Pub Date : 2026-01-02DOI: 10.1080/23249935.2024.2362356
Renjie Zhang , Min Yang , Mao Ye , Xiao Fu , Enhui Chen
Express/local mode is an innovation combined with both express train and local train in metro system, which can offer conventional service for every station and rapid service for selected stations. The traditional operation planning for express/local mode is often carried out sequentially, leading to sub-optimality in the overall scheme and even an inability to match passenger demand. This paper aims to propose an integrated optimization approach of timetable and train ratio in express/local mode. An event-driven model and a ratio decomposition method are introduced to facilitate modeling of the problem. Then, a Two-stage Active Set Method is designed to solve the proposed model. The approach is verified through an example from Guangzhou Metro Line 14, revealing the correlation between train ratio and passenger waiting time. The results indicate that the approach can effectively allocate capacity resources of trains, leading to a significant 19.2% reduction in passenger waiting time.
{"title":"An integrated approach of timetable and train ratio optimisation based on event-driven model with express/local mode","authors":"Renjie Zhang , Min Yang , Mao Ye , Xiao Fu , Enhui Chen","doi":"10.1080/23249935.2024.2362356","DOIUrl":"10.1080/23249935.2024.2362356","url":null,"abstract":"<div><div>Express/local mode is an innovation combined with both express train and local train in metro system, which can offer conventional service for every station and rapid service for selected stations. The traditional operation planning for express/local mode is often carried out sequentially, leading to sub-optimality in the overall scheme and even an inability to match passenger demand. This paper aims to propose an integrated optimization approach of timetable and train ratio in express/local mode. An event-driven model and a ratio decomposition method are introduced to facilitate modeling of the problem. Then, a Two-stage Active Set Method is designed to solve the proposed model. The approach is verified through an example from Guangzhou Metro Line 14, revealing the correlation between train ratio and passenger waiting time. The results indicate that the approach can effectively allocate capacity resources of trains, leading to a significant 19.2% reduction in passenger waiting time.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141529063","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 : 2026-01-02DOI: 10.1080/23249935.2024.2377600
Adrian Cottam , Xiaofeng Li , Yao-Jan Wu
Passenger car equivalent (PCE) factors are used by the Highway Capacity Manual (HCM) to convert truck volumes to equivalent passenger car volumes and are typically calculated using multi-class volumes collected from traffic sensors. However, this requires costly sensor installations that provide limited spatial coverage. Therefore, this study proposes a novel approach to estimate PCE volumes using crowdsourced and open data. A multi-class volume estimation model (TS-SAE-XGB) is proposed to estimate passenger car and truck volumes, and single unit truck ratios. These parameters are input to a PCE interpolation algorithm which estimates PCE values using HCM methods. A spatial leave-one-out cross validation was conducted to compare the proposed model against five other machine learning models when estimating PCE values. The TS-SAE-XGB model estimated PCE and heavy vehicle factors with a MAPE of 6.22% and 3.03%, respectively, providing transportation professionals a practical method of estimating freeway PCE values where sensors are unavailable.
{"title":"Machine-learning approach for estimating passenger car equivalent factors using crowdsourced data","authors":"Adrian Cottam , Xiaofeng Li , Yao-Jan Wu","doi":"10.1080/23249935.2024.2377600","DOIUrl":"10.1080/23249935.2024.2377600","url":null,"abstract":"<div><div>Passenger car equivalent (PCE) factors are used by the Highway Capacity Manual (HCM) to convert truck volumes to equivalent passenger car volumes and are typically calculated using multi-class volumes collected from traffic sensors. However, this requires costly sensor installations that provide limited spatial coverage. Therefore, this study proposes a novel approach to estimate PCE volumes using crowdsourced and open data. A multi-class volume estimation model (TS-SAE-XGB) is proposed to estimate passenger car and truck volumes, and single unit truck ratios. These parameters are input to a PCE interpolation algorithm which estimates PCE values using HCM methods. A spatial leave-one-out cross validation was conducted to compare the proposed model against five other machine learning models when estimating PCE values. The TS-SAE-XGB model estimated PCE and heavy vehicle factors with a MAPE of 6.22% and 3.03%, respectively, providing transportation professionals a practical method of estimating freeway PCE values where sensors are unavailable.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141884641","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 : 2026-01-02DOI: 10.1080/23249935.2024.2388617
Richard Dzinyela , Monire Jafari , Subasish Das , Tahmida Hossian Shimu , Nawaf Alnawmasi , Dominique Lord
This study aims to explore the phenomenon of pedestrian crash severity by investigating how pedestrian injury levels have evolved in incidents occurring prior to (2019), during (2020), and after (2021) the COVID-19 lockdowns. Using Louisiana crash data, distinct annual models for pedestrian injury severity (categorised as severe (fatal and severe), minor (moderate and minor), and no injury) were developed using a random parameters logit approach, accounting for potential heterogeneity in means and variances of random parameters. Likelihood ratio tests were employed to assess the overall stability of model estimates across the studied years, and a comparison was made between partially constrained and unconstrained temporal modelling approaches. The results reveal statistically significant differences in injury severity before, during, and after the COVID-19 pandemic.
{"title":"Unconstrained and partially constrained temporal modelling of pedestrian injury severities","authors":"Richard Dzinyela , Monire Jafari , Subasish Das , Tahmida Hossian Shimu , Nawaf Alnawmasi , Dominique Lord","doi":"10.1080/23249935.2024.2388617","DOIUrl":"10.1080/23249935.2024.2388617","url":null,"abstract":"<div><div>This study aims to explore the phenomenon of pedestrian crash severity by investigating how pedestrian injury levels have evolved in incidents occurring prior to (2019), during (2020), and after (2021) the COVID-19 lockdowns. Using Louisiana crash data, distinct annual models for pedestrian injury severity (categorised as severe (fatal and severe), minor (moderate and minor), and no injury) were developed using a random parameters logit approach, accounting for potential heterogeneity in means and variances of random parameters. Likelihood ratio tests were employed to assess the overall stability of model estimates across the studied years, and a comparison was made between partially constrained and unconstrained temporal modelling approaches. The results reveal statistically significant differences in injury severity before, during, and after the COVID-19 pandemic.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141949363","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 : 2026-01-02DOI: 10.1080/23249935.2024.2346631
Youngmin Choi , Bruce L. Golden , Paul M. Schonfeld
Optimizing Traveling Salesman Problem (TSP) tours requires substantial computational effort, leading researchers to develop approximations relating tour length to the number of visited points, n. Existing models, such as the √nA predictor, effectively approximate tour lengths for large-capacity vehicles but sacrifice accuracy for small n values relevant for most practical applications. Consequently, this study addresses this gap by proposing models with uniform node distributions, which incorporate realistic factors, such as central vs. random starting points and various service zone shapes. These factors are then integrated into a single equation, enhancing applicability. Furthermore, the exponent of n is statistically estimated to be significantly different from 0.5, challenging previous studies. Our proposed model estimates TSP tour lengths more accurately, particularly for small n values, and maintains accuracy for large n values, with errors below 3.11% for up to 600 points. This model offers a more precise and versatile alternative to current models.
优化旅行推销员问题（TSP）的游程需要大量的计算工作，因此研究人员开发了游程长度与访问点数 n 有关的近似值。
{"title":"Improving analytic approximations of TSP tour lengths with adjustment factors","authors":"Youngmin Choi , Bruce L. Golden , Paul M. Schonfeld","doi":"10.1080/23249935.2024.2346631","DOIUrl":"10.1080/23249935.2024.2346631","url":null,"abstract":"<div><div>Optimizing Traveling Salesman Problem (TSP) tours requires substantial computational effort, leading researchers to develop approximations relating tour length to the number of visited points, <em>n</em>. Existing models, such as the <em>√nA</em> predictor, effectively approximate tour lengths for large-capacity vehicles but sacrifice accuracy for small <em>n</em> values relevant for most practical applications. Consequently, this study addresses this gap by proposing models with uniform node distributions, which incorporate realistic factors, such as central vs. random starting points and various service zone shapes. These factors are then integrated into a single equation, enhancing applicability. Furthermore, the exponent of n is statistically estimated to be significantly different from 0.5, challenging previous studies. Our proposed model estimates TSP tour lengths more accurately, particularly for small <em>n</em> values, and maintains accuracy for large <em>n</em> values, with errors below 3.11% for up to 600 points. This model offers a more precise and versatile alternative to current models.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140828095","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}
Macroscopic fundamental diagram (MFD) is widely applied in network modelling and management, such as route guidance and vehicle relocation, which are formulated as generalised dynamic traffic assignment (DTA) problems. MFD can effectively reduce the spatial dimension thus making the generalised DTA problems computationally efficient. In the literature, three MFD models, the accumulation-based model, the trip-based model, and the time delay model, were proposed to capture the traffic flow propagation under different traffic conditions and demand scenarios. However, no consensus has been reached on their computational efficiency and which model should be chosen under certain traffic conditions and demand scenarios. In this paper, we revisit these models regarding two important theoretical properties regarding flow propagation in the DTA, i.e. the first-in-first-out (FIFO) principle and causality. Corresponding dynamic network loading algorithms are designed to compare their numerical accuracy and computational efficiency. Numerical comparisons with Lighthill-Whitham-Richards (LWR) model and a micro simulator confirm that the accumulation-based model is valid in saturation, the trip-based model is valid in free-flow, while the time delay model provides a good approximation in both free-flow and saturation scenarios. On the other hand, violation of strict causality is observed in the accumulation-based and trip-based models, rendering it hard to pursue analytical DTA. This issue is not observed in the time delay model. Overall, the time delay model is a promising alternative for dynamic network loading in large-scale network applications.
{"title":"A comparison of the accumulation-based, trip-based and time delay macroscopic fundamental diagram models","authors":"Yunping Huang , Jianhui Xiong , Shu-Chien Hsu , Agachai Sumalee , William Lam , Renxin Zhong","doi":"10.1080/23249935.2024.2338258","DOIUrl":"10.1080/23249935.2024.2338258","url":null,"abstract":"<div><div>Macroscopic fundamental diagram (MFD) is widely applied in network modelling and management, such as route guidance and vehicle relocation, which are formulated as generalised dynamic traffic assignment (DTA) problems. MFD can effectively reduce the spatial dimension thus making the generalised DTA problems computationally efficient. In the literature, three MFD models, the accumulation-based model, the trip-based model, and the time delay model, were proposed to capture the traffic flow propagation under different traffic conditions and demand scenarios. However, no consensus has been reached on their computational efficiency and which model should be chosen under certain traffic conditions and demand scenarios. In this paper, we revisit these models regarding two important theoretical properties regarding flow propagation in the DTA, i.e. the first-in-first-out (FIFO) principle and causality. Corresponding dynamic network loading algorithms are designed to compare their numerical accuracy and computational efficiency. Numerical comparisons with Lighthill-Whitham-Richards (LWR) model and a micro simulator confirm that the accumulation-based model is valid in saturation, the trip-based model is valid in free-flow, while the time delay model provides a good approximation in both free-flow and saturation scenarios. On the other hand, violation of strict causality is observed in the accumulation-based and trip-based models, rendering it hard to pursue analytical DTA. This issue is not observed in the time delay model. Overall, the time delay model is a promising alternative for dynamic network loading in large-scale network applications.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140594638","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 : 2026-01-02DOI: 10.1080/23249935.2024.2371350
Mengying Cui , Zhe Dai , David Levinson
This paper develops a link-based full cost model for auto travel, which identifies both internal and external costs of travel, and gives a link-based cost estimate for the Minneapolis – St. Paul (Twin Cities) metropolitan region. The key cost components are time, emissions, crashes, user monetary, and infrastructure. The estimates show that the average full cost of travel is a $0.694/veh-km traffic-weighted average over the study area, of which the time and user monetary costs account for approximately 70% of the total. Except for the infrastructure cost, highways are more cost-effective than other surface roadways considering all the other cost components, as well as the internal and full costs. Quantifying the full costs of auto travel is essential for making sustainable investments.
{"title":"Link-based full cost analysis of travel by automobile","authors":"Mengying Cui , Zhe Dai , David Levinson","doi":"10.1080/23249935.2024.2371350","DOIUrl":"10.1080/23249935.2024.2371350","url":null,"abstract":"<div><div>This paper develops a link-based full cost model for auto travel, which identifies both internal and external costs of travel, and gives a link-based cost estimate for the Minneapolis – St. Paul (Twin Cities) metropolitan region. The key cost components are time, emissions, crashes, user monetary, and infrastructure. The estimates show that the average full cost of travel is a $0.694/veh-km traffic-weighted average over the study area, of which the time and user monetary costs account for approximately 70% of the total. Except for the infrastructure cost, highways are more cost-effective than other surface roadways considering all the other cost components, as well as the internal and full costs. Quantifying the full costs of auto travel is essential for making sustainable investments.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141504699","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 : 2026-01-02DOI: 10.1080/23249935.2024.2344631
Mingxue Guo , Tingting Zhao , Ziyou Gao
Protecting transportation systems from severe damage is crucial for their post-disaster functionality. We adopt network topological metrics and generalised topological metrics involving demand and traffic flow characteristics to identify critical links for enhancing post-event transportation network performance. A single-parameter, non-monotonic function is proposed to allocate limited resources based on these metrics. Monte Carlo simulation generates failure scenarios to evaluate residual network performance through network topological measures and network level of service indicators. This work introduces ‘Trip Efficiency’, a novel level of service indicator that considers both demand connectivity and travel efficiency for a network with multiple links interrupted. In Anaheim case study network, betweenness-based resource allocation leads to better performance on network topological measures; while generalised topological metrics result in more connected OD pairs and higher travel efficiency. The experimental results demonstrate the effectiveness of the proposed method in enhancing network resilience against multisite disruptive events through proactive resource allocations.
{"title":"Pre-disaster resource allocation based on network topology and flow features","authors":"Mingxue Guo , Tingting Zhao , Ziyou Gao","doi":"10.1080/23249935.2024.2344631","DOIUrl":"10.1080/23249935.2024.2344631","url":null,"abstract":"<div><div>Protecting transportation systems from severe damage is crucial for their post-disaster functionality. We adopt network topological metrics and generalised topological metrics involving demand and traffic flow characteristics to identify critical links for enhancing post-event transportation network performance. A single-parameter, non-monotonic function is proposed to allocate limited resources based on these metrics. Monte Carlo simulation generates failure scenarios to evaluate residual network performance through network topological measures and network level of service indicators. This work introduces ‘Trip Efficiency’, a novel level of service indicator that considers both demand connectivity and travel efficiency for a network with multiple links interrupted. In Anaheim case study network, betweenness-based resource allocation leads to better performance on network topological measures; while generalised topological metrics result in more connected OD pairs and higher travel efficiency. The experimental results demonstrate the effectiveness of the proposed method in enhancing network resilience against multisite disruptive events through proactive resource allocations.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140931768","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 : 2026-01-02DOI: 10.1080/23249935.2024.2338249
Ruiyou Zhang , Zhujun Liu , Ilkyeong Moon
The problem of heterogeneous vehicle scheduling with precedence constraints is inspired by the transportation service in tourism areas. Tourists must take the shuttle vehicles provided by the areas because of the long distances between the scenic spots. The scheduling of vehicles in tourism areas is complicated because the transportation requests of tourists are precedence-constrained temporally and spatially. The problem optimises both the cost of using vehicles and the waiting time of tourists. A mixed-integer linear programming model is formulated according to the description of a graph. An adaptive large neighbourhood search algorithm with several specialised operators is designed to solve the problem. Experiments based on randomly generated instances validate the mathematical model and the algorithm. A real-size instance based on Qiandao Lake in China is also analysed. The results indicate that the algorithm outperforms the model. The sensitivities of key parameters are analysed with managerial insights presented.
带优先级约束的异构车辆调度问题是受旅游区交通服务的启发而提出的。游客必须乘坐景区提供的班车...
{"title":"Heterogeneous vehicle scheduling with precedence constraints","authors":"Ruiyou Zhang , Zhujun Liu , Ilkyeong Moon","doi":"10.1080/23249935.2024.2338249","DOIUrl":"10.1080/23249935.2024.2338249","url":null,"abstract":"<div><div>The problem of heterogeneous vehicle scheduling with precedence constraints is inspired by the transportation service in tourism areas. Tourists must take the shuttle vehicles provided by the areas because of the long distances between the scenic spots. The scheduling of vehicles in tourism areas is complicated because the transportation requests of tourists are precedence-constrained temporally and spatially. The problem optimises both the cost of using vehicles and the waiting time of tourists. A mixed-integer linear programming model is formulated according to the description of a graph. An adaptive large neighbourhood search algorithm with several specialised operators is designed to solve the problem. Experiments based on randomly generated instances validate the mathematical model and the algorithm. A real-size instance based on Qiandao Lake in China is also analysed. The results indicate that the algorithm outperforms the model. The sensitivities of key parameters are analysed with managerial insights presented.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140594414","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 : 2026-01-02DOI: 10.1080/23249935.2024.2393226
Yating Wu , Minghui Lai , Ruiling Yang , Yuan Wang
Mobility-as-a-Service (MaaS) seamlessly integrates public transit with mobility-on-demand services to provide users with a one-stop tailored mobility service. Motivated by the practices of the SocialCar project, we study the integration of one-to-many peer-to-peer ridesharing and public transit in the morning commute setting. However, it becomes extremely difficult for the platform to optimise matching, routeing and scheduling for the users over a large network. For practical application, we develop a decision model for the integrated matching problem and propose an iterative distributed optimisation algorithm. The algorithm decomposes the original problem into parallel small subproblems within clusters and iteratively updates clustering as guided by theoretical results; furthermore, an incremental approach is adopted when updating clusters to reduce computational complexity. We conduct extensive computational experiments with real-world data, which demonstrate that our algorithm can quickly generate high-quality solutions for MaaS systems in practice while substantially reducing the users' vehicle miles travelled.
{"title":"Integrating one-to-many peer-to-peer ridesharing and public transit for morning commute on a mobility-as-a-service platform","authors":"Yating Wu , Minghui Lai , Ruiling Yang , Yuan Wang","doi":"10.1080/23249935.2024.2393226","DOIUrl":"10.1080/23249935.2024.2393226","url":null,"abstract":"<div><div>Mobility-as-a-Service (MaaS) seamlessly integrates public transit with mobility-on-demand services to provide users with a one-stop tailored mobility service. Motivated by the practices of the SocialCar project, we study the integration of one-to-many peer-to-peer ridesharing and public transit in the morning commute setting. However, it becomes extremely difficult for the platform to optimise matching, routeing and scheduling for the users over a large network. For practical application, we develop a decision model for the integrated matching problem and propose an iterative distributed optimisation algorithm. The algorithm decomposes the original problem into parallel small subproblems within clusters and iteratively updates clustering as guided by theoretical results; furthermore, an incremental approach is adopted when updating clusters to reduce computational complexity. We conduct extensive computational experiments with real-world data, which demonstrate that our algorithm can quickly generate high-quality solutions for MaaS systems in practice while substantially reducing the users' vehicle miles travelled.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071085","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 : 2026-01-02DOI: 10.1080/23249935.2024.2390009
Sion Kim , Ilho Jeong , Minje Choi , Juhyeon Kwak , Madiha Bencekri , Seungjae Lee
As urban areas face rapid population and vehicle growth, understanding system dynamics is crucial for managing transportation congestion effectively. Utilizing fractal and metabolic concepts offers fresh perspectives on the behavior and efficiency of complex urban transportation systems. To understand the dynamics of congested traffic flows, we conducted fractal analysis on the traffic pattern in Seoul city with chronic congestion worldwide and investigated its potential for evaluating metabolic efficiency. Our rank and size fractal analysis revealed that Seoul's fractal dimension ranges from 6.7060 to 7.6801. The fractal dimension's curve, when plotted against traffic congestion, shows a peculiar symmetrical relationship. The linear correlation between fractal dimension and metabolic indicators suggests that fractal dimension could potentially serve as a novel metric for evaluating traffic flow efficiency. This study introduces new insights by integrating fractal and metabolic principles to understand traffic system dynamics, marking the first use of fractal analysis in traffic pattern evaluation.
{"title":"Fractal dimensional analysis to reveal traffic flow dynamics as organic metabolism","authors":"Sion Kim , Ilho Jeong , Minje Choi , Juhyeon Kwak , Madiha Bencekri , Seungjae Lee","doi":"10.1080/23249935.2024.2390009","DOIUrl":"10.1080/23249935.2024.2390009","url":null,"abstract":"<div><div>As urban areas face rapid population and vehicle growth, understanding system dynamics is crucial for managing transportation congestion effectively. Utilizing fractal and metabolic concepts offers fresh perspectives on the behavior and efficiency of complex urban transportation systems. To understand the dynamics of congested traffic flows, we conducted fractal analysis on the traffic pattern in Seoul city with chronic congestion worldwide and investigated its potential for evaluating metabolic efficiency. Our rank and size fractal analysis revealed that Seoul's fractal dimension ranges from 6.7060 to 7.6801. The fractal dimension's curve, when plotted against traffic congestion, shows a peculiar symmetrical relationship. The linear correlation between fractal dimension and metabolic indicators suggests that fractal dimension could potentially serve as a novel metric for evaluating traffic flow efficiency. This study introduces new insights by integrating fractal and metabolic principles to understand traffic system dynamics, marking the first use of fractal analysis in traffic pattern evaluation.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142210959","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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