Pub Date : 2024-11-01DOI: 10.1016/j.trd.2024.104455
Hao Chen , Haoluan Wang , Yingqi Hu
Transportation systems are growingly subject to extreme weather events induced by climate change. Yet, delays in operating public transportation systems due to adverse weather conditions are not well understood. In this study, we quantify the impact of temperature shocks on school bus delays in New York City during 2015–2019. We find that low temperatures lead to significant school bus delays regarding the frequency and delay time. Our heterogeneity analysis further shows that increased school bus delay time in cold weather is primarily driven by Curb-to-School buses (for students with special education and needs) and school bus operations in the mornings. Our findings provide new evidence on how temperature shocks affect transportation systems and highlight the need for adaptive strategies and planning that can aid school buses in better responding to adverse weather conditions.
{"title":"Weathering the wait: Temperature impacts on school bus delays","authors":"Hao Chen , Haoluan Wang , Yingqi Hu","doi":"10.1016/j.trd.2024.104455","DOIUrl":"10.1016/j.trd.2024.104455","url":null,"abstract":"<div><div>Transportation systems are growingly subject to extreme weather events induced by climate change. Yet, delays in operating public transportation systems due to adverse weather conditions are not well understood. In this study, we quantify the impact of temperature shocks on school bus delays in New York City during 2015–2019. We find that low temperatures lead to significant school bus delays regarding the frequency and delay time. Our heterogeneity analysis further shows that increased school bus delay time in cold weather is primarily driven by Curb-to-School buses (for students with special education and needs) and school bus operations in the mornings. Our findings provide new evidence on how temperature shocks affect transportation systems and highlight the need for adaptive strategies and planning that can aid school buses in better responding to adverse weather conditions.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104455"},"PeriodicalIF":7.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-11-01DOI: 10.1016/j.trd.2024.104479
Wei Gao , Yiyang Lu , Naihui Wang , Guozhu Cheng , Zhenyang Qiu , Xiaowei Hu
Rainfall events frequently disrupt the subway system, significantly impacting operational efficiency and service quality. It is challenging to measure and predict subway system resilience due to the different construction environments of subway stations. We develop an approach based on probabilistic modeling techniques to measure subway system and station resilience. Random forest is used to analyze the heterogeneity of resilience patterns from an environmental perspective. Based on wavelet decomposition and spatial–temporal networks, we design an ensemble neural network modeling framework considering environmental factors to predict system and station resilience. According to an analysis of a dataset from Harbin, China, subway system resilience decreases by 1/6 for every 10 mm increase in rainfall intensity when the rainfall is under 60 mm. 44.6 % of low-resilience stations are near roads at the Level of Service III and IV. The proposed prediction model outperforms the state-of-the-art models with a prediction accuracy of 96.82 %.
降雨事件经常干扰地铁系统，严重影响运营效率和服务质量。由于地铁站的施工环境各不相同，因此测量和预测地铁系统的恢复能力具有挑战性。我们开发了一种基于概率建模技术的方法来测量地铁系统和车站的恢复能力。随机森林用于从环境角度分析弹性模式的异质性。基于小波分解和时空网络，我们设计了一个考虑环境因素的集合神经网络建模框架，以预测系统和车站的复原力。根据对中国哈尔滨数据集的分析，当降雨量低于 60 毫米时，降雨强度每增加 10 毫米，地铁系统的恢复能力就会下降 1/6。44.6%的低弹性车站靠近服务等级为 III 和 IV 级的道路。所提出的预测模型优于最先进的模型，预测准确率达 96.82%。
{"title":"Measurement and prediction of subway resilience under rainfall events: An environment perspective","authors":"Wei Gao , Yiyang Lu , Naihui Wang , Guozhu Cheng , Zhenyang Qiu , Xiaowei Hu","doi":"10.1016/j.trd.2024.104479","DOIUrl":"10.1016/j.trd.2024.104479","url":null,"abstract":"<div><div>Rainfall events frequently disrupt the subway system, significantly impacting operational efficiency and service quality. It is challenging to measure and predict subway system resilience due to the different construction environments of subway stations. We develop an approach based on probabilistic modeling techniques to measure subway system and station resilience. Random forest is used to analyze the heterogeneity of resilience patterns from an environmental perspective. Based on wavelet decomposition and spatial–temporal networks, we design an ensemble neural network modeling framework considering environmental factors to predict system and station resilience. According to an analysis of a dataset from Harbin, China, subway system resilience decreases by 1/6 for every 10 mm increase in rainfall intensity when the rainfall is under 60 mm. 44.6 % of low-resilience stations are near roads at the Level of Service III and IV. The proposed prediction model outperforms the state-of-the-art models with a prediction accuracy of 96.82 %.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104479"},"PeriodicalIF":7.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-11-01DOI: 10.1016/j.trd.2024.104482
Jinpeng Wang, Yujie Hu
Understanding how human mobility patterns respond to natural disasters is crucial. This study investigates Hurricane Ian’s impact on human mobility patterns and subsequent recovery in southwest Florida. Using privacy-preserving mobile phone GPS data, this research analyzes human mobility networks before, during, and after the hurricane, examining both macro and substructure (motif) levels. Additionally, this study investigates spatial variations in motifs over time, revealing localized connectivity patterns and adaptations in response to the hurricane’s impact. The macroscale analysis shows a substantial decrease in mobility during the hurricane, leading to disruptions in connectivity and efficiency. However, the network demonstrated resilience by swiftly recovering post-hurricane. At the substructure level, different motifs exhibited varied responses, with densely connected motifs experiencing reductions in their percentage distribution, while less connected motifs showed increases. Moreover, there were shifts in the spatial distribution of motifs, which underscored vulnerabilities and adaptations within the mobility network. Understanding these dynamics during natural disasters can guide more targeted, spatially informed disaster management policies.
{"title":"Unraveling hurricane Ian’s Impact: A multiscale analysis of mobility networks in Florida","authors":"Jinpeng Wang, Yujie Hu","doi":"10.1016/j.trd.2024.104482","DOIUrl":"10.1016/j.trd.2024.104482","url":null,"abstract":"<div><div>Understanding how human mobility patterns respond to natural disasters is crucial. This study investigates Hurricane Ian’s impact on human mobility patterns and subsequent recovery in southwest Florida. Using privacy-preserving mobile phone GPS data, this research analyzes human mobility networks before, during, and after the hurricane, examining both macro and substructure (motif) levels. Additionally, this study investigates spatial variations in motifs over time, revealing localized connectivity patterns and adaptations in response to the hurricane’s impact. The macroscale analysis shows a substantial decrease in mobility during the hurricane, leading to disruptions in connectivity and efficiency. However, the network demonstrated resilience by swiftly recovering post-hurricane. At the substructure level, different motifs exhibited varied responses, with densely connected motifs experiencing reductions in their percentage distribution, while less connected motifs showed increases. Moreover, there were shifts in the spatial distribution of motifs, which underscored vulnerabilities and adaptations within the mobility network. Understanding these dynamics during natural disasters can guide more targeted, spatially informed disaster management policies.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104482"},"PeriodicalIF":7.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-11-01DOI: 10.1016/j.trd.2024.104484
Bin Sun , Le Hu , Qijun Zhang , Chao Zou , Ning Wei , Zhenyu Jia , Zhong Wu , Hongjun Mao
Traffic-signal-based speed guidance system (TSSGS) play a crucial role in the realization of sustainable urban road transportation systems. This study aims to uncover the underlying mechanisms of the TSSGS on energy consumption and traffic efficiency across different application stages. Real-time vehicle operational data were collected for three TSSGS scenarios: (1) Non-TSSGS (pre-deployment of TSSGS), (2) Prim-TSSGS (early deployment of TSSGS), and (3) Prof-TSSGS (mature deployment of TSSGS). The results revealed that Prim-TSSGS leads to increased aggressive driving behavior, decreased travel comfort, and a rise in energy consumption by 23.8% for vehicles and 30.0% for roads, attributed the lack of driver experience with the TSSGS. When drivers have a good understanding of the TSSGS, Prof-TSSGS significantly reduces the energy consumption by 29.5% for vehicles and by 23.1% for roads. This study highlights the importance of improving driver proficiency in active TSSGS to improve the sustainability of road transportation.
{"title":"Impacts of traffic-signal-based speed guidance system across different application stages on traffic","authors":"Bin Sun , Le Hu , Qijun Zhang , Chao Zou , Ning Wei , Zhenyu Jia , Zhong Wu , Hongjun Mao","doi":"10.1016/j.trd.2024.104484","DOIUrl":"10.1016/j.trd.2024.104484","url":null,"abstract":"<div><div>Traffic-signal-based speed guidance system (TSSGS) play a crucial role in the realization of sustainable urban road transportation systems. This study aims to uncover the underlying mechanisms of the TSSGS on energy consumption and traffic efficiency across different application stages. Real-time vehicle operational data were collected for three TSSGS scenarios: (1) Non-TSSGS (pre-deployment of TSSGS), (2) Prim-TSSGS (early deployment of TSSGS), and (3) Prof-TSSGS (mature deployment of TSSGS). The results revealed that Prim-TSSGS leads to increased aggressive driving behavior, decreased travel comfort, and a rise in energy consumption by 23.8% for vehicles and 30.0% for roads, attributed the lack of driver experience with the TSSGS. When drivers have a good understanding of the TSSGS, Prof-TSSGS significantly reduces the energy consumption by 29.5% for vehicles and by 23.1% for roads. This study highlights the importance of improving driver proficiency in active TSSGS to improve the sustainability of road transportation.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104484"},"PeriodicalIF":7.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-11-01DOI: 10.1016/j.trd.2024.104453
Mehrnoush Bahramimehr, Golam Kabir
Railway transportation, integral to Canada’s supply chain, is recognized for its reliability and safety, yet its complexity introduces various risks. In this study, a meteorological risk assessment of the Canadian transcontinental freight railway is performed using a comprehensive spatial analysis. Flood (areas prone to flood risk across the province), rain (maximum daily precipitation in mm), snow (maximum snowfall in cm), minimum temperature (minimum temperature in Celsius), and wind (maximum gust speed in Km/h) have been selected as factors to generate meteorological risk maps of the Transcontinental Freight Canadian National Railway (CN) for the Saskatchewan and Ontario provinces. The study generated five integrated risk maps, varying in factor weighting approaches, including equal weight, score-based weighting, expert opinion-based Analytical Hierarchy Process, and seasonal considerations for both warm and cold seasons. These risk maps demonstrate hotspots and hazardous areas that require more attention and planning to maintain the continuity of the supply chain. The results of this study can be used to enhance safety, reduce service disruptions, and ensure the smooth operation of the railway network.
{"title":"Meteorological risk assessment of Canadian transcontinental freight railway","authors":"Mehrnoush Bahramimehr, Golam Kabir","doi":"10.1016/j.trd.2024.104453","DOIUrl":"10.1016/j.trd.2024.104453","url":null,"abstract":"<div><div>Railway transportation, integral to Canada’s supply chain, is recognized for its reliability and safety, yet its complexity introduces various risks. In this study, a meteorological risk assessment of the Canadian transcontinental freight railway is performed using a comprehensive spatial analysis. Flood (areas prone to flood risk across the province), rain (maximum daily precipitation in mm), snow (maximum snowfall in cm), minimum temperature (minimum temperature in Celsius), and wind (maximum gust speed in Km/h) have been selected as factors to generate meteorological risk maps of the Transcontinental Freight Canadian National Railway (CN) for the Saskatchewan and Ontario provinces. The study generated five integrated risk maps, varying in factor weighting approaches, including equal weight, score-based weighting, expert opinion-based Analytical Hierarchy Process, and seasonal considerations for both warm and cold seasons. These risk maps demonstrate hotspots and hazardous areas that require more attention and planning to maintain the continuity of the supply chain. The results of this study can be used to enhance safety, reduce service disruptions, and ensure the smooth operation of the railway network.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104453"},"PeriodicalIF":7.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.trd.2024.104422
Hong Zhang , Xin Xu , Chi Zhang , Hong-Zhi Yang , Yiik Diew Wong
This study identified and assessed spatiotemporal distribution, and modeled influencing factors, of roadside geological risks for the Qinghai-Tibetan Plateau regions towards enhancing the safety of road operations. It utilized Latent Dirichlet Allocation model to identify risks, hotspot analysis and normalized spectral entropy to assess the spatiotemporal risk distribution, and Generalized Estimation Equations to analyze the relationship between geological risk susceptibility and the influencing factors. Finally, a case study was conducted to apply this methodology. The findings indicated that mountain geological hazards could affect areas up to 2,000 m from the roadway. Roadbed and tunnel sections, and lower-grade highways were more susceptible to mountain geological hazards, while higher-grade highways tended to have lower frozen soil thermal stability in their roadbed sections. This study provides valuable insights into the coupling effects between engineering and geological environments, crucial for informed route layout decisions and effective management of roadside geological risks.
{"title":"Assessment and modeling of roadside geological risks in the Qinghai-Tibetan Plateau region","authors":"Hong Zhang , Xin Xu , Chi Zhang , Hong-Zhi Yang , Yiik Diew Wong","doi":"10.1016/j.trd.2024.104422","DOIUrl":"10.1016/j.trd.2024.104422","url":null,"abstract":"<div><div>This study identified and assessed spatiotemporal distribution, and modeled influencing factors, of roadside geological risks for the Qinghai-Tibetan Plateau regions towards enhancing the safety of road operations. It utilized Latent Dirichlet Allocation model to identify risks, hotspot analysis and normalized spectral entropy to assess the spatiotemporal risk distribution, and Generalized Estimation Equations to analyze the relationship between geological risk susceptibility and the influencing factors. Finally, a case study was conducted to apply this methodology. The findings indicated that mountain geological hazards could affect areas up to 2,000 m from the roadway. Roadbed and tunnel sections, and lower-grade highways were more susceptible to mountain geological hazards, while higher-grade highways tended to have lower frozen soil thermal stability in their roadbed sections. This study provides valuable insights into the coupling effects between engineering and geological environments, crucial for informed route layout decisions and effective management of roadside geological risks.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104422"},"PeriodicalIF":7.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-11-01DOI: 10.1016/j.trd.2024.104427
Nanxi Wang , Min Wu , Kum Fai Yuen , Xueyi Gao
Resilience has increasingly been recognized as crucial for coping with disruptions and sustaining urban transportation systems (UTSs). However, long-term and dynamic resilience research is lacking. Therefore, this study redefines resilience and develops a comprehensive dynamic long-term resilience assessment model for UTSs. To capture the dynamic characteristics of UTS, we constructed a dynamic Bayesian network model to explore the system’s latent learning ability. To reflect the multidimensional considerations in measuring system resilience, leading indicators from four dimensions (economic, environmental, social, and technological) are selected. Case studies reveal that 1) UTS resilience shows dynamic characteristics, 2) environmental and technical indicators enhance resilience, 3) learning capability is positively related to resilience, and 4) resilience does not always correlate with economic development or urban GDP. The proposed research framework offers a reference for integrating subjective and objective data, and the evaluation model serves as a guide for dynamic assessments of system resilience.
人们日益认识到，抗灾能力对于应对破坏和维持城市交通系统（UTS）至关重要。然而，长期和动态的复原力研究还很缺乏。因此，本研究重新定义了抗灾能力，并为UTS开发了一个全面的动态长期抗灾能力评估模型。为了捕捉UTS的动态特征，我们构建了一个动态贝叶斯网络模型来探索系统的潜在学习能力。为了反映衡量系统恢复能力的多维度考虑，我们从四个维度（经济、环境、社会和技术）选取了领先指标。案例研究表明：1）UTS 复原力呈现动态特征；2）环境和技术指标增强了复原力；3）学习能力与复原力正相关；4）复原力并不总是与经济发展或城市 GDP 相关。所提出的研究框架为整合主观和客观数据提供了参考，而评估模型则为系统复原力的动态评估提供了指导。
{"title":"Urban transportation system long-term resilience assessment using multi-dimensional dynamic Bayesian network","authors":"Nanxi Wang , Min Wu , Kum Fai Yuen , Xueyi Gao","doi":"10.1016/j.trd.2024.104427","DOIUrl":"10.1016/j.trd.2024.104427","url":null,"abstract":"<div><div>Resilience has increasingly been recognized as crucial for coping with disruptions and sustaining urban transportation systems (UTSs). However, long-term and dynamic resilience research is lacking. Therefore, this study redefines resilience and develops a comprehensive dynamic long-term resilience assessment model for UTSs. To capture the dynamic characteristics of UTS, we constructed a dynamic Bayesian network model to explore the system’s latent learning ability. To reflect the multidimensional considerations in measuring system resilience, leading indicators from four dimensions (economic, environmental, social, and technological) are selected. Case studies reveal that 1) UTS resilience shows dynamic characteristics, 2) environmental and technical indicators enhance resilience, 3) learning capability is positively related to resilience, and 4) resilience does not always correlate with economic development or urban GDP. The proposed research framework offers a reference for integrating subjective and objective data, and the evaluation model serves as a guide for dynamic assessments of system resilience.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104427"},"PeriodicalIF":7.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-11-01DOI: 10.1016/j.trd.2024.104480
Zhichao Chen , Changjiang Zheng , Meng Xu , Muqing Du , Junze Ma , Shukang Zheng
Urban Underground-Aboveground Logistics Networks (UUALNs) are susceptible to disruptions from unforeseen events such as rainfall and flooding, leading to severe road congestion. This paper investigates the reliability of UUALNs under various attack-recovery conditions, focusing on their ability to recover from cascading failures triggered by extreme rainfall-flood scenarios. We propose a coupled model that integrates a rainfall-flood model with a cascading failure framework. A case study of Nanjing is conducted to simulate the model’s performance and validate its spatiotemporal adaptability in different attack-recovery scenarios. The findings demonstrate that different recovery strategies show varying degrees of effectiveness in mitigating network damage, with strategies based on the interaction attributes of coupled networks proving more resilient in rainfall-flood scenarios. When network congestion exceeds the percolation threshold, the diffusion of congestion intensifies, posing further challenges to network reliability. This study provides a robust framework for enhancing the resilience of urban logistics networks under adverse conditions.
{"title":"Reliability of urban underground-aboveground logistics networks under rainfall-flood and cascading failure scenarios","authors":"Zhichao Chen , Changjiang Zheng , Meng Xu , Muqing Du , Junze Ma , Shukang Zheng","doi":"10.1016/j.trd.2024.104480","DOIUrl":"10.1016/j.trd.2024.104480","url":null,"abstract":"<div><div>Urban Underground-Aboveground Logistics Networks (UUALNs) are susceptible to disruptions from unforeseen events such as rainfall and flooding, leading to severe road congestion. This paper investigates the reliability of UUALNs under various attack-recovery conditions, focusing on their ability to recover from cascading failures triggered by extreme rainfall-flood scenarios. We propose a coupled model that integrates a rainfall-flood model with a cascading failure framework. A case study of Nanjing is conducted to simulate the model’s performance and validate its spatiotemporal adaptability in different attack-recovery scenarios. The findings demonstrate that different recovery strategies show varying degrees of effectiveness in mitigating network damage, with strategies based on the interaction attributes of coupled networks proving more resilient in rainfall-flood scenarios. When network congestion exceeds the percolation threshold, the diffusion of congestion intensifies, posing further challenges to network reliability. This study provides a robust framework for enhancing the resilience of urban logistics networks under adverse conditions.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104480"},"PeriodicalIF":7.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-11-01DOI: 10.1016/j.trd.2024.104399
Hang Su , Min Xu , Xiaolei Wang , Xiaoning Zhang
Unpredictable large amount of travel demands often occurs in urban area, and e-hailing services are often used as an important travel modal for mitigating such surge traffic. Effective pricing and scheduling strategies are urgently needed to optimize e-hailing vehicle supply and enhance evacuation efficiency during mass gathering events. Based on the method of Macroscopic Fundamental Diagram (MFD), mathematical models are presented to characterize the time-varying evolution of both e-hailing vehicles and other vehicles within a two-region transport system, and management approaches are also provided to improve the evacuation process. Considering drivers’ repositioning decisions and passengers’ demand dynamics, a region-dependent pricing strategy is developed for rapid massive evacuation. In the numerical examples, it is observed that the region-dependent pricing strategy effectively allocates a more balanced distribution of vacant vehicle supply, despite higher generalized wage for drivers and increased generalized cost for passengers. More importantly, the region-dependent pricing strategy can significantly shorten total evacuation time, and lead to more stable traffic condition.
{"title":"A region-dependent e-hailing service pricing strategy for rapid massive evacuation","authors":"Hang Su , Min Xu , Xiaolei Wang , Xiaoning Zhang","doi":"10.1016/j.trd.2024.104399","DOIUrl":"10.1016/j.trd.2024.104399","url":null,"abstract":"<div><div>Unpredictable large amount of travel demands often occurs in urban area, and e-hailing services are often used as an important travel modal for mitigating such surge traffic. Effective pricing and scheduling strategies are urgently needed to optimize e-hailing vehicle supply and enhance evacuation efficiency during mass gathering events. Based on the method of Macroscopic Fundamental Diagram (MFD), mathematical models are presented to characterize the time-varying evolution of both e-hailing vehicles and other vehicles within a two-region transport system, and management approaches are also provided to improve the evacuation process. Considering drivers’ repositioning decisions and passengers’ demand dynamics, a region-dependent pricing strategy is developed for rapid massive evacuation. In the numerical examples, it is observed that the region-dependent pricing strategy effectively allocates a more balanced distribution of vacant vehicle supply, despite higher generalized wage for drivers and increased generalized cost for passengers. More importantly, the region-dependent pricing strategy can significantly shorten total evacuation time, and lead to more stable traffic condition.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104399"},"PeriodicalIF":7.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-11-01DOI: 10.1016/j.trd.2024.104450
Mushtaq Ahmad , Zhang Jida , Izhar Ul Haq , Muhammad Tufail , Shah Saud
Climate change and global warming pose severe environmental challenges globally, with transportation and industrialization significantly contributing to CO2 emissions. This study investigates the interplay between green transport initiatives, environmental taxes, and CO2 emissions in energy transition countries from 1990 to 2020. Utilizing the Method of Moments Quantile Regression (MMQR), Fully Modified Ordinary Least Squares (FMOLS), and Feasible Generalized Least Squares (FGLS), the study reveals that environmental taxes (ETax) and green transport (GT) are strongly negatively correlated with CO2 emissions. These results underscore the potential of increasing environmental taxes and advancing green transportation technologies as effective strategies for mitigating environmental degradation. This study highlights that improvements in energy efficiency and renewable energy adoption further contribute to reducing CO2 emissions, while globalization (GI) also plays a role in decreasing emissions. This research adds to the existing literature by providing robust empirical evidence on the effectiveness of green policies and sustainable practices in reducing CO2 emissions, thereby offering policy recommendations for governments to enhance green transportation and promote environmental sustainability in the long term.
{"title":"Linking green transportation and technology, and environmental taxes for transport carbon emissions","authors":"Mushtaq Ahmad , Zhang Jida , Izhar Ul Haq , Muhammad Tufail , Shah Saud","doi":"10.1016/j.trd.2024.104450","DOIUrl":"10.1016/j.trd.2024.104450","url":null,"abstract":"<div><div>Climate change and global warming pose severe environmental challenges globally, with transportation and industrialization significantly contributing to CO2 emissions. This study investigates the interplay between green transport initiatives, environmental taxes, and CO2 emissions in energy transition countries from 1990 to 2020. Utilizing the Method of Moments Quantile Regression (MMQR), Fully Modified Ordinary Least Squares (FMOLS), and Feasible Generalized Least Squares (FGLS), the study reveals that environmental taxes (ETax) and green transport (GT) are strongly negatively correlated with CO2 emissions. These results underscore the potential of increasing environmental taxes and advancing green transportation technologies as effective strategies for mitigating environmental degradation. This study highlights that improvements in energy efficiency and renewable energy adoption further contribute to reducing CO2 emissions, while globalization (GI) also plays a role in decreasing emissions. This research adds to the existing literature by providing robust empirical evidence on the effectiveness of green policies and sustainable practices in reducing CO2 emissions, thereby offering policy recommendations for governments to enhance green transportation and promote environmental sustainability in the long term.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104450"},"PeriodicalIF":7.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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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