the MSSN range have great impact on both station passengers and flow imbalance. This research provides theoretical insights for urban planners and policymakers to formulate effective strategies for urban rail transit networks.","PeriodicalId":47271,"journal":{"name":"Journal of Transport and Land Use","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141660901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cristina Bircu, F. Cavallaro, Gianfranco Pozzer, S. Nocera
The Covid-19 pandemic has affected the travel behavior of commuters, with soft modes emerging as reliable options for short-distance trips. This research focuses on evaluating the bike-friendliness of Venice, Italy, a unique city for its morphological and mobility characteristics. When considering daily commuting between the mainland and the historic city center in the lagoon, the bicycle is not an adopted solution. Yet, the recent construction of a bicycle and pedestrian path that runs alongside the main bridge between the mainland and historical city could alleviate the pressure on public transport and the use of cars, especially in peak hours. This contribution evaluates the potential for using bicycles to reach the historic center of Venice from the mainland, and the appropriateness of the infrastructural equipment. The quantitative analysis examines the current supply and demand in absolute values and in terms of modal share. Projecting the number of actual users under different scenarios until 2030, in accordance with the Venice Sustainable Urban Mobility Plan and other relevant plans, the inadequate provision of parking areas for bikes emerges as an unsolved issue. A revision of the mobility layout is thus required if bicycles are expected to be a competitive alternative solution.
{"title":"Exploring the prospects and challenges of sustainable urban mobility: Potential and limits of cycling in Venice","authors":"Cristina Bircu, F. Cavallaro, Gianfranco Pozzer, S. Nocera","doi":"10.5198/jtlu.2024.2448","DOIUrl":"https://doi.org/10.5198/jtlu.2024.2448","url":null,"abstract":"The Covid-19 pandemic has affected the travel behavior of commuters, with soft modes emerging as reliable options for short-distance trips. This research focuses on evaluating the bike-friendliness of Venice, Italy, a unique city for its morphological and mobility characteristics. When considering daily commuting between the mainland and the historic city center in the lagoon, the bicycle is not an adopted solution. Yet, the recent construction of a bicycle and pedestrian path that runs alongside the main bridge between the mainland and historical city could alleviate the pressure on public transport and the use of cars, especially in peak hours. This contribution evaluates the potential for using bicycles to reach the historic center of Venice from the mainland, and the appropriateness of the infrastructural equipment. The quantitative analysis examines the current supply and demand in absolute values and in terms of modal share. Projecting the number of actual users under different scenarios until 2030, in accordance with the Venice Sustainable Urban Mobility Plan and other relevant plans, the inadequate provision of parking areas for bikes emerges as an unsolved issue. A revision of the mobility layout is thus required if bicycles are expected to be a competitive alternative solution.","PeriodicalId":47271,"journal":{"name":"Journal of Transport and Land Use","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141118014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaowei Li, Lanxin Shi, Ju Tang, Jiaying Li, Pengjun Zhao, Qian Liu, Jun Chen, Changxi Ma
The impact of the built environment and weather conditions on travel behavior has been widely studied. However, limited studies have focused on better understanding such effects in medium-sized cities with bus-oriented transit systems, particularly from a separate perspective of travelers’ origins and destinations. We took Weinan, China, as a representative of second-tier cities in developing countries that concentrate on bus-oriented development strategies. New evidence of feature importance and nonlinear effects of crucial factors were revealed by an interpretable machine learning-based approach combining XGBoost and Shapley Additive Explanation (SHAP) with multi-source data. Most key factors were critical at both origins and destinations, such as the density of residential and commercial facilities. However, several important factors, such as road density and boarding time, had strong imbalanced effects on travel behavior. These findings provide novel insights and empirical implications to support urban planning strategies in medium-sized cities.
{"title":"Effects of the built environment on travel distance in bus-oriented, medium-sized cities in China","authors":"Xiaowei Li, Lanxin Shi, Ju Tang, Jiaying Li, Pengjun Zhao, Qian Liu, Jun Chen, Changxi Ma","doi":"10.5198/jtlu.2024.2427","DOIUrl":"https://doi.org/10.5198/jtlu.2024.2427","url":null,"abstract":"The impact of the built environment and weather conditions on travel behavior has been widely studied. However, limited studies have focused on better understanding such effects in medium-sized cities with bus-oriented transit systems, particularly from a separate perspective of travelers’ origins and destinations. We took Weinan, China, as a representative of second-tier cities in developing countries that concentrate on bus-oriented development strategies. New evidence of feature importance and nonlinear effects of crucial factors were revealed by an interpretable machine learning-based approach combining XGBoost and Shapley Additive Explanation (SHAP) with multi-source data. Most key factors were critical at both origins and destinations, such as the density of residential and commercial facilities. However, several important factors, such as road density and boarding time, had strong imbalanced effects on travel behavior. These findings provide novel insights and empirical implications to support urban planning strategies in medium-sized cities.","PeriodicalId":47271,"journal":{"name":"Journal of Transport and Land Use","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141113978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maryam Bostanara, Amarin Siripanich, M. Ghasri, Taha Hossein Rashidi
This study investigates household residential relocation timing, an aspect vital for transport and urban planning. Analyzing a high-dimensional dataset from 1,024 relocations in Sydney, Australia, the research contrasts ten machine learning survival techniques with three classical survival models. Results indicate that when classical models are paired with tree-based automated feature selectors, they align closely with machine learning outcomes. Notably, the GBM, XGBoost, and Random Forest models emerge as standout performers. The study provides a comprehensive comparison between automatic and manual feature selection, shedding light on variables influencing households’ duration of stay. While stacked ensemble modeling, which leverages predictions from various models, is used to enhance accuracy, the improvements are marginal, underscoring inherent modeling challenges, particularly the recurring issue of misclassifying specific pairs of households in the concordance index measure. A thorough feature analysis highlights homeownership as the foremost predictor, underscoring the importance of recent life events and accessibility features in relocation decisions. The research emphasizes the importance of considering the accessibility of both current and future homes in relocation models, with 20% feature significance in model outcomes. Building on these foundational insights, the study paves the way for a deeper understanding of individual decision-making processes in sustainable urban planning.
{"title":"Sydney’s residential relocation landscape: Machine learning and feature selection methods unpack the whys and whens","authors":"Maryam Bostanara, Amarin Siripanich, M. Ghasri, Taha Hossein Rashidi","doi":"10.5198/jtlu.2024.2440","DOIUrl":"https://doi.org/10.5198/jtlu.2024.2440","url":null,"abstract":"This study investigates household residential relocation timing, an aspect vital for transport and urban planning. Analyzing a high-dimensional dataset from 1,024 relocations in Sydney, Australia, the research contrasts ten machine learning survival techniques with three classical survival models. Results indicate that when classical models are paired with tree-based automated feature selectors, they align closely with machine learning outcomes. Notably, the GBM, XGBoost, and Random Forest models emerge as standout performers. The study provides a comprehensive comparison between automatic and manual feature selection, shedding light on variables influencing households’ duration of stay. While stacked ensemble modeling, which leverages predictions from various models, is used to enhance accuracy, the improvements are marginal, underscoring inherent modeling challenges, particularly the recurring issue of misclassifying specific pairs of households in the concordance index measure. A thorough feature analysis highlights homeownership as the foremost predictor, underscoring the importance of recent life events and accessibility features in relocation decisions. The research emphasizes the importance of considering the accessibility of both current and future homes in relocation models, with 20% feature significance in model outcomes. Building on these foundational insights, the study paves the way for a deeper understanding of individual decision-making processes in sustainable urban planning.","PeriodicalId":47271,"journal":{"name":"Journal of Transport and Land Use","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141126493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniela Arias Molinares, Rubén Talavera-García, Gustavo Romanillos-Arroyo, Juan Carlos García Palomares
Journey planners could be one of the most relevant aspects to consider when choosing and deciding our daily trips. However, many of these trip apps still do not consider the new forms of mobility that are emerging in cities, also known as micromobility services (shared bikes, mopeds and scooters). In this study, we pursue two main objectives. On one hand, we create a journey planner for micromobility in Madrid. On the other hand, we use the journey planner to estimate and analyze micromobility flow considering the origin and destination points of trips registered in 2019 from the three different shared modes. Our results involve a series of maps that illustrate how micromobility flow is distributed in the city and the different dynamics considering two scenarios (weekdays and weekends). The journey planner helps to visualize those streets where micromobility flow concentrates, making micromobility users more visible and thus promoting that their paths become safer, attracting new users to start using micromobility (positive loop). Also, the maps could help policy planners to allocate new infrastructure in the city where it is needed most.
{"title":"On the path to develop a micromobility journey planner for Madrid: A tool to estimate, visualize, and analyze cycling and other shared mobility services’ flow","authors":"Daniela Arias Molinares, Rubén Talavera-García, Gustavo Romanillos-Arroyo, Juan Carlos García Palomares","doi":"10.5198/jtlu.2024.2451","DOIUrl":"https://doi.org/10.5198/jtlu.2024.2451","url":null,"abstract":"Journey planners could be one of the most relevant aspects to consider when choosing and deciding our daily trips. However, many of these trip apps still do not consider the new forms of mobility that are emerging in cities, also known as micromobility services (shared bikes, mopeds and scooters). In this study, we pursue two main objectives. On one hand, we create a journey planner for micromobility in Madrid. On the other hand, we use the journey planner to estimate and analyze micromobility flow considering the origin and destination points of trips registered in 2019 from the three different shared modes. Our results involve a series of maps that illustrate how micromobility flow is distributed in the city and the different dynamics considering two scenarios (weekdays and weekends). The journey planner helps to visualize those streets where micromobility flow concentrates, making micromobility users more visible and thus promoting that their paths become safer, attracting new users to start using micromobility (positive loop). Also, the maps could help policy planners to allocate new infrastructure in the city where it is needed most.","PeriodicalId":47271,"journal":{"name":"Journal of Transport and Land Use","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140974803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Long-range planning is an uncertain endeavor. This is especially true for urban regions, small ships in a global urban storm that are too small to influence macro policies and without the land-use powers of local governments. Exploratory scenarios, the established practice for planning under deep uncertainty, have inspired stakeholders to consider multiple futures but have fallen short of identifying robust and contingent policies. We need new tools to plan under conditions of deep uncertainty. Scenario discovery is a technique for using simulation models to explore the performance of policy options across uncertain scenarios. This paper presents an application of scenario discovery in land-use modeling and asks what this computationally intensive approach offers relative to a more circumscribed exploration of uncertainty space. The introduction of autonomous vehicles (AVs) and their associated impacts on land use provide a test case demonstrating this method, as well as a topic of substantive concern. This research concludes that scenario discovery is particularly valuable for identifying the conditions under which contingent policies are likely to succeed. In terms of AV policy, this research establishes that forward-thinking, transit-oriented-development strategies can mitigate spatial dispersion while also reducing overall housing costs. In addition, I find that AVs may blunt the impacts of some current policy tools if they extend the distance individuals are willing to travel to work.
{"title":"The value of scenario discovery in land-use modeling: An automated vehicle test case","authors":"Daniel Engelberg","doi":"10.5198/jtlu.2024.2401","DOIUrl":"https://doi.org/10.5198/jtlu.2024.2401","url":null,"abstract":"Long-range planning is an uncertain endeavor. This is especially true for urban regions, small ships in a global urban storm that are too small to influence macro policies and without the land-use powers of local governments. Exploratory scenarios, the established practice for planning under deep uncertainty, have inspired stakeholders to consider multiple futures but have fallen short of identifying robust and contingent policies. We need new tools to plan under conditions of deep uncertainty. Scenario discovery is a technique for using simulation models to explore the performance of policy options across uncertain scenarios. This paper presents an application of scenario discovery in land-use modeling and asks what this computationally intensive approach offers relative to a more circumscribed exploration of uncertainty space. The introduction of autonomous vehicles (AVs) and their associated impacts on land use provide a test case demonstrating this method, as well as a topic of substantive concern. This research concludes that scenario discovery is particularly valuable for identifying the conditions under which contingent policies are likely to succeed. In terms of AV policy, this research establishes that forward-thinking, transit-oriented-development strategies can mitigate spatial dispersion while also reducing overall housing costs. In addition, I find that AVs may blunt the impacts of some current policy tools if they extend the distance individuals are willing to travel to work.","PeriodicalId":47271,"journal":{"name":"Journal of Transport and Land Use","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140994665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Promoting sustainable mobility systems by encouraging the use of the bicycle as a transport mode is now a public policy objective. This political will is also pursued in France where the modal share of cycling is relatively low. However, young people and those with a high level of human capital, such as members of the university community, are observed to be more advanced in their adoption of cycling. An understanding of how cycling is used by university students and staff would therefore help to inform public decision-making and support more efficient targeted policies to develop this mode of transport. Using original data from the MobiCampus-UdL project, the aim of this article is to analyze the determinants of bicycle use by the university community at the University of Lyon, France. Two multivariate logistic regression models are estimated on the subsamples of students and staff: one explaining the probability of using the bicycle as an exclusive mode of transport to get to the campus and the other explaining the probability of using the bicycle in combination with other modes. Our results suggest that while socio-demographic characteristics have little influence within our two relatively homogeneous subsamples, access to mobility resources and the spatial characteristics of the campus and place of residence are crucial. We also find that access to bicycles is an important determinant of the utilization of cycling. Given that the adoption of cycling is still very low, our findings justify policies to increase the availability of bicycles and subsidize their purchase. More specifically, our results suggest that access to a shared bike station on campus encourages the exclusive use of bicycles by students and staff but has no effect when used in combination with other modes. On the other hand, good accessibility to public transport, whether from home or from campus, does not reduce the use of bicycles by either sub-population, either exclusively or in combination. Furthermore, while living far from the city center is an obstacle to the exclusive use of the bicycles, especially for staff, it does not in any way prevent their use in combination with other modes, such as the train. These results open up new avenues for anticipating the development of intermodality between public transport and cycling.
{"title":"Bicycle use in the university community: Empirical analysis using MobiCampus-UdL data (Lyon, France)","authors":"Nathalie Havet, L. Bouzouina","doi":"10.5198/jtlu.2024.2450","DOIUrl":"https://doi.org/10.5198/jtlu.2024.2450","url":null,"abstract":"Promoting sustainable mobility systems by encouraging the use of the bicycle as a transport mode is now a public policy objective. This political will is also pursued in France where the modal share of cycling is relatively low. However, young people and those with a high level of human capital, such as members of the university community, are observed to be more advanced in their adoption of cycling. An understanding of how cycling is used by university students and staff would therefore help to inform public decision-making and support more efficient targeted policies to develop this mode of transport. Using original data from the MobiCampus-UdL project, the aim of this article is to analyze the determinants of bicycle use by the university community at the University of Lyon, France. Two multivariate logistic regression models are estimated on the subsamples of students and staff: one explaining the probability of using the bicycle as an exclusive mode of transport to get to the campus and the other explaining the probability of using the bicycle in combination with other modes. Our results suggest that while socio-demographic characteristics have little influence within our two relatively homogeneous subsamples, access to mobility resources and the spatial characteristics of the campus and place of residence are crucial. We also find that access to bicycles is an important determinant of the utilization of cycling. Given that the adoption of cycling is still very low, our findings justify policies to increase the availability of bicycles and subsidize their purchase. More specifically, our results suggest that access to a shared bike station on campus encourages the exclusive use of bicycles by students and staff but has no effect when used in combination with other modes. On the other hand, good accessibility to public transport, whether from home or from campus, does not reduce the use of bicycles by either sub-population, either exclusively or in combination. Furthermore, while living far from the city center is an obstacle to the exclusive use of the bicycles, especially for staff, it does not in any way prevent their use in combination with other modes, such as the train. These results open up new avenues for anticipating the development of intermodality between public transport and cycling.","PeriodicalId":47271,"journal":{"name":"Journal of Transport and Land Use","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140657049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The impacts of transit-oriented development (TOD) on travel behavior have been extensively studied, with a predominant focus on cross-sectional analyses that provide a static evaluation at a specific point in time by comparing TODs and non-TODs. Longitudinal assessments that capture changes in behavior over time remain relatively uncommon, and the literature tends to overlook differences in evaluating TOD effects across cross-sectional and longitudinal analyses. Additionally, the role of trip purpose as a significant but unexplored variable influencing the degree of TOD effects is often disregarded. To address these gaps, this systematic review examines 48 quantitative studies, comparing the effects of TOD on travel behavior from cross-sectional and longitudinal perspectives, restructuring indicators of effects into transit use, non-motorized travel, vehicle dependence, and vehicle ownership, and differentiating the effects by trip purpose. A metric has been introduced to quantitatively assess the impact of TOD on travel behavior. The pooled results indicate that private vehicle usage remains high in TOD areas, particularly for non-commuting trips, and that the longitudinal effects of TOD are limited and potentially influenced by individual travel attitudes, residential self-selection, and long-term travel habit change. Furthermore, the methodological differences between cross-sectional and longitudinal studies may lead to divergent conclusions regarding the effects of TOD on travel behavior. Our analysis sheds light on the importance of carefully selecting an appropriate method for a given research question to maximize the accuracy and relevance of the findings. Combining TOD and shared mobility can create a more efficient multi-model transport network that meets the diverse needs of city residents and improves accessibility for all. Overall, this review provides new insights into the impacts of TOD on travel behavior and supports the potential for a paradigm shift toward multimodal transport through the integration of TOD and shared mobility.
以公交为导向的开发（TOD）对出行行为的影响已得到广泛研究，主要集中在横断面分析上，通过比较 TOD 和非 TOD，提供特定时间点的静态评估。捕捉行为随时间变化的纵向评估仍相对少见，而且文献往往忽略了横截面分析和纵向分析在评估 TOD 效果方面的差异。此外，作为影响 TOD 效应程度的一个重要变量，出行目的的作用往往被忽视，但这一问题尚未得到探讨。为了弥补这些不足，本系统性综述审查了 48 项定量研究，从横截面和纵向角度比较了 TOD 对出行行为的影响，将影响指标重组为公交使用、非机动化出行、车辆依赖性和车辆拥有量，并按出行目的区分影响。此外，还引入了一个指标来量化评估 TOD 对出行行为的影响。汇总结果表明，在 TOD 地区，私家车的使用率仍然很高，尤其是非通勤出行，而且 TOD 的纵向影响有限，可能受到个人出行态度、居住地自我选择和长期出行习惯改变的影响。此外，横断面研究和纵向研究在方法上的差异可能会导致关于 TOD 对出行行为影响的不同结论。我们的分析揭示了针对特定研究问题谨慎选择适当方法的重要性，从而最大限度地提高研究结果的准确性和相关性。将 TOD 与共享交通结合起来，可以创建一个更高效的多模式交通网络，满足城市居民的不同需求，并改善所有人的交通可达性。总之，本综述就 TOD 对出行行为的影响提供了新的见解，并支持通过整合 TOD 和共享交通向多式联运模式转变的潜力。
{"title":"TOD effects on travel behavior: A synthesis of evidence from cross-sectional and longitudinal studies","authors":"Bin Chi, Jinwoo Lee","doi":"10.5198/jtlu.2024.2417","DOIUrl":"https://doi.org/10.5198/jtlu.2024.2417","url":null,"abstract":"The impacts of transit-oriented development (TOD) on travel behavior have been extensively studied, with a predominant focus on cross-sectional analyses that provide a static evaluation at a specific point in time by comparing TODs and non-TODs. Longitudinal assessments that capture changes in behavior over time remain relatively uncommon, and the literature tends to overlook differences in evaluating TOD effects across cross-sectional and longitudinal analyses. Additionally, the role of trip purpose as a significant but unexplored variable influencing the degree of TOD effects is often disregarded. To address these gaps, this systematic review examines 48 quantitative studies, comparing the effects of TOD on travel behavior from cross-sectional and longitudinal perspectives, restructuring indicators of effects into transit use, non-motorized travel, vehicle dependence, and vehicle ownership, and differentiating the effects by trip purpose. A metric has been introduced to quantitatively assess the impact of TOD on travel behavior. The pooled results indicate that private vehicle usage remains high in TOD areas, particularly for non-commuting trips, and that the longitudinal effects of TOD are limited and potentially influenced by individual travel attitudes, residential self-selection, and long-term travel habit change. Furthermore, the methodological differences between cross-sectional and longitudinal studies may lead to divergent conclusions regarding the effects of TOD on travel behavior. Our analysis sheds light on the importance of carefully selecting an appropriate method for a given research question to maximize the accuracy and relevance of the findings. Combining TOD and shared mobility can create a more efficient multi-model transport network that meets the diverse needs of city residents and improves accessibility for all. Overall, this review provides new insights into the impacts of TOD on travel behavior and supports the potential for a paradigm shift toward multimodal transport through the integration of TOD and shared mobility.","PeriodicalId":47271,"journal":{"name":"Journal of Transport and Land Use","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140724053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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