Pub Date : 2021-09-15DOI: 10.1080/19439962.2021.1971812
Amirarsalan Mehrara Molan, J. Hummer, Logan J. Aspeitia, Alex S. Deatherage
Abstract Many existing interchanges, which were built mostly in 1950s and 1960s based on old design guidelines, have operational and/or safety problems due to the inconsistency with current traffic and pedestrian demands. Therefore, upgrading existing designs based on recent policies and demands could result in improving the performance of old interchanges. This research evaluates traffic safety and pedestrian performance of the new offset diamond interchange (ODI) as a substitute for failing conventional interchanges. The ODI design, which showed potential in improving traffic operation in a past study by the authors, was compared to nine interchange designs using VISSIM and the Surrogate Safety Assessment Model (SSAM) in this study to examine the safety and pedestrian performance. Overall, 324 simulation scenarios were tested with various conditions of traffic and pedestrian volumes, turning traffic ratios, traffic distribution, and truck percentages. According to the results, the ODI showed potential to be a promising design in terms of safety and pedestrian performance. However, the diverging diamond interchange (DDI) resulted in fewer simulated conflicts compared to the new ODI. On the other hand, the ODI design had a better performance in terms of pedestrian performance.
{"title":"Evaluating safety performance of the offset diamond interchange design using VISSIM and surrogate safety assessment model","authors":"Amirarsalan Mehrara Molan, J. Hummer, Logan J. Aspeitia, Alex S. Deatherage","doi":"10.1080/19439962.2021.1971812","DOIUrl":"https://doi.org/10.1080/19439962.2021.1971812","url":null,"abstract":"Abstract Many existing interchanges, which were built mostly in 1950s and 1960s based on old design guidelines, have operational and/or safety problems due to the inconsistency with current traffic and pedestrian demands. Therefore, upgrading existing designs based on recent policies and demands could result in improving the performance of old interchanges. This research evaluates traffic safety and pedestrian performance of the new offset diamond interchange (ODI) as a substitute for failing conventional interchanges. The ODI design, which showed potential in improving traffic operation in a past study by the authors, was compared to nine interchange designs using VISSIM and the Surrogate Safety Assessment Model (SSAM) in this study to examine the safety and pedestrian performance. Overall, 324 simulation scenarios were tested with various conditions of traffic and pedestrian volumes, turning traffic ratios, traffic distribution, and truck percentages. According to the results, the ODI showed potential to be a promising design in terms of safety and pedestrian performance. However, the diverging diamond interchange (DDI) resulted in fewer simulated conflicts compared to the new ODI. On the other hand, the ODI design had a better performance in terms of pedestrian performance.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"240 1","pages":"1815 - 1837"},"PeriodicalIF":2.6,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78159402","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 : 2021-09-15DOI: 10.1080/19439962.2021.1978022
Burak Yiğit Katanalp, Ezgi Eren
Abstract In this study, both micro and macro level evaluation of pedestrian-vehicle crashes were conducted. Macro-level findings were obtained with GIS-based density analyzes, and critical road segments were determined. The data on road characteristics, traffic characteristics, built environment and land use were collected in 70 critical urban road segments. While conducting micro-level research, commonly used multilayer perceptron and C4.5 decision tree, as well as innovative converted fuzzy-decision model and revised fuzzy-decision model, which significantly reduces the expert judgements on fuzzy models, were used. Significant rules were extracted, and were evaluated from safety perspective. Information gain ratio was used to deal with the black-box structure of machine learning models and to examine independent factors in-depth. The best performance was achieved in revised fuzzy decision model with 68.57% accuracy. The results revealed that land use, parking and peak hour volume have high effect, as well as public transport, speed and road type factors have the greatest effect on pedestrian safety. In the light of the results, various managerial implications such as controlling the density of public transport on main arterials, preventing stop-and-go effects, and monitoring vehicle speeds especially during peak hours were suggested to improve pedestrian safety.
{"title":"GIS-based assessment of pedestrian-vehicle accidents in terms of safety with four different ML models","authors":"Burak Yiğit Katanalp, Ezgi Eren","doi":"10.1080/19439962.2021.1978022","DOIUrl":"https://doi.org/10.1080/19439962.2021.1978022","url":null,"abstract":"Abstract In this study, both micro and macro level evaluation of pedestrian-vehicle crashes were conducted. Macro-level findings were obtained with GIS-based density analyzes, and critical road segments were determined. The data on road characteristics, traffic characteristics, built environment and land use were collected in 70 critical urban road segments. While conducting micro-level research, commonly used multilayer perceptron and C4.5 decision tree, as well as innovative converted fuzzy-decision model and revised fuzzy-decision model, which significantly reduces the expert judgements on fuzzy models, were used. Significant rules were extracted, and were evaluated from safety perspective. Information gain ratio was used to deal with the black-box structure of machine learning models and to examine independent factors in-depth. The best performance was achieved in revised fuzzy decision model with 68.57% accuracy. The results revealed that land use, parking and peak hour volume have high effect, as well as public transport, speed and road type factors have the greatest effect on pedestrian safety. In the light of the results, various managerial implications such as controlling the density of public transport on main arterials, preventing stop-and-go effects, and monitoring vehicle speeds especially during peak hours were suggested to improve pedestrian safety.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"59 1","pages":"1598 - 1632"},"PeriodicalIF":2.6,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90055003","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 : 2021-08-30DOI: 10.1080/19439962.2021.1960660
S. Nafis, Priyanka Alluri, Wensong Wu, B. G. Kibria
Abstract Wrong-way driving (WWD) crashes result in more fatalities per crash, involve more vehicles, and cause extended road closures compared to other types of crashes. Previous studies have used descriptive and parametric statistical models to identify factors that affect WWD crash severity on limited access facilities. This study adopted a combination of non-parametric data mining techniques aiming to recognize the pattern of contributing factors that affect the WWD crash severity on non-limited access facilities. These non-parametric methods can handle heterogeneity in crash datasets well. In this study, hierarchical clustering was used to divide the crash dataset into homogeneous clusters. A random forests analysis was used to select important variables, and decision trees and decision rules were generated to show the underlying pattern and interactions between different factors that affect WWD crash severity. The analysis was based on 1,475 WWD crashes that occurred on arterial streets from 2012-2016 in Florida. Results show that head-on collisions, weekend days, high-speed facilities, crashes involving vehicles entering from a driveway, dark-not lighted roadways, older drivers, and driver impairment are important factors that play a crucial role in WWD crash severity on non-limited access facilities.
{"title":"Wrong-way driving crash injury analysis on arterial road networks using non-parametric data mining techniques","authors":"S. Nafis, Priyanka Alluri, Wensong Wu, B. G. Kibria","doi":"10.1080/19439962.2021.1960660","DOIUrl":"https://doi.org/10.1080/19439962.2021.1960660","url":null,"abstract":"Abstract Wrong-way driving (WWD) crashes result in more fatalities per crash, involve more vehicles, and cause extended road closures compared to other types of crashes. Previous studies have used descriptive and parametric statistical models to identify factors that affect WWD crash severity on limited access facilities. This study adopted a combination of non-parametric data mining techniques aiming to recognize the pattern of contributing factors that affect the WWD crash severity on non-limited access facilities. These non-parametric methods can handle heterogeneity in crash datasets well. In this study, hierarchical clustering was used to divide the crash dataset into homogeneous clusters. A random forests analysis was used to select important variables, and decision trees and decision rules were generated to show the underlying pattern and interactions between different factors that affect WWD crash severity. The analysis was based on 1,475 WWD crashes that occurred on arterial streets from 2012-2016 in Florida. Results show that head-on collisions, weekend days, high-speed facilities, crashes involving vehicles entering from a driveway, dark-not lighted roadways, older drivers, and driver impairment are important factors that play a crucial role in WWD crash severity on non-limited access facilities.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"11 1","pages":"1702 - 1730"},"PeriodicalIF":2.6,"publicationDate":"2021-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75144269","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 : 2021-08-28DOI: 10.1080/19439962.2021.1971813
S. Gehrke, Brendan J. Russo, Bita Sadeghinasr, Katherine R. Riffle, E. Smaglik, T. Reardon
Abstract In recent years, a rush of privately-owned shared micromobility services has descended on many American cities. The increased availability in these emergent mobility options, which include dockless bikeshare and electric scooter systems, offers urban residents, workers, and visitors a convenient travel alternative to more established modes. However, with limited regulation and dedicated infrastructure, the rapid introduction of new micromobility services has come with rising safety concerns. This study provides new evidence on the spatial associations between e-scooter trip generation and vulnerable road user crash counts by investigating eight months of shared mobility data collected during a 2019 pilot program in Brookline, Massachusetts. The findings from traditional and spatial negative binomial models with a set of network and environmental predictors are presented and demonstrate a connection between shared e-scooter and long-term vulnerable user crash activity. Our results illustrate the need for policies that promote shared mobility services through safer infrastructure provisions.
{"title":"Spatial interactions of shared e-scooter trip generation and vulnerable road user crash frequency","authors":"S. Gehrke, Brendan J. Russo, Bita Sadeghinasr, Katherine R. Riffle, E. Smaglik, T. Reardon","doi":"10.1080/19439962.2021.1971813","DOIUrl":"https://doi.org/10.1080/19439962.2021.1971813","url":null,"abstract":"Abstract In recent years, a rush of privately-owned shared micromobility services has descended on many American cities. The increased availability in these emergent mobility options, which include dockless bikeshare and electric scooter systems, offers urban residents, workers, and visitors a convenient travel alternative to more established modes. However, with limited regulation and dedicated infrastructure, the rapid introduction of new micromobility services has come with rising safety concerns. This study provides new evidence on the spatial associations between e-scooter trip generation and vulnerable road user crash counts by investigating eight months of shared mobility data collected during a 2019 pilot program in Brookline, Massachusetts. The findings from traditional and spatial negative binomial models with a set of network and environmental predictors are presented and demonstrate a connection between shared e-scooter and long-term vulnerable user crash activity. Our results illustrate the need for policies that promote shared mobility services through safer infrastructure provisions.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"20 1","pages":"1798 - 1814"},"PeriodicalIF":2.6,"publicationDate":"2021-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81509472","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 : 2021-08-13DOI: 10.1080/19439962.2021.1960662
Lin Hu, Jian Ou, Jing Huang, Fang Wang, Yanxia Wang, Bo Ren, Huachao Peng, Lei Zhou
Abstract The purpose of this study is to investigate the unsafe conditions of pedestrian crossings at signalized intersections under the mixed traffic environment in Changsha, China. For this purpose, based really pedestrian-related crash data of Changsha city and visualized crash geographic information, six typical urban signalized intersections were selected. The peak and off-peak surveillance videos of six signalized intersections were collected via field surveys, 1,070 conflicts were extracted through using professional trajectory tracking software Traker to track pedestrian and vehicle trajectories. PSMT (Pedestrian Safety Margin Time) was used as an indicator to identify the severity of conflicts, and manually recorded the characteristics of pedestrian crossing behavior, vehicles and roads during the conflict. An Ordered Probit model was established to analyze the risk factors that led to different severities of the conflict between pedestrians and vehicles. The model outcome indicates a significant relationship between the severity level and characteristics of pedestrian behavior, vehicles and conflict. Moreover, it was identified that, in addition to the above characteristics, roadway characteristics significantly influenced likelihood of severe pedestrian-vehicle conflict. Finally, these factors are discussed, and suggestions for improving the pedestrian traffic environment are proposed from different perspectives.
{"title":"Safety evaluation of pedestrian-vehicle interaction at signalized intersections in Changsha, China","authors":"Lin Hu, Jian Ou, Jing Huang, Fang Wang, Yanxia Wang, Bo Ren, Huachao Peng, Lei Zhou","doi":"10.1080/19439962.2021.1960662","DOIUrl":"https://doi.org/10.1080/19439962.2021.1960662","url":null,"abstract":"Abstract The purpose of this study is to investigate the unsafe conditions of pedestrian crossings at signalized intersections under the mixed traffic environment in Changsha, China. For this purpose, based really pedestrian-related crash data of Changsha city and visualized crash geographic information, six typical urban signalized intersections were selected. The peak and off-peak surveillance videos of six signalized intersections were collected via field surveys, 1,070 conflicts were extracted through using professional trajectory tracking software Traker to track pedestrian and vehicle trajectories. PSMT (Pedestrian Safety Margin Time) was used as an indicator to identify the severity of conflicts, and manually recorded the characteristics of pedestrian crossing behavior, vehicles and roads during the conflict. An Ordered Probit model was established to analyze the risk factors that led to different severities of the conflict between pedestrians and vehicles. The model outcome indicates a significant relationship between the severity level and characteristics of pedestrian behavior, vehicles and conflict. Moreover, it was identified that, in addition to the above characteristics, roadway characteristics significantly influenced likelihood of severe pedestrian-vehicle conflict. Finally, these factors are discussed, and suggestions for improving the pedestrian traffic environment are proposed from different perspectives.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"37 1","pages":"1750 - 1775"},"PeriodicalIF":2.6,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76770268","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 : 2021-08-09DOI: 10.1080/19439962.2021.1960663
Mohamed El Esawey, Joy Sengupta, John E. Babineau, Emmanuel A. Takyi
Abstract This study reports the safety benefits associated with the installation of Variable Speed Limit System (VSLS) on provincial highways in British Columbia (BC), Canada. A VSLS is an intelligent transportation system (ITS) that aims at increasing the safety level on highways by varying the speed limit according to downstream operational condition and/or weather conditions. The analysis made use of police-attended serious crashes (i.e. fatal + injury) that took place during winter seasons. Three winter seasons were available as a before-implementation period, and three winter seasons were available as an after-implementation period. The results of a simple-before-and-after showed overall reductions of 35.8% and 36.8% in winter serious collision (WSC) frequency and rate, respectively, were found for the evaluation corridors. An Empirical Bayes (EB) before-and-after safety evaluation was also carried out to ensure that the results are reliable. The EB analysis showed an overall reduction of 34.4% in WSC. An economic assessment of the system was undertaken and the results showed that the benefits of implementing a VSLS exceeded the system cost with an overall benefit-cost (B/C) ratio of 4.3 and a Net Present Value (NPV) of C$34.41 million. The results of this study may motivate stakeholders who are interested in pursuing similar systems for mitigating weather-related safety challenges.
{"title":"Safety evaluation of variable speed limit system in British Columbia","authors":"Mohamed El Esawey, Joy Sengupta, John E. Babineau, Emmanuel A. Takyi","doi":"10.1080/19439962.2021.1960663","DOIUrl":"https://doi.org/10.1080/19439962.2021.1960663","url":null,"abstract":"Abstract This study reports the safety benefits associated with the installation of Variable Speed Limit System (VSLS) on provincial highways in British Columbia (BC), Canada. A VSLS is an intelligent transportation system (ITS) that aims at increasing the safety level on highways by varying the speed limit according to downstream operational condition and/or weather conditions. The analysis made use of police-attended serious crashes (i.e. fatal + injury) that took place during winter seasons. Three winter seasons were available as a before-implementation period, and three winter seasons were available as an after-implementation period. The results of a simple-before-and-after showed overall reductions of 35.8% and 36.8% in winter serious collision (WSC) frequency and rate, respectively, were found for the evaluation corridors. An Empirical Bayes (EB) before-and-after safety evaluation was also carried out to ensure that the results are reliable. The EB analysis showed an overall reduction of 34.4% in WSC. An economic assessment of the system was undertaken and the results showed that the benefits of implementing a VSLS exceeded the system cost with an overall benefit-cost (B/C) ratio of 4.3 and a Net Present Value (NPV) of C$34.41 million. The results of this study may motivate stakeholders who are interested in pursuing similar systems for mitigating weather-related safety challenges.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"21 1","pages":"1776 - 1797"},"PeriodicalIF":2.6,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88554111","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 : 2021-08-06DOI: 10.1080/19439962.2021.1960661
T. K. O. Madsen, Charlotte Tønning, A. V. Olesen, Tove Hels, H. Lahrmann
Abstract Advanced stop boxes (ASBs) (i.e., marked areas for cyclists in front of the stop line) are mentioned as a potential means to reducing the risk of crashes between cyclists and right-turning vehicles. This study estimates the safety effect of ASBs at signalised intersections using the log-odds method. Seven signalised intersections were filmed for 3,627 hours before and after constructing ASBs. Traffic conflicts were used as a surrogate for crashes. In total, the study found 644 traffic conflicts. The overall safety effect was not statistically significant: the conflict rate for right-hook conflicts decreased by 6% (p = 0.72), and for left-hook conflicts it increased by 21% (p = 0.26). The results differed at the seven sites, and there were only a few statistically significant results. At one site, the conflict rate of cyclists vs. right-turning vehicles decreased significantly, while it significantly increased at another site. One of the seven sites showed a significant increase in the conflict rate of cyclists vs. left-turning vehicles. A likely explanation is that few conflicts occur during the early green phase. In addition, the use rate of the ASB was low (0–2.7%).
{"title":"Advanced stop boxes and their effect on traffic conflict rates between cyclists and turning vehicles","authors":"T. K. O. Madsen, Charlotte Tønning, A. V. Olesen, Tove Hels, H. Lahrmann","doi":"10.1080/19439962.2021.1960661","DOIUrl":"https://doi.org/10.1080/19439962.2021.1960661","url":null,"abstract":"Abstract Advanced stop boxes (ASBs) (i.e., marked areas for cyclists in front of the stop line) are mentioned as a potential means to reducing the risk of crashes between cyclists and right-turning vehicles. This study estimates the safety effect of ASBs at signalised intersections using the log-odds method. Seven signalised intersections were filmed for 3,627 hours before and after constructing ASBs. Traffic conflicts were used as a surrogate for crashes. In total, the study found 644 traffic conflicts. The overall safety effect was not statistically significant: the conflict rate for right-hook conflicts decreased by 6% (p = 0.72), and for left-hook conflicts it increased by 21% (p = 0.26). The results differed at the seven sites, and there were only a few statistically significant results. At one site, the conflict rate of cyclists vs. right-turning vehicles decreased significantly, while it significantly increased at another site. One of the seven sites showed a significant increase in the conflict rate of cyclists vs. left-turning vehicles. A likely explanation is that few conflicts occur during the early green phase. In addition, the use rate of the ASB was low (0–2.7%).","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"90 1","pages":"1731 - 1749"},"PeriodicalIF":2.6,"publicationDate":"2021-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79035995","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 : 2021-08-04DOI: 10.1080/19439962.2021.1958036
D. Saha, Eric Dumbaugh
Abstract This paper presents a study that evaluates the nature of the associations (i.e., linear or non-linear) between built environment variables and pedestrian crash frequency at the census block group level. A machine learning approach, called the componentwise model-based gradient boosting algorithm, was implemented to estimate the nature and effects of sociodemographic, land use, road network, and traffic attributes on pedestrian crashes from Broward and Miami-Dade Counties in Florida. The algorithm provides the flexibility to use different types of base-learners, including but not limited to decision tree (DT), generalized additive model (GAM), and Markov Random Field (MRF). While gradient boosting with DT base-learner has widely been used in safety studies, other base-learners and their performances in crash frequency predictions are yet to be explored. This study compared the performance of DT and GAM base-learners, with an MRF base-learner to account for spatial correlation among analysis units. Models fitted with GAM base-learner were found to perform better than the models fitted with DT base-learner, with several variables showing non-linear and several showing linear or approximately linear correlations with pedestrian crash frequency. The study provides useful insights on how the results can help urban planners and policy makers to optimize pedestrian safety measures.
{"title":"Use of a model-based gradient boosting framework to assess spatial and non-linear effects of variables on pedestrian crash frequency at macro-level","authors":"D. Saha, Eric Dumbaugh","doi":"10.1080/19439962.2021.1958036","DOIUrl":"https://doi.org/10.1080/19439962.2021.1958036","url":null,"abstract":"Abstract This paper presents a study that evaluates the nature of the associations (i.e., linear or non-linear) between built environment variables and pedestrian crash frequency at the census block group level. A machine learning approach, called the componentwise model-based gradient boosting algorithm, was implemented to estimate the nature and effects of sociodemographic, land use, road network, and traffic attributes on pedestrian crashes from Broward and Miami-Dade Counties in Florida. The algorithm provides the flexibility to use different types of base-learners, including but not limited to decision tree (DT), generalized additive model (GAM), and Markov Random Field (MRF). While gradient boosting with DT base-learner has widely been used in safety studies, other base-learners and their performances in crash frequency predictions are yet to be explored. This study compared the performance of DT and GAM base-learners, with an MRF base-learner to account for spatial correlation among analysis units. Models fitted with GAM base-learner were found to perform better than the models fitted with DT base-learner, with several variables showing non-linear and several showing linear or approximately linear correlations with pedestrian crash frequency. The study provides useful insights on how the results can help urban planners and policy makers to optimize pedestrian safety measures.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"59 1","pages":"1419 - 1450"},"PeriodicalIF":2.6,"publicationDate":"2021-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84003758","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 : 2021-07-28DOI: 10.1080/19439962.2021.1958037
Shaojie Liu, Zijing Lin, W. Fan
Abstract Vulnerable road users (VRUs) including pedestrians and cyclists tend to experience more severe injuries when they are involved in crashes compared with motorized vehicle users. Such concern has been expressed as an impediment to the promotion of environment-friendly transportation. To provide insights on the causes of crashes involving VRUs, this study aims to explore the underlying factors that contribute to VRUs injury severity levels and provide constructive recommendations to mitigate injury severity in crashes. In order to minimize heterogeneity existing in the collected data, a latent class clustering method is conducted to categorize collected crash records into different groups. Then the mixed logit models are developed for each cluster as well as the overall crash data. The analysis is conducted based on the crash data retrieved from the Highway Safety Information System (HSIS) from 2012 to 2016 in North Carolina. Distinguished sets of significant factors are identified for clusters with different dominant features. Some factors are found to yield different or even opposite effects in identified clusters, including male gender and non-roadway location. These findings would enhance the understanding of the vulnerable road user (VRU) injury severity mechanism and help policymakers to make reasoned and efficient decisions to improve safety.
{"title":"Investigating contributing factors to injury severity levels in crashes involving pedestrians and cyclists using latent class clustering analysis and mixed logit models","authors":"Shaojie Liu, Zijing Lin, W. Fan","doi":"10.1080/19439962.2021.1958037","DOIUrl":"https://doi.org/10.1080/19439962.2021.1958037","url":null,"abstract":"Abstract Vulnerable road users (VRUs) including pedestrians and cyclists tend to experience more severe injuries when they are involved in crashes compared with motorized vehicle users. Such concern has been expressed as an impediment to the promotion of environment-friendly transportation. To provide insights on the causes of crashes involving VRUs, this study aims to explore the underlying factors that contribute to VRUs injury severity levels and provide constructive recommendations to mitigate injury severity in crashes. In order to minimize heterogeneity existing in the collected data, a latent class clustering method is conducted to categorize collected crash records into different groups. Then the mixed logit models are developed for each cluster as well as the overall crash data. The analysis is conducted based on the crash data retrieved from the Highway Safety Information System (HSIS) from 2012 to 2016 in North Carolina. Distinguished sets of significant factors are identified for clusters with different dominant features. Some factors are found to yield different or even opposite effects in identified clusters, including male gender and non-roadway location. These findings would enhance the understanding of the vulnerable road user (VRU) injury severity mechanism and help policymakers to make reasoned and efficient decisions to improve safety.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"2432 1","pages":"1674 - 1701"},"PeriodicalIF":2.6,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86576426","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 : 2021-07-22DOI: 10.1080/19439962.2021.1951912
Pengzi Chu, Yi Yu, Jingshuai Yang, Chuanchuan Huang
Abstract Young drivers are more likely to be involved in traffic accidents. The study aims to explore mechanisms behind distracted driving behaviour, traffic safety environment, driving responsibility, and hazard perception. A conceptual model is proposed based on Stimulus-Organism-Response (S-O-R) theory. The self-reported data from 367 drivers are used to estimate and modify the model based on exploratory factor analysis, structural equation modelling, and bias-corrected bootstrap method. The regression relationships and the mediators have been identified. The traffic safety environment including the traffic enforcement and the driving condition isn’t related to the distracted driving behaviour. The traffic enforcement is associated the driving responsibility, the relationships between the driving responsibility, the hazard perception and the driving condition are significant, and the relationships between the distracted driving behaviour, the driving responsibility and the hazard perception are noteworthy. A positive traffic safety environment is beneficial to the safety of young drivers. The sense of driving responsibility and the self-cognition of hazard perception need attention for the early intervention of young drivers’ distracted driving behaviours.
{"title":"Understanding the mechanism behind young drivers’ distracted driving behaviour based on S-O-R theory","authors":"Pengzi Chu, Yi Yu, Jingshuai Yang, Chuanchuan Huang","doi":"10.1080/19439962.2021.1951912","DOIUrl":"https://doi.org/10.1080/19439962.2021.1951912","url":null,"abstract":"Abstract Young drivers are more likely to be involved in traffic accidents. The study aims to explore mechanisms behind distracted driving behaviour, traffic safety environment, driving responsibility, and hazard perception. A conceptual model is proposed based on Stimulus-Organism-Response (S-O-R) theory. The self-reported data from 367 drivers are used to estimate and modify the model based on exploratory factor analysis, structural equation modelling, and bias-corrected bootstrap method. The regression relationships and the mediators have been identified. The traffic safety environment including the traffic enforcement and the driving condition isn’t related to the distracted driving behaviour. The traffic enforcement is associated the driving responsibility, the relationships between the driving responsibility, the hazard perception and the driving condition are significant, and the relationships between the distracted driving behaviour, the driving responsibility and the hazard perception are noteworthy. A positive traffic safety environment is beneficial to the safety of young drivers. The sense of driving responsibility and the self-cognition of hazard perception need attention for the early intervention of young drivers’ distracted driving behaviours.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"62 1","pages":"1655 - 1673"},"PeriodicalIF":2.6,"publicationDate":"2021-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74957834","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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