Pub Date : 2022-04-15DOI: 10.1080/19439962.2022.2061095
Mutasem Alzoubaidi, M. Zlatkovic
Abstract This study proposes and investigates the safety performance of a new innovative interchange design, called the continuous green T-partial cloverleaf A (CGT-parclo A). The CGT-parclo A was compared with various other conventional and unconventional service interchange designs. To address the objectives of this research, a simulation modeling network was built using VISSIM microsimulation software coupled with Econolite’s external ASC/3 Software-in-the-Loop signal controller. The Federal Highway Administration’s Surrogate Safety Assessment Model was employed to produce results of surrogate safety measures. Moreover, analyses of variance were conducted to examine the statistical significance of the results. The findings indicate that the CGT-parclo A is the best form of parclo A interchanges, with the potential to reduce the likelihood of crashes as well as their frequencies and severities. Specifically, the CGT-parclo A reduced the crossing conflicts, rear-end conflicts, lane change conflicts, and the total number of conflicts by ranges of 6.4% to 43.7%, 4.8% to 19.7%, 1.2% to 30.0%, and 7.6% to 28.1%, respectively.
{"title":"Investigating the safety performance of the new continuous green T-partial cloverleaf A interchange","authors":"Mutasem Alzoubaidi, M. Zlatkovic","doi":"10.1080/19439962.2022.2061095","DOIUrl":"https://doi.org/10.1080/19439962.2022.2061095","url":null,"abstract":"Abstract This study proposes and investigates the safety performance of a new innovative interchange design, called the continuous green T-partial cloverleaf A (CGT-parclo A). The CGT-parclo A was compared with various other conventional and unconventional service interchange designs. To address the objectives of this research, a simulation modeling network was built using VISSIM microsimulation software coupled with Econolite’s external ASC/3 Software-in-the-Loop signal controller. The Federal Highway Administration’s Surrogate Safety Assessment Model was employed to produce results of surrogate safety measures. Moreover, analyses of variance were conducted to examine the statistical significance of the results. The findings indicate that the CGT-parclo A is the best form of parclo A interchanges, with the potential to reduce the likelihood of crashes as well as their frequencies and severities. Specifically, the CGT-parclo A reduced the crossing conflicts, rear-end conflicts, lane change conflicts, and the total number of conflicts by ranges of 6.4% to 43.7%, 4.8% to 19.7%, 1.2% to 30.0%, and 7.6% to 28.1%, respectively.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"11 1","pages":"350 - 375"},"PeriodicalIF":2.6,"publicationDate":"2022-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75160544","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 : 2022-04-11DOI: 10.1080/19439962.2022.2063464
E. Adanu, A. Lidbe, Jun Liu, Steven L. Jones
Abstract This study was carried out to examine the factors associated with motorcycle crash severity in Alabama, under different manner of crash and causal scenarios using mixed logit modeling. Three crash mechanisms were considered in this study: single-vehicle motorcycle crash with motorcyclist at fault, multi-vehicle collision between a motorcycle and another vehicle with motorcyclist being at fault, and motorcyclist not at fault in a collision between a motorcycle and another vehicle. The model estimation results showed that crashes that happened in rural areas were more likely to be severe, irrespective of the causal unit or manner of collision. The results also show that fatigue among motorcyclists was associated with severe injury, whereas driver fatigue was linked to no injury outcome. Further, it was found that risky behaviors such as speeding, driving/riding under the influence of alcohol or drugs, driving/riding with invalid license were significantly associated with severe injury outcome. Developing the injury-severity models based on the segmented crash data has helped to reveal some similarities and differences in crash outcomes based on the crash mechanism and the at-fault road user. It is expected that these findings would provide a data-driven evidence to improve motorcycle safety in the state.
{"title":"A comparative study of factors associated with motorcycle crash severities under different causal scenarios","authors":"E. Adanu, A. Lidbe, Jun Liu, Steven L. Jones","doi":"10.1080/19439962.2022.2063464","DOIUrl":"https://doi.org/10.1080/19439962.2022.2063464","url":null,"abstract":"Abstract This study was carried out to examine the factors associated with motorcycle crash severity in Alabama, under different manner of crash and causal scenarios using mixed logit modeling. Three crash mechanisms were considered in this study: single-vehicle motorcycle crash with motorcyclist at fault, multi-vehicle collision between a motorcycle and another vehicle with motorcyclist being at fault, and motorcyclist not at fault in a collision between a motorcycle and another vehicle. The model estimation results showed that crashes that happened in rural areas were more likely to be severe, irrespective of the causal unit or manner of collision. The results also show that fatigue among motorcyclists was associated with severe injury, whereas driver fatigue was linked to no injury outcome. Further, it was found that risky behaviors such as speeding, driving/riding under the influence of alcohol or drugs, driving/riding with invalid license were significantly associated with severe injury outcome. Developing the injury-severity models based on the segmented crash data has helped to reveal some similarities and differences in crash outcomes based on the crash mechanism and the at-fault road user. It is expected that these findings would provide a data-driven evidence to improve motorcycle safety in the state.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"897 1","pages":"376 - 396"},"PeriodicalIF":2.6,"publicationDate":"2022-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83349541","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 : 2022-04-06DOI: 10.1080/19439962.2022.2056932
M. Shirazi, Srinivas R. Geedipally
Abstract The Highway Safety Manual (HSM) recommends calibrating Safety Performance Functions using a scalar calibration factor. Recently, a few studies explored the merits of estimating a calibration function instead of a calibration factor. Although it seems a promising approach, it is not clear when a calibration function should be preferred over a scalar calibration factor. On the one hand estimating a scalar factor is easier than estimating a calibration function; on the other hand, the calibration results may improve using a calibration function. This study performs a simulation study to compare the two calibration strategies for different ranges of data characteristics (i.e.: sample mean and variance) as well as the sample size. A measure of prediction accuracy is used to compare the two methods. The results show that as the sample size increases, or variation of data decreases, the calibration function performs better than the scalar calibration factor. If the analyst can collect a sample of at least 150 locations, calibration function is recommended over the scalar factor. If the HSM recommendation of 30-50 locations is used and the analyst desires a better accuracy, calibration function is recommended only if the coefficient of variation of data is less than 2. Otherwise, calibration factor yields better results.
{"title":"A simulation analysis to explore when using a calibration function is preferred over a scalar factor for calibrating safety performance functions","authors":"M. Shirazi, Srinivas R. Geedipally","doi":"10.1080/19439962.2022.2056932","DOIUrl":"https://doi.org/10.1080/19439962.2022.2056932","url":null,"abstract":"Abstract The Highway Safety Manual (HSM) recommends calibrating Safety Performance Functions using a scalar calibration factor. Recently, a few studies explored the merits of estimating a calibration function instead of a calibration factor. Although it seems a promising approach, it is not clear when a calibration function should be preferred over a scalar calibration factor. On the one hand estimating a scalar factor is easier than estimating a calibration function; on the other hand, the calibration results may improve using a calibration function. This study performs a simulation study to compare the two calibration strategies for different ranges of data characteristics (i.e.: sample mean and variance) as well as the sample size. A measure of prediction accuracy is used to compare the two methods. The results show that as the sample size increases, or variation of data decreases, the calibration function performs better than the scalar calibration factor. If the analyst can collect a sample of at least 150 locations, calibration function is recommended over the scalar factor. If the HSM recommendation of 30-50 locations is used and the analyst desires a better accuracy, calibration function is recommended only if the coefficient of variation of data is less than 2. Otherwise, calibration factor yields better results.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"91 1","pages":"335 - 349"},"PeriodicalIF":2.6,"publicationDate":"2022-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86972263","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 : 2022-04-04DOI: 10.1080/19439962.2022.2056931
Jingfeng Ma, Gang Ren, Haojie Li, S. Wang, Jingcai Yu
Abstract It is of paramount importance for mitigating road crash losses to characterize the relationship between crash injury severities and contributing factors. Existing studies have revealed mechanism differences of single-vehicle (SV) and multi-vehicle (MV) crashes. This study positions itself at exploring the differences from spatiotemporal, road-environment, driver-vehicle, and collision characteristics. A model comparison as well as the elasticities for the optimal model (partial proportional odds model) is implemented based on 18,083 SV crashes and 22,162 MV crashes in China. The results evidenced the great differences that time, road, speed, lighting, and weather are found to have a positive correlation with only SV crash injury severity, yet negatively related with only MV crash injury severity. Area, location, and angle are significant only for SV crashes, while day, interference, and wind are significant only for MV crashes. The findings revealed that gender, age, collision, location, and time are more influencing factors in SV crashes, while collision, age, gender, vehicle, and wind have more contributions to MV crashes. The findings could provide an insightful reference for prioritizing effective countermeasures to mitigate traffic crash losses.
{"title":"Characterizing the differences of injury severity between single-vehicle and multi-vehicle crashes in China","authors":"Jingfeng Ma, Gang Ren, Haojie Li, S. Wang, Jingcai Yu","doi":"10.1080/19439962.2022.2056931","DOIUrl":"https://doi.org/10.1080/19439962.2022.2056931","url":null,"abstract":"Abstract It is of paramount importance for mitigating road crash losses to characterize the relationship between crash injury severities and contributing factors. Existing studies have revealed mechanism differences of single-vehicle (SV) and multi-vehicle (MV) crashes. This study positions itself at exploring the differences from spatiotemporal, road-environment, driver-vehicle, and collision characteristics. A model comparison as well as the elasticities for the optimal model (partial proportional odds model) is implemented based on 18,083 SV crashes and 22,162 MV crashes in China. The results evidenced the great differences that time, road, speed, lighting, and weather are found to have a positive correlation with only SV crash injury severity, yet negatively related with only MV crash injury severity. Area, location, and angle are significant only for SV crashes, while day, interference, and wind are significant only for MV crashes. The findings revealed that gender, age, collision, location, and time are more influencing factors in SV crashes, while collision, age, gender, vehicle, and wind have more contributions to MV crashes. The findings could provide an insightful reference for prioritizing effective countermeasures to mitigate traffic crash losses.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"79 1","pages":"314 - 334"},"PeriodicalIF":2.6,"publicationDate":"2022-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81414779","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 : 2022-04-04DOI: 10.1080/19439962.2022.2056930
Đorđe Petrović, Dalibor Pešić, R. Mijailović, Bojana Milošević
Abstract Almost 200 million persons with disabilities face specific difficulties in everyday life. Private vehicles provide persons with disabilities with a high level of flexibility, a high level of time efficiency, and a better quality of life. It is sometimes necessary to make vehicle modifications to enable persons with disabilities to drive. One of the most frequent modifications is hand controls. Although drivers with disabilities who use hand controls face the same risk of road accidents as non-disabled drivers, predictors of road accidents for drivers with disabilities who use hand controls have not been the subject of earlier research. The predictors show which factors influence the occurrence of road accidents of drivers with disabilities who use hand controls. This paper aims to develop a model that describes the participation in road accidents of drivers with disabilities who use hand controls and recognises contributing predictors. A multidisciplinary team of experts identified twenty-three predictors that impact road accidents of drivers with disabilities who use hand controls. Bayesian logistic regression models have identified speeding, alcohol consumption, mobile phone usage, and especially fatigue as risky behaviours. This paper proposes several important measures that would improve the safety of drivers with disabilities using hand controls.
{"title":"Modelling participation in road accidents of drivers with disabilities who use hand controls","authors":"Đorđe Petrović, Dalibor Pešić, R. Mijailović, Bojana Milošević","doi":"10.1080/19439962.2022.2056930","DOIUrl":"https://doi.org/10.1080/19439962.2022.2056930","url":null,"abstract":"Abstract Almost 200 million persons with disabilities face specific difficulties in everyday life. Private vehicles provide persons with disabilities with a high level of flexibility, a high level of time efficiency, and a better quality of life. It is sometimes necessary to make vehicle modifications to enable persons with disabilities to drive. One of the most frequent modifications is hand controls. Although drivers with disabilities who use hand controls face the same risk of road accidents as non-disabled drivers, predictors of road accidents for drivers with disabilities who use hand controls have not been the subject of earlier research. The predictors show which factors influence the occurrence of road accidents of drivers with disabilities who use hand controls. This paper aims to develop a model that describes the participation in road accidents of drivers with disabilities who use hand controls and recognises contributing predictors. A multidisciplinary team of experts identified twenty-three predictors that impact road accidents of drivers with disabilities who use hand controls. Bayesian logistic regression models have identified speeding, alcohol consumption, mobile phone usage, and especially fatigue as risky behaviours. This paper proposes several important measures that would improve the safety of drivers with disabilities using hand controls.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"97 1","pages":"291 - 313"},"PeriodicalIF":2.6,"publicationDate":"2022-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74375593","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 : 2022-03-28DOI: 10.1080/19439962.2022.2048763
M. Hossain, Huaguo Zhou, Subasish Das, Xiaoduan Sun, Ahmed Hossain
Abstract More than 30% of cellphone-distracted fatal crashes occurred to drivers younger than 25-years-old in 2018, even though they constitute less than 12% of total licensed drivers in the U.S. Using joint correspondence analysis (JCA), this study analyzed six years (2014–2019) of cellphone-related fatal crashes involving young drivers based on the data from the Fatality Analysis Reporting System (FARS). This unsupervised learning algorithm can graphically display the co-occurrence of variable categories in a lower-dimensional space by effectively summarizing the knowledge of a complex crash dataset. The Boruta algorithm was applied to select the relevant features from the preliminary crash dataset. The empirical results of JCA manifest a few interesting fatal crash patterns. For example, young male drivers in light trucks were involved in deadly collisions while performing specific cellphone activities (other than talking and listening), cellphone-related fatal crashes occurred to young females with prior crash records, and so on. Apart from alcohol and drug involvement, this study identified young drivers’ additional risk-taking maneuvers while engaged in cellphone usage, including: disregarding traffic signs and signals, speeding, and unrestrained driving. The associations could guide the safety officials and policymakers in developing appropriate engineering, education, and enforcement strategies when dealing with cellphone-distracted young drivers.
{"title":"Young drivers and cellphone distraction: Pattern recognition from fatal crashes","authors":"M. Hossain, Huaguo Zhou, Subasish Das, Xiaoduan Sun, Ahmed Hossain","doi":"10.1080/19439962.2022.2048763","DOIUrl":"https://doi.org/10.1080/19439962.2022.2048763","url":null,"abstract":"Abstract More than 30% of cellphone-distracted fatal crashes occurred to drivers younger than 25-years-old in 2018, even though they constitute less than 12% of total licensed drivers in the U.S. Using joint correspondence analysis (JCA), this study analyzed six years (2014–2019) of cellphone-related fatal crashes involving young drivers based on the data from the Fatality Analysis Reporting System (FARS). This unsupervised learning algorithm can graphically display the co-occurrence of variable categories in a lower-dimensional space by effectively summarizing the knowledge of a complex crash dataset. The Boruta algorithm was applied to select the relevant features from the preliminary crash dataset. The empirical results of JCA manifest a few interesting fatal crash patterns. For example, young male drivers in light trucks were involved in deadly collisions while performing specific cellphone activities (other than talking and listening), cellphone-related fatal crashes occurred to young females with prior crash records, and so on. Apart from alcohol and drug involvement, this study identified young drivers’ additional risk-taking maneuvers while engaged in cellphone usage, including: disregarding traffic signs and signals, speeding, and unrestrained driving. The associations could guide the safety officials and policymakers in developing appropriate engineering, education, and enforcement strategies when dealing with cellphone-distracted young drivers.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"122 1","pages":"239 - 264"},"PeriodicalIF":2.6,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84780901","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 : 2022-03-23DOI: 10.1080/19439962.2022.2054038
M. Haq, A. Molan, K. Ksaibati
Abstract This paper aims to advance the current research on the new super diverging diamond interchange (Super DDI) design by evaluating the safety performance of its two versions (super DDI-1 and super DDI-2) using real-field data. Three interchanges were selected in Denver metro, Colorado as the potential candidates to model for future retrofit. This study considered four interchange designs (i.e., existing diamond, DDI, super DDI-1, and super DDI-2) to assess the safety performance using the combination of VISSIM, Synchro, and SSAM analyzing tools. Several microsimulation models (120 scenarios with 600 runs in total) were created with three peak hours (AM, Noon, and PM) for existing (the year 2020) and projected (the year 2030) traffic volumes. Based on the results, both super DDI versions showed high potential in improving safety. As an important finding from this research, super DDI designs outperformed DDI when considering adjacent signals, while DDI performed apparently similar or sometimes even insignificantly better compared to super DDI if no adjacent intersections were located in the vicinity and if the demand was lower than DDI’s capacity.
{"title":"Surrogate safety assessment of super DDI design: A case study in Denver, Colorado","authors":"M. Haq, A. Molan, K. Ksaibati","doi":"10.1080/19439962.2022.2054038","DOIUrl":"https://doi.org/10.1080/19439962.2022.2054038","url":null,"abstract":"Abstract This paper aims to advance the current research on the new super diverging diamond interchange (Super DDI) design by evaluating the safety performance of its two versions (super DDI-1 and super DDI-2) using real-field data. Three interchanges were selected in Denver metro, Colorado as the potential candidates to model for future retrofit. This study considered four interchange designs (i.e., existing diamond, DDI, super DDI-1, and super DDI-2) to assess the safety performance using the combination of VISSIM, Synchro, and SSAM analyzing tools. Several microsimulation models (120 scenarios with 600 runs in total) were created with three peak hours (AM, Noon, and PM) for existing (the year 2020) and projected (the year 2030) traffic volumes. Based on the results, both super DDI versions showed high potential in improving safety. As an important finding from this research, super DDI designs outperformed DDI when considering adjacent signals, while DDI performed apparently similar or sometimes even insignificantly better compared to super DDI if no adjacent intersections were located in the vicinity and if the demand was lower than DDI’s capacity.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"84 1","pages":"265 - 290"},"PeriodicalIF":2.6,"publicationDate":"2022-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77222793","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 : 2022-03-12DOI: 10.1080/19439962.2022.2048760
Burak Yigit Katanalp, Ezgi Eren, Y. Alver
Abstract Spatial distributions of pedestrian-vehicle accident-prone locations (APLs) according to GIS-based models differ. Also, which APLs are determined by conventional models are more critical or which model is more successful in determining APL is still a major concern. To bridge this gap, this paper presents an innovative GIS-based Multi-Criteria Decision Making (MCDM) approach to identify the most critical APLs and to rank APLs with the compromising results of four GIS-based models. The results of planar KDE, network-based KDE, Getis-Ord Gi*, and Local Moran’s I which are weighted with prediction accuracy index (PAI), were evaluated together with MCDM methods: traditional VIKOR and psychometric VIKOR. Results & Discussion: The 15 most critical APLs in the compromise solution were ranked for four time periods. Network-based KDE gave the best performance, while Local Moran’s I performed the worst. Sensitivity analysis showed that the Psychometric VIKOR provides acceptable stability in the rankings of the APLs. The innovative MCDM approaches allowed the results of several models to be evaluated together. Thus, more reliable APLs were identified. Local governments with limited budgets can determine which APLs should be considered to improve pedestrian safety with the recommended approach and can apply to any study area.
{"title":"An integrated solution to identify pedestrian-vehicle accident prone locations: GIS-based multicriteria decision approach","authors":"Burak Yigit Katanalp, Ezgi Eren, Y. Alver","doi":"10.1080/19439962.2022.2048760","DOIUrl":"https://doi.org/10.1080/19439962.2022.2048760","url":null,"abstract":"Abstract Spatial distributions of pedestrian-vehicle accident-prone locations (APLs) according to GIS-based models differ. Also, which APLs are determined by conventional models are more critical or which model is more successful in determining APL is still a major concern. To bridge this gap, this paper presents an innovative GIS-based Multi-Criteria Decision Making (MCDM) approach to identify the most critical APLs and to rank APLs with the compromising results of four GIS-based models. The results of planar KDE, network-based KDE, Getis-Ord Gi*, and Local Moran’s I which are weighted with prediction accuracy index (PAI), were evaluated together with MCDM methods: traditional VIKOR and psychometric VIKOR. Results & Discussion: The 15 most critical APLs in the compromise solution were ranked for four time periods. Network-based KDE gave the best performance, while Local Moran’s I performed the worst. Sensitivity analysis showed that the Psychometric VIKOR provides acceptable stability in the rankings of the APLs. The innovative MCDM approaches allowed the results of several models to be evaluated together. Thus, more reliable APLs were identified. Local governments with limited budgets can determine which APLs should be considered to improve pedestrian safety with the recommended approach and can apply to any study area.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"1 1","pages":"137 - 176"},"PeriodicalIF":2.6,"publicationDate":"2022-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88827158","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 : 2022-03-11DOI: 10.1080/19439962.2022.2048759
Md Saddam Hussain, A. Goswami, Ankit Gupta
Abstract Pedestrians are one of the most vulnerable road users globally. Recent years have witnessed an increasing interest among the scientific community to analyze and enhance pedestrians' safety in an environment dominated by motor vehicles. This study proposes a three-step methodology to identify current and future critical pedestrian crash hotspots. Firstly, available multi-year crash data from two cities in India is digitized, and the spatial autocorrelation tool is used to determine the pedestrian crash hotspots. Secondly, space-time cube and emerging hotspot analysis are carried out to predict crash hotspots along urban streets. Finally, Hotspot Identification (HSID) methods, i.e., Equivalent Property Damage Only (EPDO) and Upper-tail Critical Tests are used to rank the road links based on spatio-temporal crash severity leading to the identification of links needing urgent interventions. The proposed three-step integrated methodology is novel and has never been used to simultaneously identify and prioritize the critical pedestrian crash locations as it has been done in the present study. The developed methodology identifies sections of arterial roads—Strand Road and AJC Bose Road in Kolkata and Gota Road in Ahmedabad, as the critical hotspot links that require urgent intervention.
{"title":"Predicting pedestrian crash locations in urban India: An integrated GIS-based spatiotemporal HSID technique","authors":"Md Saddam Hussain, A. Goswami, Ankit Gupta","doi":"10.1080/19439962.2022.2048759","DOIUrl":"https://doi.org/10.1080/19439962.2022.2048759","url":null,"abstract":"Abstract Pedestrians are one of the most vulnerable road users globally. Recent years have witnessed an increasing interest among the scientific community to analyze and enhance pedestrians' safety in an environment dominated by motor vehicles. This study proposes a three-step methodology to identify current and future critical pedestrian crash hotspots. Firstly, available multi-year crash data from two cities in India is digitized, and the spatial autocorrelation tool is used to determine the pedestrian crash hotspots. Secondly, space-time cube and emerging hotspot analysis are carried out to predict crash hotspots along urban streets. Finally, Hotspot Identification (HSID) methods, i.e., Equivalent Property Damage Only (EPDO) and Upper-tail Critical Tests are used to rank the road links based on spatio-temporal crash severity leading to the identification of links needing urgent interventions. The proposed three-step integrated methodology is novel and has never been used to simultaneously identify and prioritize the critical pedestrian crash locations as it has been done in the present study. The developed methodology identifies sections of arterial roads—Strand Road and AJC Bose Road in Kolkata and Gota Road in Ahmedabad, as the critical hotspot links that require urgent intervention.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"46 1","pages":"103 - 136"},"PeriodicalIF":2.6,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77888984","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 : 2022-03-11DOI: 10.1080/19439962.2022.2048761
Arash Khoda Bakhshi, Mohamed M. Ahmed
Abstract Traffic crashes impose tremendous socio-economic losses on societies. To alleviate these concerns, countless traffic safety researches have shed light on the cognition of observable crash/crash severity contributing factors. Nonetheless, some influential factors might not be observable or measurable, referred to as unobserved heterogeneity, that could be accounted for by structuring random intercepts and slopes in hierarchical models. With this respect, although it is known random slopes can capture more unobserved heterogeneity, most previous studies utilized random intercepts to simplify result interpretations, indicating an inconsistency in the literature considering the hierarchical modeling specification. This study delves into the mentioned confusion within an empirical real-time clustering critical crashes, involving fatal or incapacitating injuries, versus non-critical crashes throughout 402-miles of Interstate-80 in Wyoming. The crash dataset was conflated with real-time traffic-related and environmental contributing factors. Regarding the inclusion of random intercepts and slopes, eleven Logistic regressions were conducted. As a data-dependent matter, results depicted random slopes, compared to random intercepts, do not necessarily enhance models’ out-of-sample predictive performance because they impose much more complexity on the models’ structure. Besides, considering the type of unobserved heterogeneity, if random slopes are required, random intercepts should be accompanied to allow data showing their true patterns.
{"title":"Does random slope hierarchical modeling always outperform random intercept counterpart? Accounting for unobserved heterogeneity in a real-time empirical analysis of critical crash occurrence","authors":"Arash Khoda Bakhshi, Mohamed M. Ahmed","doi":"10.1080/19439962.2022.2048761","DOIUrl":"https://doi.org/10.1080/19439962.2022.2048761","url":null,"abstract":"Abstract Traffic crashes impose tremendous socio-economic losses on societies. To alleviate these concerns, countless traffic safety researches have shed light on the cognition of observable crash/crash severity contributing factors. Nonetheless, some influential factors might not be observable or measurable, referred to as unobserved heterogeneity, that could be accounted for by structuring random intercepts and slopes in hierarchical models. With this respect, although it is known random slopes can capture more unobserved heterogeneity, most previous studies utilized random intercepts to simplify result interpretations, indicating an inconsistency in the literature considering the hierarchical modeling specification. This study delves into the mentioned confusion within an empirical real-time clustering critical crashes, involving fatal or incapacitating injuries, versus non-critical crashes throughout 402-miles of Interstate-80 in Wyoming. The crash dataset was conflated with real-time traffic-related and environmental contributing factors. Regarding the inclusion of random intercepts and slopes, eleven Logistic regressions were conducted. As a data-dependent matter, results depicted random slopes, compared to random intercepts, do not necessarily enhance models’ out-of-sample predictive performance because they impose much more complexity on the models’ structure. Besides, considering the type of unobserved heterogeneity, if random slopes are required, random intercepts should be accompanied to allow data showing their true patterns.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"3 1","pages":"177 - 214"},"PeriodicalIF":2.6,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85443482","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}