Pub Date : 2026-01-09DOI: 10.1007/s11116-025-10716-4
Ingrid Johansson, Hans Sipilä, Carl-William Palmqvist
The railway transport system has seen an increasing demand in recent years, while delays and missed punctuality goals continue to be problems in many countries. To improve punctuality, the amount of primary delays needs to be decreased, and knowledge of the shares of the different types of delay – entry, run, and dwell – is important to identify the most efficient countermeasures. This paper investigates the punctuality in the three Swedish metropolitan regions around Stockholm, Gothenburg, and Malmö, applying Circumscribed Central Composite Design in the calibration of a macroscopic simulation tool. The results show that the ratio of primary to secondary delays varied from 1:1.8 to 1:3.8 between the geographical regions, and that the mix of primary entry, run, and dwell delays can vary substantially between regions. In all cases, the primary delays need to decrease by well over $$40%$$ to reach the goal of $$95%$$ punctuality, highlighting the importance of reducing primary dwell delays to improve punctuality. For simulation purposes, our results highlight that large networks require careful calibration, as key parameters and inputs vary significantly between different parts of the network. Future work includes experimenting with iterated calibration runs, modelling the prediction error between simulated and observed punctuality, simulating a larger network while allowing for regional differences in input settings and distributions, investigating the potential relationship between capacity utilisation and the occurrence of secondary delays, and exploring the possibility of automating the calibration process.
{"title":"Simulating railway punctuality in three Swedish metropolitan regions","authors":"Ingrid Johansson, Hans Sipilä, Carl-William Palmqvist","doi":"10.1007/s11116-025-10716-4","DOIUrl":"https://doi.org/10.1007/s11116-025-10716-4","url":null,"abstract":"The railway transport system has seen an increasing demand in recent years, while delays and missed punctuality goals continue to be problems in many countries. To improve punctuality, the amount of primary delays needs to be decreased, and knowledge of the shares of the different types of delay – entry, run, and dwell – is important to identify the most efficient countermeasures. This paper investigates the punctuality in the three Swedish metropolitan regions around Stockholm, Gothenburg, and Malmö, applying Circumscribed Central Composite Design in the calibration of a macroscopic simulation tool. The results show that the ratio of primary to secondary delays varied from 1:1.8 to 1:3.8 between the geographical regions, and that the mix of primary entry, run, and dwell delays can vary substantially between regions. In all cases, the primary delays need to decrease by well over <jats:inline-formula> <jats:tex-math>$$40%$$</jats:tex-math> </jats:inline-formula> to reach the goal of <jats:inline-formula> <jats:tex-math>$$95%$$</jats:tex-math> </jats:inline-formula> punctuality, highlighting the importance of reducing primary dwell delays to improve punctuality. For simulation purposes, our results highlight that large networks require careful calibration, as key parameters and inputs vary significantly between different parts of the network. Future work includes experimenting with iterated calibration runs, modelling the prediction error between simulated and observed punctuality, simulating a larger network while allowing for regional differences in input settings and distributions, investigating the potential relationship between capacity utilisation and the occurrence of secondary delays, and exploring the possibility of automating the calibration process.","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"21 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145947256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-09DOI: 10.1007/s11116-025-10714-6
Haotian Su, Nazmul A. Khan, Krishna M. Gurumurthy, Joseph Paul, Rakesh Gangadharaiah, Lisa Boor, Kristin Kolodge, Joshua Auld, Johnell O. Brooks, Yunyi Jia
Ridesharing has become an increasingly popular transportation method over the past decade. Transportation network companies such as Uber and Lyft generally provide two types of rideshare services: personal rideshare, in which users ride alone or with individuals they know, and pooled rideshare, in which users ride with passengers they do not know but share similar routes. Pooled rideshare is capable of reducing energy consumption and traffic in the transportation system in comparison to personal rideshare. Despite the growth in trip volume, ridesharing usage is still low compared to other popular transportation methods in the U.S., particularly traveling in one’s own personal vehicle. Furthermore, pooled rideshare usage is lower than personal rideshare. To understand riders’ preferences, a national survey ( N = 2884) was conducted in the U.S. to investigate users’ choice behaviors in rideshare services examining personal versus pooled rideshare. Each survey respondent completed 20 stated-preference scenarios where participants choose between a personal or pooled rideshare option. Based on the responses, a mixed logit model was developed to capture the choice behavior preferences of the participants. The model unveiled the impact of demographic and trip attribute variables on users’ rideshare preferences. The discussion encompassed insights into demographic backgrounds and trip attributes, accompanied by a set of policy recommendations aimed at enhancing future pooled rideshare utilization.
{"title":"Analyzing users’ preferences between personal and pooled rideshare services using a mixed logit modeling approach","authors":"Haotian Su, Nazmul A. Khan, Krishna M. Gurumurthy, Joseph Paul, Rakesh Gangadharaiah, Lisa Boor, Kristin Kolodge, Joshua Auld, Johnell O. Brooks, Yunyi Jia","doi":"10.1007/s11116-025-10714-6","DOIUrl":"https://doi.org/10.1007/s11116-025-10714-6","url":null,"abstract":"Ridesharing has become an increasingly popular transportation method over the past decade. Transportation network companies such as Uber and Lyft generally provide two types of rideshare services: personal rideshare, in which users ride alone or with individuals they know, and pooled rideshare, in which users ride with passengers they do not know but share similar routes. Pooled rideshare is capable of reducing energy consumption and traffic in the transportation system in comparison to personal rideshare. Despite the growth in trip volume, ridesharing usage is still low compared to other popular transportation methods in the U.S., particularly traveling in one’s own personal vehicle. Furthermore, pooled rideshare usage is lower than personal rideshare. To understand riders’ preferences, a national survey ( <jats:italic>N</jats:italic> = 2884) was conducted in the U.S. to investigate users’ choice behaviors in rideshare services examining personal versus pooled rideshare. Each survey respondent completed 20 stated-preference scenarios where participants choose between a personal or pooled rideshare option. Based on the responses, a mixed logit model was developed to capture the choice behavior preferences of the participants. The model unveiled the impact of demographic and trip attribute variables on users’ rideshare preferences. The discussion encompassed insights into demographic backgrounds and trip attributes, accompanied by a set of policy recommendations aimed at enhancing future pooled rideshare utilization.","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"65 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145947216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-06DOI: 10.1007/s11116-025-10706-6
Adam Krathaus, Gongda Yu, Irina Benedyk, Panagiotis Ch. Anastasopoulos
This paper investigates the relationship between social networks and the activities they generate, by exploring inter-social-activity durations as a proposed measure of social activity participation frequency. To model the proposed measure, data were collected and processed from a publicly-available dataset sourced from the location-based social networking service Gowalla. The data include information from 3065 Texas Gowalla users, regarding social activity-travel behavior, and performance of modularity- and surprise-based community detection. To account for the longitudinal nature of the data, and for possible spatial instability of the model parameters across two major Texas cities, a grouped-random-parameters hazard-based duration modeling approach with heterogeneity in means is employed, and separate models are estimated for Austin and Dallas users. The results suggest that social activity participation frequency is affected by individual mobility, and by a number of social network effects, such as ego social network size, social group variety, and local closeness centrality. The findings call for a thorough investigation of the transportation system and social network interrelationships.
{"title":"Impacts of mobility and social networks on social activity-travel participation using location-based social network data","authors":"Adam Krathaus, Gongda Yu, Irina Benedyk, Panagiotis Ch. Anastasopoulos","doi":"10.1007/s11116-025-10706-6","DOIUrl":"https://doi.org/10.1007/s11116-025-10706-6","url":null,"abstract":"This paper investigates the relationship between social networks and the activities they generate, by exploring inter-social-activity durations as a proposed measure of social activity participation frequency. To model the proposed measure, data were collected and processed from a publicly-available dataset sourced from the location-based social networking service Gowalla. The data include information from 3065 Texas Gowalla users, regarding social activity-travel behavior, and performance of modularity- and surprise-based community detection. To account for the longitudinal nature of the data, and for possible spatial instability of the model parameters across two major Texas cities, a grouped-random-parameters hazard-based duration modeling approach with heterogeneity in means is employed, and separate models are estimated for Austin and Dallas users. The results suggest that social activity participation frequency is affected by individual mobility, and by a number of social network effects, such as ego social network size, social group variety, and local closeness centrality. The findings call for a thorough investigation of the transportation system and social network interrelationships.","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"40 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-20DOI: 10.1007/s11116-025-10710-w
Yunting Miao, Jiangping Zhou
In high-density cities, metro riders’ activities often extend beyond boundaries of one station’s typical service area (e.g., 800 m around the station), spilling into the urban spaces between adjacent stations. We define this phenomenon—where riders exit Station A, engage in non-metro everyday activities, and re-enter at a neighboring Station B—as Life between Stations (LbS). LbS transforms the urban space around and between stations into a domain of attraction. Using LbS as a proxy for vibrancy—capturing the intensity, diversity, and continuity of human activity in the space—we (a) operationalized the LbS concept and (b) analyzed its spatiotemporal patterns and influencing factors with empirical smart card and open data from Hong Kong. Based on LbS intensity, temporal dynamics, and related riders’ characteristics, we identified six distinct station-pair and/or urban-space groups: Groups 1 & 3 represented vibrant urban cores with abundant leisure and consumption opportunities. Groups 2 & 5 featured mixed-use transit corridors. Groups 4 & 6 corresponded to the urban space with limited amenities and lower degree of centrality in the local transit network. Using machine learning, we identified key factors shaping the vibrancy of all these groups: between-station distance, functional density differences (e.g., dining, shopping, and social amenities) between the two stations, historical factors, and station centrality. Our study thus introduces a novel approach to measuring urban vibrancy around and between metro stations using the increasingly prevalent smart card and open data, offering evidence-based insights for enhancing such vibrancy through conscious urban/transport planning and policy interventions.
在人口密集的城市，地铁乘客的活动通常会超出一个车站典型服务区的边界（例如，车站周围800米），蔓延到邻近车站之间的城市空间。我们将这种现象定义为站间生活（Life between Stations, LbS），即乘客离开A站，从事非地铁日常活动，然后在邻近的b站重新进入。LbS将车站周围和车站之间的城市空间转变为一个吸引人的领域。利用地理位置作为活力的代表——捕捉空间中人类活动的强度、多样性和连续性——我们(a)对地理位置概念进行了操作，(b)利用香港的经验智能卡和开放数据分析了地理位置的时空格局和影响因素。基于LbS强度、时间动态和相关乘客特征，我们确定了6个不同的站点对和/或城市空间组：组1和组3代表了充满活力的城市核心，拥有丰富的休闲和消费机会。第2组和第5组以混合用途的交通走廊为特色。第4组和第6组对应的城市空间设施有限，在当地交通网络中中心度较低。通过机器学习，我们确定了影响所有这些群体活力的关键因素：车站之间的距离、两个车站之间的功能密度差异（例如，餐饮、购物和社会设施）、历史因素和车站中心性。因此，我们的研究引入了一种利用日益普及的智能卡和开放数据来衡量地铁站周围和地铁站之间的城市活力的新方法，为通过有意识的城市/交通规划和政策干预来增强这种活力提供了基于证据的见解。
{"title":"Vibrancy of the space around and between metro stations: Life between Stations and its determinants in Hong Kong","authors":"Yunting Miao, Jiangping Zhou","doi":"10.1007/s11116-025-10710-w","DOIUrl":"https://doi.org/10.1007/s11116-025-10710-w","url":null,"abstract":"In high-density cities, metro riders’ activities often extend beyond boundaries of one station’s typical service area (e.g., 800 m around the station), spilling into the urban spaces between adjacent stations. We define this phenomenon—where riders exit Station A, engage in non-metro everyday activities, and re-enter at a neighboring Station B—as Life between Stations (LbS). LbS transforms the urban space around and between stations into a domain of attraction. Using LbS as a proxy for vibrancy—capturing the intensity, diversity, and continuity of human activity in the space—we (a) operationalized the LbS concept and (b) analyzed its spatiotemporal patterns and influencing factors with empirical smart card and open data from Hong Kong. Based on LbS intensity, temporal dynamics, and related riders’ characteristics, we identified six distinct station-pair and/or urban-space groups: Groups 1 & 3 represented vibrant urban cores with abundant leisure and consumption opportunities. Groups 2 & 5 featured mixed-use transit corridors. Groups 4 & 6 corresponded to the urban space with limited amenities and lower degree of centrality in the local transit network. Using machine learning, we identified key factors shaping the vibrancy of all these groups: between-station distance, functional density differences (e.g., dining, shopping, and social amenities) between the two stations, historical factors, and station centrality. Our study thus introduces a novel approach to measuring urban vibrancy around and between metro stations using the increasingly prevalent smart card and open data, offering evidence-based insights for enhancing such vibrancy through conscious urban/transport planning and policy interventions.","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"67 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-12DOI: 10.1007/s11116-025-10708-4
Suxia Gong, Ismaïl Saadi, Jacques Teller, Mario Cools
This study evaluates the comparability of aggregated mobile phone data (MPD) derived from passive network signalling events and traditional travel survey data for urban transport planning, using the province of Liège as a case study. Our analysis demonstrates that while MPD captures a higher density of origin–destination (OD) connections, it cannot fully replicate all flows observed in surveys, underscoring the need for a complementary approach between the two data sources. Key mobility indicators, including average trip rates, hourly trip volumes, and structural patterns in daily OD matrices, show strong alignment. This structural similarity is rigorously quantified using a Mean Structural Similarity Index with a distance decay effect. Furthermore, Kolmogorov-Smirnov tests confirm comparable trip length distributions between the sources. While MPD-based population estimates closely match official 3:00 AM census counts, discrepancies in specific zones highlight potential pitfalls for real-time population mapping. Our findings confirm that MPD provides a robust and valuable complement to traditional surveys, particularly in contexts with limited or infrequent survey data. The study offers critical insights for integrating MPD into urban policy planning, emphasizing its utility for validation and its caveats for population estimation.
{"title":"A comparative analysis of mobile phone data and travel surveys in understanding travel behaviour","authors":"Suxia Gong, Ismaïl Saadi, Jacques Teller, Mario Cools","doi":"10.1007/s11116-025-10708-4","DOIUrl":"https://doi.org/10.1007/s11116-025-10708-4","url":null,"abstract":"This study evaluates the comparability of aggregated mobile phone data (MPD) derived from passive network signalling events and traditional travel survey data for urban transport planning, using the province of Liège as a case study. Our analysis demonstrates that while MPD captures a higher density of origin–destination (OD) connections, it cannot fully replicate all flows observed in surveys, underscoring the need for a complementary approach between the two data sources. Key mobility indicators, including average trip rates, hourly trip volumes, and structural patterns in daily OD matrices, show strong alignment. This structural similarity is rigorously quantified using a Mean Structural Similarity Index with a distance decay effect. Furthermore, Kolmogorov-Smirnov tests confirm comparable trip length distributions between the sources. While MPD-based population estimates closely match official 3:00 AM census counts, discrepancies in specific zones highlight potential pitfalls for real-time population mapping. Our findings confirm that MPD provides a robust and valuable complement to traditional surveys, particularly in contexts with limited or infrequent survey data. The study offers critical insights for integrating MPD into urban policy planning, emphasizing its utility for validation and its caveats for population estimation.","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"362 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145752829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-06DOI: 10.1007/s11116-025-10691-w
Tong Zhang, Dawei Li, Yuchen Song, Xiaowei Jiang
{"title":"Modeling activity capacity of multimodal transportation network: a bi-level optimization framework with land use constraints","authors":"Tong Zhang, Dawei Li, Yuchen Song, Xiaowei Jiang","doi":"10.1007/s11116-025-10691-w","DOIUrl":"https://doi.org/10.1007/s11116-025-10691-w","url":null,"abstract":"","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"28 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145680426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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