Pub Date : 2025-02-01DOI: 10.1080/15568318.2024.2448004
Mengjie Han , Johan Håkansson , Tony Svensson , Xiaoyun Zhao
Urban and transport planning can strongly affect energy usage induced by travel in cities. However, most studies investigate large cities with crude measurements of induced travel without consideration of the urban configuration of residences and their trip destinations, and little attention has been paid to smaller cities. We investigate energy usage (CO2-emissions) from car travel in a small Swedish city using a novel approach based on detailed GPS-tracking data of actual car mobility to calculate CO2-emissions on street segments and to identify major destinations. We also construct configuration scenarios, applied to the case city. These scenarios’ induced CO2 emission from transports is evaluated in relation to the current configuration of the city. We find that changes in the urban configuration can impact on energy usage from intra-urban car travel by some 40% compared to the current situation and that the configurations display large relative differences in transport-efficiency, polycentric and public transport-based configurations being more efficient than monocentric development. We conclude that housing allocation is less important for car transport efficiency than re-location of existing destination points. Urban planning needs to be critical to over-simplified densification strategies and analyze the urban configuration to find optimal solutions.
{"title":"Planning for energy-efficient transport in a small town: Influence from different urban configurations of destination points and housing establishments","authors":"Mengjie Han , Johan Håkansson , Tony Svensson , Xiaoyun Zhao","doi":"10.1080/15568318.2024.2448004","DOIUrl":"10.1080/15568318.2024.2448004","url":null,"abstract":"<div><div>Urban and transport planning can strongly affect energy usage induced by travel in cities. However, most studies investigate large cities with crude measurements of induced travel without consideration of the urban configuration of residences and their trip destinations, and little attention has been paid to smaller cities. We investigate energy usage (CO<sub>2</sub>-emissions) from car travel in a small Swedish city using a novel approach based on detailed GPS-tracking data of actual car mobility to calculate CO<sub>2</sub>-emissions on street segments and to identify major destinations. We also construct configuration scenarios, applied to the case city. These scenarios’ induced CO<sub>2</sub> emission from transports is evaluated in relation to the current configuration of the city. We find that changes in the urban configuration can impact on energy usage from intra-urban car travel by some 40% compared to the current situation and that the configurations display large relative differences in transport-efficiency, polycentric and public transport-based configurations being more efficient than monocentric development. We conclude that housing allocation is less important for car transport efficiency than re-location of existing destination points. Urban planning needs to be critical to over-simplified densification strategies and analyze the urban configuration to find optimal solutions.</div></div>","PeriodicalId":47824,"journal":{"name":"International Journal of Sustainable Transportation","volume":"19 2","pages":"Pages 121-132"},"PeriodicalIF":3.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-02-01DOI: 10.1080/15568318.2024.2449436
Jose Acedo Aguilar , Shian Wang
This article offers a comprehensive summary of the profound impacts stemming from the integration of electric vehicles (EVs) into traffic-power systems. While the introduction of EVs promises to curtail greenhouse gas (GHG) emissions within the automotive sector, it could trigger a cascade of effects across the intertwined traffic-power system. These ramifications manifest in several key areas, including (i) shifts in driver behavior and route choice, (ii) alterations in energy consumption patterns, (iii) the expansion and placement of charging infrastructure, and (iv) the evolving demands placed on the electric grid. Although the current penetration rate of EVs remains relatively low, their increasing presence on the road will inevitably amplify these consequences, leading to altered traffic dynamics, more conservative driving behavior to reduce energy consumption, and an uptick in electricity demand during charging periods. This review meticulously summarizes the multifaceted effects of EV integration in these domains and outlines various strategies and technologies aimed at mitigating these challenges. These include eco-driving techniques that leverage intelligent vehicle controls to minimize energy consumption, innovative charging schemes to flatten the electricity demand curve, and the implementation of vehicle-to-everything (V2X) communication enabling vehicles to better respond to their surroundings, among others. In summary, this review seeks to consolidate the current academic consensus regarding EV performance within the integrated traffic-power network while paving the way for future research directions in this dynamic field.
{"title":"Impacts of electric vehicles on traffic-power systems: A review","authors":"Jose Acedo Aguilar , Shian Wang","doi":"10.1080/15568318.2024.2449436","DOIUrl":"10.1080/15568318.2024.2449436","url":null,"abstract":"<div><div>This article offers a comprehensive summary of the profound impacts stemming from the integration of electric vehicles (EVs) into traffic-power systems. While the introduction of EVs promises to curtail greenhouse gas (GHG) emissions within the automotive sector, it could trigger a cascade of effects across the intertwined traffic-power system. These ramifications manifest in several key areas, including (i) shifts in driver behavior and route choice, (ii) alterations in energy consumption patterns, (iii) the expansion and placement of charging infrastructure, and (iv) the evolving demands placed on the electric grid. Although the current penetration rate of EVs remains relatively low, their increasing presence on the road will inevitably amplify these consequences, leading to altered traffic dynamics, more conservative driving behavior to reduce energy consumption, and an uptick in electricity demand during charging periods. This review meticulously summarizes the multifaceted effects of EV integration in these domains and outlines various strategies and technologies aimed at mitigating these challenges. These include eco-driving techniques that leverage intelligent vehicle controls to minimize energy consumption, innovative charging schemes to flatten the electricity demand curve, and the implementation of vehicle-to-everything (V2X) communication enabling vehicles to better respond to their surroundings, among others. In summary, this review seeks to consolidate the current academic consensus regarding EV performance within the integrated traffic-power network while paving the way for future research directions in this dynamic field.</div></div>","PeriodicalId":47824,"journal":{"name":"International Journal of Sustainable Transportation","volume":"19 2","pages":"Pages 103-120"},"PeriodicalIF":3.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-02-01DOI: 10.1080/15568318.2025.2454693
Jen-Jia Lin , Qing-Qian Guo , Hung-Chi Liu
In recent years, moped-sharing services have become popular in Asian and European cities, but existing literature provides limited information about factors influencing moped-sharing use. This research explored the associations of built environments with the probabilities that idle shared mopeds become rented through survival analyses. The study observations are from the global positioning system records of an anonymous moped-sharing operator in Taipei, Taiwan. The empirical results indicate the following findings: (1) The associations of density and diversity attributes with moped-sharing use can refer to those of other shared vehicle uses but are dissimilar to those of general mopeds. (2) Moped-sharing service operators are suggested to move idle shared mopeds from employment centers to areas with dense residential, school, or retailing activities; diverse floor uses, industries, or transit services; and dense streetlights or moped parking spaces. (3) Moped-sharing service operators are also suggested to develop vehicle-rebalancing strategies in accordance with the built environment attributes within different catchment area sizes and periods. (4) Moped sharing is a complementary service rather than a competitive service to other intracity public transport services.
{"title":"Associations of built environment with moped-sharing use: A vehicle-based approach","authors":"Jen-Jia Lin , Qing-Qian Guo , Hung-Chi Liu","doi":"10.1080/15568318.2025.2454693","DOIUrl":"10.1080/15568318.2025.2454693","url":null,"abstract":"<div><div>In recent years, moped-sharing services have become popular in Asian and European cities, but existing literature provides limited information about factors influencing moped-sharing use. This research explored the associations of built environments with the probabilities that idle shared mopeds become rented through survival analyses. The study observations are from the global positioning system records of an anonymous moped-sharing operator in Taipei, Taiwan. The empirical results indicate the following findings: (1) The associations of density and diversity attributes with moped-sharing use can refer to those of other shared vehicle uses but are dissimilar to those of general mopeds. (2) Moped-sharing service operators are suggested to move idle shared mopeds from employment centers to areas with dense residential, school, or retailing activities; diverse floor uses, industries, or transit services; and dense streetlights or moped parking spaces. (3) Moped-sharing service operators are also suggested to develop vehicle-rebalancing strategies in accordance with the built environment attributes within different catchment area sizes and periods. (4) Moped sharing is a complementary service rather than a competitive service to other intracity public transport services.</div></div>","PeriodicalId":47824,"journal":{"name":"International Journal of Sustainable Transportation","volume":"19 2","pages":"Pages 133-148"},"PeriodicalIF":3.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-02-01DOI: 10.1080/15568318.2025.2459614
Shuping Wu , Zan Yang , Shuyang Yao
This study employs a difference-in-difference (DID) regression to estimate the impact of high-speed rail (HSR) on city-level household carbon dioxide emissions across various consumption categories. The DID analysis is based on a sample of 179 Chinese cities during 2010-2018, and reveals a positive association between HSR and household carbon dioxide emissions. The findings suggest that cities with HSR emit more carbon dioxide due to increased daily consumption, and this effect grows over time. The mechanism analysis shows that the development of HSR stimulates household income growth, leading to increased consumption-based carbon dioxide in cities with HSR. Despite being considered a green transportation mode with a low carbon footprint, this research highlights potential environmental burdens associated with HSR, emphasizing the need for sustainable HSR development and environmental management policies.
{"title":"Impacts of high-speed rail on household carbon dioxide emissions: Evidence from China","authors":"Shuping Wu , Zan Yang , Shuyang Yao","doi":"10.1080/15568318.2025.2459614","DOIUrl":"10.1080/15568318.2025.2459614","url":null,"abstract":"<div><div>This study employs a difference-in-difference (DID) regression to estimate the impact of high-speed rail (HSR) on city-level household carbon dioxide emissions across various consumption categories. The DID analysis is based on a sample of 179 Chinese cities during 2010-2018, and reveals a positive association between HSR and household carbon dioxide emissions. The findings suggest that cities with HSR emit more carbon dioxide due to increased daily consumption, and this effect grows over time. The mechanism analysis shows that the development of HSR stimulates household income growth, leading to increased consumption-based carbon dioxide in cities with HSR. Despite being considered a green transportation mode with a low carbon footprint, this research highlights potential environmental burdens associated with HSR, emphasizing the need for sustainable HSR development and environmental management policies.</div></div>","PeriodicalId":47824,"journal":{"name":"International Journal of Sustainable Transportation","volume":"19 2","pages":"Pages 149-164"},"PeriodicalIF":3.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-02-01DOI: 10.1080/15568318.2025.2460637
Steven R. Gehrke , Manoj Kumar Allam , Armando E. Martinez , Ty M. Holliday , Brendan J. Russo , Edward J. Smaglik
The further motivation of bicycling as a utilitarian travel alternative has been identified as a viable solution to address societal concerns regarding physical inactivity, climate change, and transportation inequities. Yet, a profound increase in bicycling activity for many cities remains elusive to policymakers, practitioners, and researchers largely because of the inability to attract new bicyclists via safer bicycling infrastructure provision. To better understand current bicycling barriers to its future adoption, this study describes the advancement of the Cyclist Routing Algorithm for Network Connectivity (CRANC) and its application as an accessibility-oriented transportation planning tool in eight Arizona metropolitan regions. CRANC, an innovative bicyclist routing platform sensitive to bike network conditions and the varying traffic safety concerns of cyclist types (interested but concerned, enthused and confident, strong and fearless), is designed to support utilitarian bicycling promotion by identifying its latent demand. In this application, local and regional discrepancies in bicycling accessibility to jobs, schools, and grocery stores are identified and visualized by integrating the concepts of cyclist types and bicycle level of traffic stress into a new bicycling accessibility metric. Study findings show significant differences in place-based bicycling accessibility across key sociodemographic and economic indicators for the interested but concerned cyclist type, who prefers dedicated bike facilities, slower vehicle speeds, and lower traffic volumes. A recognition of these variations is important for promoting equitable bicycling access to subsistence and maintenance activities for those individuals who do not presently use this sustainable mode but would if barriers to access were removed.
{"title":"Cycling accessibility to employment, schools, and grocery stores in Arizona metropolitan regions","authors":"Steven R. Gehrke , Manoj Kumar Allam , Armando E. Martinez , Ty M. Holliday , Brendan J. Russo , Edward J. Smaglik","doi":"10.1080/15568318.2025.2460637","DOIUrl":"10.1080/15568318.2025.2460637","url":null,"abstract":"<div><div>The further motivation of bicycling as a utilitarian travel alternative has been identified as a viable solution to address societal concerns regarding physical inactivity, climate change, and transportation inequities. Yet, a profound increase in bicycling activity for many cities remains elusive to policymakers, practitioners, and researchers largely because of the inability to attract new bicyclists <em>via</em> safer bicycling infrastructure provision. To better understand current bicycling barriers to its future adoption, this study describes the advancement of the Cyclist Routing Algorithm for Network Connectivity (CRANC) and its application as an accessibility-oriented transportation planning tool in eight Arizona metropolitan regions. CRANC, an innovative bicyclist routing platform sensitive to bike network conditions and the varying traffic safety concerns of cyclist types (interested but concerned, enthused and confident, strong and fearless), is designed to support utilitarian bicycling promotion by identifying its latent demand. In this application, local and regional discrepancies in bicycling accessibility to jobs, schools, and grocery stores are identified and visualized by integrating the concepts of cyclist types and bicycle level of traffic stress into a new bicycling accessibility metric. Study findings show significant differences in place-based bicycling accessibility across key sociodemographic and economic indicators for the interested but concerned cyclist type, who prefers dedicated bike facilities, slower vehicle speeds, and lower traffic volumes. A recognition of these variations is important for promoting equitable bicycling access to subsistence and maintenance activities for those individuals who do not presently use this sustainable mode but would if barriers to access were removed.</div></div>","PeriodicalId":47824,"journal":{"name":"International Journal of Sustainable Transportation","volume":"19 2","pages":"Pages 180-193"},"PeriodicalIF":3.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-02-01DOI: 10.1080/15568318.2025.2459616
Nicola Amati , Luis M. Castellanos Molina , Alessandro Mancarella , Omar Marello , Mario Silvagni
This paper describes a methodology to develop simple energy consumption models of road vehicles exploiting transient experimental datasets obtained from a vehicle/powertrain four-dyno testbed available at the Center for Automotive Research and Sustainable mobility (CARS@POLITO) of Politecnico di Torino. These models, based on a locally weighted linear regression method, can serve as a simpler alternative to more conventional methods based, for example, on engine maps obtained by steady-state characterization at engine testbeds, and combined with powertrain subsystem models. The present methodology was applied to a conventional diesel-powered vehicle. Three different modeling approaches are proposed: vehicle-based (VB), engine-based (EB) and engine-based modified (EB*). The VB approach is the simplest, being able to estimate the vehicle fuel consumption by only using, as inputs, wheel torque and speed, while the EB and EB* approaches enhance modeling accuracy by using engine speed and torque, as inputs, along with transmission-related parameters and/or by considering the moments of inertia of the powertrain rotating parts. The manuscript describes, in full, the process used to develop these models, providing significant guidance for researchers who may want to replicate the procedure with their own experimental data. These energy consumption models can be useful tools for the development and assessment of eco-driving or ADAS functions or for energy consumption comparison between different vehicles that were not tested on the same driving cycle. They can also support the estimation of the total energy consumption of vehicles along different traffic conditions or routes, based on a limited number of experiments and low computational effort.
{"title":"Methodology for developing models to estimate vehicle instantaneous energy consumption based on hub-type dyno test data","authors":"Nicola Amati , Luis M. Castellanos Molina , Alessandro Mancarella , Omar Marello , Mario Silvagni","doi":"10.1080/15568318.2025.2459616","DOIUrl":"10.1080/15568318.2025.2459616","url":null,"abstract":"<div><div>This paper describes a methodology to develop simple energy consumption models of road vehicles exploiting transient experimental datasets obtained from a vehicle/powertrain four-dyno testbed available at the Center for Automotive Research and Sustainable mobility (CARS@POLITO) of Politecnico di Torino. These models, based on a locally weighted linear regression method, can serve as a simpler alternative to more conventional methods based, for example, on engine maps obtained by steady-state characterization at engine testbeds, and combined with powertrain subsystem models. The present methodology was applied to a conventional diesel-powered vehicle. Three different modeling approaches are proposed: vehicle-based (VB), engine-based (EB) and engine-based modified (EB*). The VB approach is the simplest, being able to estimate the vehicle fuel consumption by only using, as inputs, wheel torque and speed, while the EB and EB* approaches enhance modeling accuracy by using engine speed and torque, as inputs, along with transmission-related parameters and/or by considering the moments of inertia of the powertrain rotating parts. The manuscript describes, in full, the process used to develop these models, providing significant guidance for researchers who may want to replicate the procedure with their own experimental data. These energy consumption models can be useful tools for the development and assessment of eco-driving or ADAS functions or for energy consumption comparison between different vehicles that were not tested on the same driving cycle. They can also support the estimation of the total energy consumption of vehicles along different traffic conditions or routes, based on a limited number of experiments and low computational effort.</div></div>","PeriodicalId":47824,"journal":{"name":"International Journal of Sustainable Transportation","volume":"19 2","pages":"Pages 165-179"},"PeriodicalIF":3.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-01-02DOI: 10.1080/15568318.2024.2443827
Xinyi Wu , Yan Zhou , David Gohlke , Jarod Kelly
The electrification of light-duty vehicles (LDVs) is essential for decarbonizing the transportation sector in the United States. Both federal and state governments have begun promoting and incentivizing the adoption of plug-in electric vehicle (PEV) (battery electric vehicles (BEV) and plug-in hybrid electric vehicles (PHEV)) to reduce LDV greenhouse gas (GHG) emissions greatly. However, there remains a critical need for a robust methodology to accurately quantify the distributed emissions impacts of PEV adoption at a granular regional level. Additionally, the role of electricity traded across electrical grids in regional GHG mitigation efforts often goes unrecognized. This study addresses these gaps by developing a top-down approach for assessing county-level emissions benefits arising from PEV adoption while accounting for upstream emissions due to electricity flow across regions. Our findings underscore the significant influence of regional variations in future PEV adoption rates and vehicle usage patterns on emissions reduction potential. Nevertheless, these benefits can be tempered by local emission intensities associated with electricity generation. Importantly, our study reaffirms the necessity of considering electricity flow dynamics across grids in estimating local GHG mitigation outcomes.
{"title":"Light-duty plug-in electric vehicle adoption: County-level emissions benefits using consumption-based emissions intensities","authors":"Xinyi Wu , Yan Zhou , David Gohlke , Jarod Kelly","doi":"10.1080/15568318.2024.2443827","DOIUrl":"10.1080/15568318.2024.2443827","url":null,"abstract":"<div><div>The electrification of light-duty vehicles (LDVs) is essential for decarbonizing the transportation sector in the United States. Both federal and state governments have begun promoting and incentivizing the adoption of plug-in electric vehicle (PEV) (battery electric vehicles (BEV) and plug-in hybrid electric vehicles (PHEV)) to reduce LDV greenhouse gas (GHG) emissions greatly. However, there remains a critical need for a robust methodology to accurately quantify the distributed emissions impacts of PEV adoption at a granular regional level. Additionally, the role of electricity traded across electrical grids in regional GHG mitigation efforts often goes unrecognized. This study addresses these gaps by developing a top-down approach for assessing county-level emissions benefits arising from PEV adoption while accounting for upstream emissions due to electricity flow across regions. Our findings underscore the significant influence of regional variations in future PEV adoption rates and vehicle usage patterns on emissions reduction potential. Nevertheless, these benefits can be tempered by local emission intensities associated with electricity generation. Importantly, our study reaffirms the necessity of considering electricity flow dynamics across grids in estimating local GHG mitigation outcomes.</div></div>","PeriodicalId":47824,"journal":{"name":"International Journal of Sustainable Transportation","volume":"19 1","pages":"Pages 72-82"},"PeriodicalIF":3.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-01-02DOI: 10.1080/15568318.2024.2443821
Yang Zhao , Peijun Li , Yuan Zhang , Xiaoxia Li , Fan Zhang
The automotive industry is undergoing transformative changes propelled by the progress in technology, considerations for the environment, and the evolving tastes of consumers. This quantitative research endeavors to investigate the impact of data-driven advancements in the automotive sector. The research methodology employed a purposive sampling technique, targeting diverse stakeholders within the Chinese automotive industry. A structured questionnaire served as the primary data collection tool. Through direct interactions and visits, 900 questionnaires were distributed over three days, yielding a robust response of 850 returned surveys. Following the removal of invalid responses, the study culled valid data from 800 participants. The collected data underwent analysis using SPSS statistical software. Findings reveal significant trends in the industry, such as the increasing adoption of electric vehicles, evolving customer preferences for advanced features, and the potential impact of ride-sharing and car-sharing services on individual car ownership. Furthermore, the investigation identifies the crucial role of data analysis, predictive analytics, IoT devices, and big data in shaping various aspects of the automotive sector. The study’s novelty lies in its quantitative approach, providing objective insights into demographic characteristics, industry trends, and participants’ perspectives. The study’s exploration of data-driven design processes and their role in fostering innovation and user-friendly vehicles adds a distinctive layer to understanding the transformative impact of data science on automotive development. Overall, this research contributes valuable knowledge for industry practitioners, policymakers, and scholars interested in the intersection of data science and automotive advancements.
{"title":"Sustainable transportation through data science: Case studies from the automotive industry","authors":"Yang Zhao , Peijun Li , Yuan Zhang , Xiaoxia Li , Fan Zhang","doi":"10.1080/15568318.2024.2443821","DOIUrl":"10.1080/15568318.2024.2443821","url":null,"abstract":"<div><div>The automotive industry is undergoing transformative changes propelled by the progress in technology, considerations for the environment, and the evolving tastes of consumers. This quantitative research endeavors to investigate the impact of data-driven advancements in the automotive sector. The research methodology employed a purposive sampling technique, targeting diverse stakeholders within the Chinese automotive industry. A structured questionnaire served as the primary data collection tool. Through direct interactions and visits, 900 questionnaires were distributed over three days, yielding a robust response of 850 returned surveys. Following the removal of invalid responses, the study culled valid data from 800 participants. The collected data underwent analysis using SPSS statistical software. Findings reveal significant trends in the industry, such as the increasing adoption of electric vehicles, evolving customer preferences for advanced features, and the potential impact of ride-sharing and car-sharing services on individual car ownership. Furthermore, the investigation identifies the crucial role of data analysis, predictive analytics, IoT devices, and big data in shaping various aspects of the automotive sector. The study’s novelty lies in its quantitative approach, providing objective insights into demographic characteristics, industry trends, and participants’ perspectives. The study’s exploration of data-driven design processes and their role in fostering innovation and user-friendly vehicles adds a distinctive layer to understanding the transformative impact of data science on automotive development. Overall, this research contributes valuable knowledge for industry practitioners, policymakers, and scholars interested in the intersection of data science and automotive advancements.</div></div>","PeriodicalId":47824,"journal":{"name":"International Journal of Sustainable Transportation","volume":"19 1","pages":"Pages 55-71"},"PeriodicalIF":3.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-01-02DOI: 10.1080/15568318.2024.2447999
Rachit Soni , Akshay Dvivedi , Pradeep Kumar
GHGs significantly impact climate change, adversely affecting both the environment and human well-being. As energy production and transportation are among the primary contributors to these emissions, many nations have implemented strategies to transition to renewable energy and reduce emissions by 2050-2070. This review focuses on identifying effective policies and pathways to achieve carbon neutrality in the transport supply chain. A bibliometric analysis highlights the growing importance of hydrogen and biomass-generated energy. Key trends include alternative fuels, hydrogen, electric vehicles, solar and wind energy, carbon neutrality, and GHG mitigation. In both the short and long term, integrating green transportation innovations, renewable energy consumption, and sustainable economic growth can substantially lower carbon emissions. Factors such as population growth, urbanization rates, coal consumption, renewable energy adoption, and the increasing use of electric vehicles (EVs) are emerging as critical drivers of environmental sustainability and net-zero emission goals. Policymakers are strongly encouraged to prioritize and implement optimal strategies that capitalize on these opportunities to advance carbon neutrality objectives.
{"title":"Carbon neutrality in transportation: In the context of renewable sources","authors":"Rachit Soni , Akshay Dvivedi , Pradeep Kumar","doi":"10.1080/15568318.2024.2447999","DOIUrl":"10.1080/15568318.2024.2447999","url":null,"abstract":"<div><div>GHGs significantly impact climate change, adversely affecting both the environment and human well-being. As energy production and transportation are among the primary contributors to these emissions, many nations have implemented strategies to transition to renewable energy and reduce emissions by 2050-2070. This review focuses on identifying effective policies and pathways to achieve carbon neutrality in the transport supply chain. A bibliometric analysis highlights the growing importance of hydrogen and biomass-generated energy. Key trends include alternative fuels, hydrogen, electric vehicles, solar and wind energy, carbon neutrality, and GHG mitigation. In both the short and long term, integrating green transportation innovations, renewable energy consumption, and sustainable economic growth can substantially lower carbon emissions. Factors such as population growth, urbanization rates, coal consumption, renewable energy adoption, and the increasing use of electric vehicles (EVs) are emerging as critical drivers of environmental sustainability and net-zero emission goals. Policymakers are strongly encouraged to prioritize and implement optimal strategies that capitalize on these opportunities to advance carbon neutrality objectives.</div></div>","PeriodicalId":47824,"journal":{"name":"International Journal of Sustainable Transportation","volume":"19 1","pages":"Pages 1-15"},"PeriodicalIF":3.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the last decade, the popularity of e-bikes has increased as they have shown potential to relieve congestion and aid the environment. However, with the increase of their popularity, there has been also an increase in their traffic crashes. This study aims to understand factors playing a role in the e-bike crash injury outcomes. The analysis uses 1,351 records of e-bike crashes to estimate random parameters multinomial logit models with heterogeneity in the means and variances of random parameters in four groups. This paper also seeks to provide insights into e-bike crash injury severities across gender (female versus male) and lighting conditions (daytime and nighttime) specific models. Numerous likelihood ratio tests were performed to justify splitting the data. It was found that a variety of factors relating to the weather and road characteristics, crash type, and rider’s demographics play a role in crash outcomes. Particularly interesting are findings relating to the rollover crashes increasing the likelihood of severe outcomes as well as gender specific effects with, for example, male riders have a higher probability of severe injuries during peak traffic hours. The findings can be used to support e-bike safety as well as advocate for a more nuanced and inclusive approach relating to e-bike travel.
{"title":"E-bike crashes: Who they affect and which circumstances to avoid?","authors":"Yuntong Zhou , Natalia Barbour , Mohamed Abdel-Aty , Xin Gu , Yanyan Chen","doi":"10.1080/15568318.2024.2447993","DOIUrl":"10.1080/15568318.2024.2447993","url":null,"abstract":"<div><div>In the last decade, the popularity of e-bikes has increased as they have shown potential to relieve congestion and aid the environment. However, with the increase of their popularity, there has been also an increase in their traffic crashes. This study aims to understand factors playing a role in the e-bike crash injury outcomes. The analysis uses 1,351 records of e-bike crashes to estimate random parameters multinomial logit models with heterogeneity in the means and variances of random parameters in four groups. This paper also seeks to provide insights into e-bike crash injury severities across gender (female versus male) and lighting conditions (daytime and nighttime) specific models. Numerous likelihood ratio tests were performed to justify splitting the data. It was found that a variety of factors relating to the weather and road characteristics, crash type, and rider’s demographics play a role in crash outcomes. Particularly interesting are findings relating to the rollover crashes increasing the likelihood of severe outcomes as well as gender specific effects with, for example, male riders have a higher probability of severe injuries during peak traffic hours. The findings can be used to support e-bike safety as well as advocate for a more nuanced and inclusive approach relating to e-bike travel.</div></div>","PeriodicalId":47824,"journal":{"name":"International Journal of Sustainable Transportation","volume":"19 1","pages":"Pages 83-101"},"PeriodicalIF":3.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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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