Pub Date : 2024-09-19DOI: 10.1177/03611981241272090
Chang Xu, Qingwei Zeng, Lei Chen, Shunxin Yang
An increase in the number of work zones on roads and highways will result in more costs from the increased frequency of maintenance and rehabilitation (M&R) equipment transfers. The number of M&R decision-making segments can affect decision-making efficiency and the number of work zones. Fixed segmentation and traditional dynamic homogeneous segmentation techniques, such as the cumulative difference approach (CDA) and K-means algorithms, cannot determine the optimal number of decision-making segments. To address this issue, this paper proposes a method to develop a multi-year asphalt pavement M&R plan that incorporates homogeneous road segmentation based on an ordinal clustering approach (OCA). The proposed method first applies an ordinal clustering approach to the survey units to identify homogeneous segments. These segments are then incorporated into a multi-year asphalt pavement M&R optimization decision-making model to determine the M&R plan. Data from 2022 covering 15.9 km of continuous asphalt pavement on the Donglv Highway in Shanxi Province were selected for analysis. These results demonstrate: 1) the OCA exhibits superior decision-making accuracy compared with the CDA; 2) compared with the M&R plans for survey units and CDA for homogeneous segments, the proposed method's M&R plan can be resolved faster and see fewer work zones, all achieved with a similar level of investment and meeting performance improvement; and 3) the M&R plan generated using the proposed method requires lower M&R investment but achieves higher performance compared with the actual M&R plan. These findings validate the effectiveness of the proposed method in producing improved M&R plans.
{"title":"Ordinal Clustering Based Homogeneous Road Segments in Asphalt Pavement Maintenance and Rehabilitation Optimized Decision-Making","authors":"Chang Xu, Qingwei Zeng, Lei Chen, Shunxin Yang","doi":"10.1177/03611981241272090","DOIUrl":"https://doi.org/10.1177/03611981241272090","url":null,"abstract":"An increase in the number of work zones on roads and highways will result in more costs from the increased frequency of maintenance and rehabilitation (M&R) equipment transfers. The number of M&R decision-making segments can affect decision-making efficiency and the number of work zones. Fixed segmentation and traditional dynamic homogeneous segmentation techniques, such as the cumulative difference approach (CDA) and K-means algorithms, cannot determine the optimal number of decision-making segments. To address this issue, this paper proposes a method to develop a multi-year asphalt pavement M&R plan that incorporates homogeneous road segmentation based on an ordinal clustering approach (OCA). The proposed method first applies an ordinal clustering approach to the survey units to identify homogeneous segments. These segments are then incorporated into a multi-year asphalt pavement M&R optimization decision-making model to determine the M&R plan. Data from 2022 covering 15.9 km of continuous asphalt pavement on the Donglv Highway in Shanxi Province were selected for analysis. These results demonstrate: 1) the OCA exhibits superior decision-making accuracy compared with the CDA; 2) compared with the M&R plans for survey units and CDA for homogeneous segments, the proposed method's M&R plan can be resolved faster and see fewer work zones, all achieved with a similar level of investment and meeting performance improvement; and 3) the M&R plan generated using the proposed method requires lower M&R investment but achieves higher performance compared with the actual M&R plan. These findings validate the effectiveness of the proposed method in producing improved M&R plans.","PeriodicalId":517391,"journal":{"name":"Transportation Research Record: Journal of the Transportation Research Board","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-18DOI: 10.1177/03611981241274156
Tanmoy Bhowmik, Naveen Eluru
This study explores the dynamic relationship between COVID-19 transmission and transportation mobility, with an emphasis on understanding the time-varying bidirectional interplay across the different phases of the pandemic. To gain insight into this relationship, we analyzed county-level data on transmission and mobility patterns from the United States over a 74-week period using a comprehensive list of factors including: temporal factors, socio-demographics, health indicators, health care infrastructure attributes, and spatial factors. For our analysis, we proposed a simultaneous econometric model system that explicitly accounts for the bidirectional relationship between COVID-19 transmission and mobility patterns while also accounting for the influence of common unobserved factors on the two variables. The model results strongly support our hypothesis that COVID-19 transmission and mobility patterns are interconnected. Further, our findings show distinct phases of the bidirectional relationship influenced by behavior changes, vaccine availability, and the emergence of new variants. Additionally, we conducted a validation exercise on a hold-out sample to assess the robustness of our model. The results confirm the superiority of the simultaneous model system with enhanced interpretability and prediction capability. By analyzing data from several weeks for the COVID-19 pandemic, our study provides valuable insights into the evolving dynamics and potential strategies for future pandemics.
{"title":"Exploring the Relationship Between COVID-19 Transmission and Population Mobility over Time","authors":"Tanmoy Bhowmik, Naveen Eluru","doi":"10.1177/03611981241274156","DOIUrl":"https://doi.org/10.1177/03611981241274156","url":null,"abstract":"This study explores the dynamic relationship between COVID-19 transmission and transportation mobility, with an emphasis on understanding the time-varying bidirectional interplay across the different phases of the pandemic. To gain insight into this relationship, we analyzed county-level data on transmission and mobility patterns from the United States over a 74-week period using a comprehensive list of factors including: temporal factors, socio-demographics, health indicators, health care infrastructure attributes, and spatial factors. For our analysis, we proposed a simultaneous econometric model system that explicitly accounts for the bidirectional relationship between COVID-19 transmission and mobility patterns while also accounting for the influence of common unobserved factors on the two variables. The model results strongly support our hypothesis that COVID-19 transmission and mobility patterns are interconnected. Further, our findings show distinct phases of the bidirectional relationship influenced by behavior changes, vaccine availability, and the emergence of new variants. Additionally, we conducted a validation exercise on a hold-out sample to assess the robustness of our model. The results confirm the superiority of the simultaneous model system with enhanced interpretability and prediction capability. By analyzing data from several weeks for the COVID-19 pandemic, our study provides valuable insights into the evolving dynamics and potential strategies for future pandemics.","PeriodicalId":517391,"journal":{"name":"Transportation Research Record: Journal of the Transportation Research Board","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1177/03611981241270167
Jianhong Ye, Yifei Qin, Guanpei Luo, Yifan Hu, Meigen Xue
In the coordinated development of urban agglomerations in China, inter-city connections within urban agglomerations have been gradually strengthened, with more interprovincial highways built. Given the complex geological conditions, interprovincial highways often require tunnels. The construction of tunnel ventilation facilities needs to take into account the types of vehicle, traffic flows, and the market share of different vehicle powertrains using the highways. This paper aims to develop a method to predict the future market share of the powertrains of different types of vehicle on the interprovincial highway. The paper builds a policy cluster by analyzing the regional policies for new energy vehicles and then builds a parameter cluster by summarizing industry reports, expert opinion, and policy clusters to predict the market share of different vehicle types categorized by powertrains. Finally, based on the historical vehicle stock data, and using vehicle sales and scrappage rate models, the paper builds a future stock cluster to estimate the annual stock share of different vehicle powertrains up to 2045. The paper applies the method to the interprovincial highway S7 in the Yangtze River Delta urban agglomeration. It obtains the future trend of the market share of the powertrains of different vehicle types on S7 in the target year, validating the model. The results show that the share of new energy vehicles on the S7 highway will increase gradually until 2025. Electric vehicles will dominate the growth, with light trucks forming the highest proportion, followed by cars, and finally buses and heavy trucks.
{"title":"Prediction of Market Share of Different Vehicle Powertrains on Interprovincial Highways amid the Development of Urban Agglomerations","authors":"Jianhong Ye, Yifei Qin, Guanpei Luo, Yifan Hu, Meigen Xue","doi":"10.1177/03611981241270167","DOIUrl":"https://doi.org/10.1177/03611981241270167","url":null,"abstract":"In the coordinated development of urban agglomerations in China, inter-city connections within urban agglomerations have been gradually strengthened, with more interprovincial highways built. Given the complex geological conditions, interprovincial highways often require tunnels. The construction of tunnel ventilation facilities needs to take into account the types of vehicle, traffic flows, and the market share of different vehicle powertrains using the highways. This paper aims to develop a method to predict the future market share of the powertrains of different types of vehicle on the interprovincial highway. The paper builds a policy cluster by analyzing the regional policies for new energy vehicles and then builds a parameter cluster by summarizing industry reports, expert opinion, and policy clusters to predict the market share of different vehicle types categorized by powertrains. Finally, based on the historical vehicle stock data, and using vehicle sales and scrappage rate models, the paper builds a future stock cluster to estimate the annual stock share of different vehicle powertrains up to 2045. The paper applies the method to the interprovincial highway S7 in the Yangtze River Delta urban agglomeration. It obtains the future trend of the market share of the powertrains of different vehicle types on S7 in the target year, validating the model. The results show that the share of new energy vehicles on the S7 highway will increase gradually until 2025. Electric vehicles will dominate the growth, with light trucks forming the highest proportion, followed by cars, and finally buses and heavy trucks.","PeriodicalId":517391,"journal":{"name":"Transportation Research Record: Journal of the Transportation Research Board","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1177/03611981241274152
Chunxi Huang, Ange Wang, Song Yan, Dengbo He
Although automated vehicles (AVs) were considered a promising solution to enhance traffic safety by eliminating human errors, AV crashes still happen in mixed traffic consisting of human-driven vehicles and AVs. Thus, to reduce AV-involved crashes, it is necessary to understand the factors leading to AV crashes. However, traditional regression-based methods may not reveal a structured relationship among leading factors of AV crashes, which hinders the exploration of countermeasures to AV crashes. Based on the 246 AV crash records collected by the National Highway Traffic Safety Administration, this study investigated the factors associated with AV crashes. An additive Bayesian network (ABN) approach was utilized to construct the topological relationship among potential influential factors of AV crashes, followed by post-ABN regression analyses. Results show that, though AV technologies have developed rapidly in the past few years, rear-end crashes are still dominant among AV-involved crashes, potentially because of the discrepancy in the driving behaviors between AV and human-driven vehicles. The crash type of AV-involved crashes is more related to the pre-crash movements of crash partners than it is to the pre-crash movements of AVs, while crash outcomes (e.g., injury severity) are associated with the environmental factors (e.g., operating entities) and crash-procedure-related factors (e.g., crash type). Findings from this study aid in understanding AV crash patterns, which can inform targeted interventions and technology advancements to improve safety outcomes for all road users.
尽管自动驾驶汽车（AV）被认为是消除人为失误、提高交通安全的一种有前途的解决方案，但在由人类驾驶的车辆和自动驾驶汽车组成的混合交通中，自动驾驶汽车撞车事故仍然时有发生。因此，要减少涉及自动驾驶汽车的碰撞事故，就必须了解导致自动驾驶汽车碰撞事故的因素。然而，基于回归的传统方法可能无法揭示导致反车辆交通事故的主要因素之间的结构性关系，这阻碍了对反车辆交通事故对策的探索。本研究以美国国家公路交通安全管理局收集的 246 起自动驾驶汽车碰撞事故记录为基础，调查了与自动驾驶汽车碰撞事故相关的因素。研究采用加法贝叶斯网络（ABN）方法构建了自动驾驶汽车碰撞事故潜在影响因素之间的拓扑关系，然后进行了ABN后回归分析。结果表明，虽然 AV 技术在过去几年中发展迅速，但在 AV 引起的碰撞事故中，追尾碰撞事故仍占主导地位，这可能是由于 AV 车辆与人类驾驶的车辆在驾驶行为上存在差异。在涉及 AV 的撞车事故中，撞车类型与撞车伙伴的撞车前动作的关系比与 AV 的撞车前动作的关系更大，而撞车结果（如受伤严重程度）则与环境因素（如运营实体）和撞车程序相关因素（如撞车类型）有关。这项研究的结果有助于了解自动驾驶汽车的碰撞模式，从而为有针对性的干预措施和技术进步提供依据，以改善所有道路使用者的安全结果。
{"title":"Investigating the Interrelationships among Factors Associated with Automated Vehicle Crashes Using Additive Bayesian Network","authors":"Chunxi Huang, Ange Wang, Song Yan, Dengbo He","doi":"10.1177/03611981241274152","DOIUrl":"https://doi.org/10.1177/03611981241274152","url":null,"abstract":"Although automated vehicles (AVs) were considered a promising solution to enhance traffic safety by eliminating human errors, AV crashes still happen in mixed traffic consisting of human-driven vehicles and AVs. Thus, to reduce AV-involved crashes, it is necessary to understand the factors leading to AV crashes. However, traditional regression-based methods may not reveal a structured relationship among leading factors of AV crashes, which hinders the exploration of countermeasures to AV crashes. Based on the 246 AV crash records collected by the National Highway Traffic Safety Administration, this study investigated the factors associated with AV crashes. An additive Bayesian network (ABN) approach was utilized to construct the topological relationship among potential influential factors of AV crashes, followed by post-ABN regression analyses. Results show that, though AV technologies have developed rapidly in the past few years, rear-end crashes are still dominant among AV-involved crashes, potentially because of the discrepancy in the driving behaviors between AV and human-driven vehicles. The crash type of AV-involved crashes is more related to the pre-crash movements of crash partners than it is to the pre-crash movements of AVs, while crash outcomes (e.g., injury severity) are associated with the environmental factors (e.g., operating entities) and crash-procedure-related factors (e.g., crash type). Findings from this study aid in understanding AV crash patterns, which can inform targeted interventions and technology advancements to improve safety outcomes for all road users.","PeriodicalId":517391,"journal":{"name":"Transportation Research Record: Journal of the Transportation Research Board","volume":"202 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1177/03611981241275547
Min Ma, Yuan Ma
Conventional measures of protecting permafrost cannot improve embankment stability in warm permafrost regions. Therefore, based on the principle of allowing permafrost to thaw, a method of replacing the 4.5 m underlying permafrost layer with 200–400 mm diameter crushed rocks was proposed to reduce embankment settlement. To evaluate the long-term stability of the embankment in question, a hydro-thermomechanical coupling model considering condensation is established for unsaturated frozen soil; the water, heat, and deformation conditions of the embankment in 20 service years are calculated; and its working mechanism is analyzed. In addition, the optimal replacement depth of the crushed rocks is discussed from thermodynamic and economic perspectives. The results show that: (1) an increase in replacement depth can increase the permafrost table under the embankment centerline, thus improving the thermal stability of the embankment; (2) the increase in replacement depth can reduce the unfrozen water content from the deep foundation to the embankment filling layer, thus reducing the cumulative settlement; (3) if only the embankment stability is considered, the embankment stability is better with the greater replacement depth. If both stability and economy are considered, a replacement depth of 4.0 m is the optimal solution. The maximum settlement, maximum horizontal deformation, maximum uneven settlement, and maximum horizontal deformation difference of this embankment are −0.693, −0.241, 0.306, and −0.358 cm. This study provides a reference for the settlement control of embankments and the optimal design of crushed-rock embankments in warm permafrost regions.
{"title":"Evaluation of the Long-Term Thermal–Mechanical Stability of an Embankment Replaced with Crushed Rocks in Cold Regions","authors":"Min Ma, Yuan Ma","doi":"10.1177/03611981241275547","DOIUrl":"https://doi.org/10.1177/03611981241275547","url":null,"abstract":"Conventional measures of protecting permafrost cannot improve embankment stability in warm permafrost regions. Therefore, based on the principle of allowing permafrost to thaw, a method of replacing the 4.5 m underlying permafrost layer with 200–400 mm diameter crushed rocks was proposed to reduce embankment settlement. To evaluate the long-term stability of the embankment in question, a hydro-thermomechanical coupling model considering condensation is established for unsaturated frozen soil; the water, heat, and deformation conditions of the embankment in 20 service years are calculated; and its working mechanism is analyzed. In addition, the optimal replacement depth of the crushed rocks is discussed from thermodynamic and economic perspectives. The results show that: (1) an increase in replacement depth can increase the permafrost table under the embankment centerline, thus improving the thermal stability of the embankment; (2) the increase in replacement depth can reduce the unfrozen water content from the deep foundation to the embankment filling layer, thus reducing the cumulative settlement; (3) if only the embankment stability is considered, the embankment stability is better with the greater replacement depth. If both stability and economy are considered, a replacement depth of 4.0 m is the optimal solution. The maximum settlement, maximum horizontal deformation, maximum uneven settlement, and maximum horizontal deformation difference of this embankment are −0.693, −0.241, 0.306, and −0.358 cm. This study provides a reference for the settlement control of embankments and the optimal design of crushed-rock embankments in warm permafrost regions.","PeriodicalId":517391,"journal":{"name":"Transportation Research Record: Journal of the Transportation Research Board","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1177/03611981241272091
Ankit Singh, Aman Srivastava, Rajalakshmi Pachamuthu, Digvijay S. Pawar
Driver distraction has proven to be among the top contributory factors in road crashes worldwide. The involvement of drivers in secondary activities, such as phone usage, conversation with co-passengers, reaching for objects, eating, and so forth, have been shown to be significant causes of in-vehicle driver distraction. Text messaging using mobile phones while driving can be detrimental to the primary driving task as it invokes manual, visual, and cognitive distractions. Numerous studies in the past have analyzed the effect of texting on driver distraction using driving simulators. This study followed a field operation test–based approach to simulate real road conditions and evaluate the impact of texting on driving behavior. The study was conducted at the connected autonomous vehicle testbed at the Indian Institute of Technology Hyderabad, using an instrumented test vehicle. Data on gaze parameters and vehicle kinematics were recorded using eye-tracker glasses and a high-end global positioning system (GPS) data logger. Thirty-one participants drove on the pre-defined path at the testbed under baseline and texting conditions. The findings demonstrated that the texting task significantly affected fixation count, mean speed, and lateral acceleration. The texting task led to a reduction in mean fixation counts, mean speed, and mean lateral acceleration by 44.37%, 34%, and 46.72%, respectively. The age and driving experience of the participants had a significant effect on their behavior. The results indicate the critical potential of texting-based driver distraction and suggest the enforcement of stringent rules for texting while driving to create a safer road environment.
{"title":"Impact of Texting-Induced Distraction on Driving Behavior Based on Field Operation Tests","authors":"Ankit Singh, Aman Srivastava, Rajalakshmi Pachamuthu, Digvijay S. Pawar","doi":"10.1177/03611981241272091","DOIUrl":"https://doi.org/10.1177/03611981241272091","url":null,"abstract":"Driver distraction has proven to be among the top contributory factors in road crashes worldwide. The involvement of drivers in secondary activities, such as phone usage, conversation with co-passengers, reaching for objects, eating, and so forth, have been shown to be significant causes of in-vehicle driver distraction. Text messaging using mobile phones while driving can be detrimental to the primary driving task as it invokes manual, visual, and cognitive distractions. Numerous studies in the past have analyzed the effect of texting on driver distraction using driving simulators. This study followed a field operation test–based approach to simulate real road conditions and evaluate the impact of texting on driving behavior. The study was conducted at the connected autonomous vehicle testbed at the Indian Institute of Technology Hyderabad, using an instrumented test vehicle. Data on gaze parameters and vehicle kinematics were recorded using eye-tracker glasses and a high-end global positioning system (GPS) data logger. Thirty-one participants drove on the pre-defined path at the testbed under baseline and texting conditions. The findings demonstrated that the texting task significantly affected fixation count, mean speed, and lateral acceleration. The texting task led to a reduction in mean fixation counts, mean speed, and mean lateral acceleration by 44.37%, 34%, and 46.72%, respectively. The age and driving experience of the participants had a significant effect on their behavior. The results indicate the critical potential of texting-based driver distraction and suggest the enforcement of stringent rules for texting while driving to create a safer road environment.","PeriodicalId":517391,"journal":{"name":"Transportation Research Record: Journal of the Transportation Research Board","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1177/03611981241275533
Reyhane Hosseinzade, Jamey M. B. Volker, Mira Evans
Automobile level of service (LOS) is the longest-standing and most commonly used performance metric in transportation impact analysis in the U.S. However, Senate Bill (SB) 743 upended that status quo for environmental impact review of land development projects in California, requiring that local governments analyze vehicle miles traveled (VMT) rather than LOS. In this study, we investigated how California’s local governments have responded to the mandated LOS-to-VMT switch. We obtained and analyzed information for 274 of the state’s 539 cities and counties, using expert interviews, documentary reviews, website searches, and communications with local government staff. We found that most jurisdictions had either adopted or were in the process of adopting their own VMT impact standards, though difficulties in implementing VMT-based standards were common and were more pronounced for smaller and more rural jurisdictions. In their standards, most jurisdictions hewed closely to the recommendations of the Governor’s Office of Planning and Research. Despite switching to VMT analysis for environmental review purposes, all respondent jurisdictions continued to use LOS outside the environmental review process. Overall, we found a consensus amongst our interviewees that swapping LOS for VMT could streamline development in urban areas but not in more suburban or rural jurisdictions. Our findings are specific to California, but they can provide useful guidance to other states or local governments outside of California that are considering adopting a VMT-based metric for transportation impact analyses.
{"title":"Swapping Level of Service for Vehicle Miles Traveled in Project-Level Environmental Impact Analysis: Trends and Challenges in California","authors":"Reyhane Hosseinzade, Jamey M. B. Volker, Mira Evans","doi":"10.1177/03611981241275533","DOIUrl":"https://doi.org/10.1177/03611981241275533","url":null,"abstract":"Automobile level of service (LOS) is the longest-standing and most commonly used performance metric in transportation impact analysis in the U.S. However, Senate Bill (SB) 743 upended that status quo for environmental impact review of land development projects in California, requiring that local governments analyze vehicle miles traveled (VMT) rather than LOS. In this study, we investigated how California’s local governments have responded to the mandated LOS-to-VMT switch. We obtained and analyzed information for 274 of the state’s 539 cities and counties, using expert interviews, documentary reviews, website searches, and communications with local government staff. We found that most jurisdictions had either adopted or were in the process of adopting their own VMT impact standards, though difficulties in implementing VMT-based standards were common and were more pronounced for smaller and more rural jurisdictions. In their standards, most jurisdictions hewed closely to the recommendations of the Governor’s Office of Planning and Research. Despite switching to VMT analysis for environmental review purposes, all respondent jurisdictions continued to use LOS outside the environmental review process. Overall, we found a consensus amongst our interviewees that swapping LOS for VMT could streamline development in urban areas but not in more suburban or rural jurisdictions. Our findings are specific to California, but they can provide useful guidance to other states or local governments outside of California that are considering adopting a VMT-based metric for transportation impact analyses.","PeriodicalId":517391,"journal":{"name":"Transportation Research Record: Journal of the Transportation Research Board","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1177/03611981241273100
Yizhou Zhao, Sajid Ali, Raima Nazar, Muhammad Khalid Anser
Over the past few years, there has been a growing convergence of energy and environmental challenges globally, necessitating decisive actions. In response to these imperatives, countries have embraced electric vehicles as a transformative solution. This study probes the connection between green finance and electric-vehicle adoption in the top 10 economies with the greatest stock of electric vehicles. Previous investigations employing panel-data tools established consistent findings about the green-finance/electric-vehicle nexus. However, some countries exhibit distinct relationships. Using the quantile-on-quantile methodology, we analyze the time-series interdependence within individual countries, providing insights into the variables’ asymmetric association. The findings show that green finance positively influences the electric-vehicle stock in certain economies, specifically at distinct points within the data distribution, each characterized by its unique traits. The findings emphasize the significance of green finance measures in promoting widespread electric-vehicle adoption, contributing to environmental sustainability, and fostering a shift toward low carbon consumption.
{"title":"Sustainable Wheels of Fortune: Understanding the Asymmetric Bond between Green Finance and Electric Vehicle Adoption","authors":"Yizhou Zhao, Sajid Ali, Raima Nazar, Muhammad Khalid Anser","doi":"10.1177/03611981241273100","DOIUrl":"https://doi.org/10.1177/03611981241273100","url":null,"abstract":"Over the past few years, there has been a growing convergence of energy and environmental challenges globally, necessitating decisive actions. In response to these imperatives, countries have embraced electric vehicles as a transformative solution. This study probes the connection between green finance and electric-vehicle adoption in the top 10 economies with the greatest stock of electric vehicles. Previous investigations employing panel-data tools established consistent findings about the green-finance/electric-vehicle nexus. However, some countries exhibit distinct relationships. Using the quantile-on-quantile methodology, we analyze the time-series interdependence within individual countries, providing insights into the variables’ asymmetric association. The findings show that green finance positively influences the electric-vehicle stock in certain economies, specifically at distinct points within the data distribution, each characterized by its unique traits. The findings emphasize the significance of green finance measures in promoting widespread electric-vehicle adoption, contributing to environmental sustainability, and fostering a shift toward low carbon consumption.","PeriodicalId":517391,"journal":{"name":"Transportation Research Record: Journal of the Transportation Research Board","volume":"73 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1177/03611981241258753
Xinlong Dong, Peicheng Shi, Taonian Liang, Aixi Yang
As the core technology of an environmental perception system, object detection has received more and more attention and has become a hot research direction for intelligent driving vehicles. The CNN–Transformer hybrid model has poor generalization ability, making it difficult to meet the detection requirements for small objects in complex scenes. We propose a novel convolutional neural network (CNN)–Transformer Adaptive Feature Fusion Network (CTAFFNet) for object detection. First, we design a Local–Global Feature Fusion unit known as the Convolutional Transformation Adaptive Fusion Kernel (CTAFFK), which is integrated into CTAFFNet. The CTAFFK kernel utilizes two branches, namely CNN and Transformer, to extract local and global features from the image, and adaptively fuses the features from both branches. Subsequently, we develop an adaptive feature fusion strategy that combines local high-frequency and global low-frequency features to obtain comprehensive feature information. Finally, CTAFFNet employs an encoder–decoder structure to facilitate the flow of fused local–global information between different stages, ensuring the model’s generalization capabilities. Results from the experiment conducted on the large and challenging KITTI dataset demonstrate the effectiveness and efficiency of the proposed network. Compared with other mainstream networks, it achieves an average precision of 91.17%, particularly excelling in the detection of small objects at longer distances with a remarkable 70.18% accuracy, while also providing real-time detection capabilities.
{"title":"CTAFFNet: CNN–Transformer Adaptive Feature Fusion Object Detection Algorithm for Complex Traffic Scenarios","authors":"Xinlong Dong, Peicheng Shi, Taonian Liang, Aixi Yang","doi":"10.1177/03611981241258753","DOIUrl":"https://doi.org/10.1177/03611981241258753","url":null,"abstract":"As the core technology of an environmental perception system, object detection has received more and more attention and has become a hot research direction for intelligent driving vehicles. The CNN–Transformer hybrid model has poor generalization ability, making it difficult to meet the detection requirements for small objects in complex scenes. We propose a novel convolutional neural network (CNN)–Transformer Adaptive Feature Fusion Network (CTAFFNet) for object detection. First, we design a Local–Global Feature Fusion unit known as the Convolutional Transformation Adaptive Fusion Kernel (CTAFFK), which is integrated into CTAFFNet. The CTAFFK kernel utilizes two branches, namely CNN and Transformer, to extract local and global features from the image, and adaptively fuses the features from both branches. Subsequently, we develop an adaptive feature fusion strategy that combines local high-frequency and global low-frequency features to obtain comprehensive feature information. Finally, CTAFFNet employs an encoder–decoder structure to facilitate the flow of fused local–global information between different stages, ensuring the model’s generalization capabilities. Results from the experiment conducted on the large and challenging KITTI dataset demonstrate the effectiveness and efficiency of the proposed network. Compared with other mainstream networks, it achieves an average precision of 91.17%, particularly excelling in the detection of small objects at longer distances with a remarkable 70.18% accuracy, while also providing real-time detection capabilities.","PeriodicalId":517391,"journal":{"name":"Transportation Research Record: Journal of the Transportation Research Board","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1177/03611981241270154
Mingyu Hou, Chenzhu Wang, Said M. Easa, Jianchuan Cheng
Vision is one of the most important human senses, accounting for most of the external information pedestrians receive while crossing the street. However, distracted mobile phone usage during street crossing consumes pedestrians’ cognitive resources and diverts their visual attention. As a result, pedestrians may be unable to fully concentrate on observing the traffic environment and effectively planning their crossing path and behavior. This study evaluated the effect of pedestrian behavioral activities at street crossings on eye-movement (EM) characteristics. The crossing tasks were natural behavior, voice call, text messaging, and listening to music. The tasks were further categorized as simple or complex. A total of 29 participants were recruited in Nanjing: 18 males (62.1%) and 11 females (37.9%) with an average age of 23.59 years (SD = 2.44). The Friedman test was used to analyze differences in saccade frequency, fixation time, browsing number, and browsing time across different scenarios. Text messaging had the most significant impact on pedestrians’ EM characteristics, followed by voice call; music listening had a relatively weaker effect. Secondary task difficulty influenced the percentage of browsing, viewing, and to some extent gaze time. On the other hand, music rhythm and style only partially influenced the percentage of gaze and gaze time. Mobile phones substantially affected pedestrians’ EM characteristics and attention allocation for the same level of secondary task difficulty. These findings contribute to a better understanding of pedestrians’ visual characteristics under distracted mobile phone usage conditions and provide valuable insights for developing appropriate measures to enhance pedestrian safety.
{"title":"Eye Movement Evaluation of Pedestrians' Mobile Phone Usage at Street Crossings","authors":"Mingyu Hou, Chenzhu Wang, Said M. Easa, Jianchuan Cheng","doi":"10.1177/03611981241270154","DOIUrl":"https://doi.org/10.1177/03611981241270154","url":null,"abstract":"Vision is one of the most important human senses, accounting for most of the external information pedestrians receive while crossing the street. However, distracted mobile phone usage during street crossing consumes pedestrians’ cognitive resources and diverts their visual attention. As a result, pedestrians may be unable to fully concentrate on observing the traffic environment and effectively planning their crossing path and behavior. This study evaluated the effect of pedestrian behavioral activities at street crossings on eye-movement (EM) characteristics. The crossing tasks were natural behavior, voice call, text messaging, and listening to music. The tasks were further categorized as simple or complex. A total of 29 participants were recruited in Nanjing: 18 males (62.1%) and 11 females (37.9%) with an average age of 23.59 years (SD = 2.44). The Friedman test was used to analyze differences in saccade frequency, fixation time, browsing number, and browsing time across different scenarios. Text messaging had the most significant impact on pedestrians’ EM characteristics, followed by voice call; music listening had a relatively weaker effect. Secondary task difficulty influenced the percentage of browsing, viewing, and to some extent gaze time. On the other hand, music rhythm and style only partially influenced the percentage of gaze and gaze time. Mobile phones substantially affected pedestrians’ EM characteristics and attention allocation for the same level of secondary task difficulty. These findings contribute to a better understanding of pedestrians’ visual characteristics under distracted mobile phone usage conditions and provide valuable insights for developing appropriate measures to enhance pedestrian safety.","PeriodicalId":517391,"journal":{"name":"Transportation Research Record: Journal of the Transportation Research Board","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：