Analytic Methods in Accident Research最新文献

{"title":"Investigating work-related distraction’s impact on male taxi driver safety: A hazard-based duration model","authors":"Shi Ye ,&nbsp;Tiantian Chen ,&nbsp;Oscar Oviedo-Trespalacios ,&nbsp;N.N. Sze ,&nbsp;Sikai Chen","doi":"10.1016/j.amar.2024.100350","DOIUrl":"10.1016/j.amar.2024.100350","url":null,"abstract":"<div><p>With the increasing use of phone-based ride-hailing apps, concerns have arisen regarding road safety and driver distraction. Despite the recognized safety risks of driver distraction, limited research has explored how distractions from various ride-hailing systems affect drivers in the taxi industry. To close this gap, the current research utilized a driving simulator experiment involving 51 male taxi drivers in two road environments (urban street and motorway) and three distracted driving conditions (no distraction, auditory distraction via radio dispatching system, and visual-manual distraction via mobile application). A car-following scenario with sudden brake events was incorporated into the experiments because this is a typical safety–critical situation where attention will determine the outcome. The collected performance indicators include brake reaction time, time headway, and car-following distance. The grouped random parameters Weibull accelerated failure time model was applied to model the duration data under different road conditions. The brake reaction time and time headway are dependent variables, while the car-following distance is a covariate in the models. The results indicate that although taxi drivers show longer brake reaction time when distracted by mobile app and radio system, this does not necessarily equate with greater risk or reduced safety since they compensate for the risk of rear-end crashes by maintaining a longer time headway. In general, taxi drivers’ brake reaction time and time headway are more profoundly affected by mobile apps when distracted in both urban and motorway scenarios. This highlights the elevated risks associated with such technologies. In addition, significant interaction effects revealed the observed heterogeneity, which suggests that drivers’ personal characteristics influence the relationship between distraction type and driving performance. This research provides valuable insights for designing safer ride-hailing operations and systems.</p></div>","PeriodicalId":47520,"journal":{"name":"Analytic Methods in Accident Research","volume":"44 ","pages":"Article 100350"},"PeriodicalIF":12.5,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142077395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rethinking cycling safety: The role of gender in cyclist crash injury severity outcomes","authors":"Natalia Barbour,&nbsp;Mohamed Abdel-Aty","doi":"10.1016/j.amar.2024.100349","DOIUrl":"10.1016/j.amar.2024.100349","url":null,"abstract":"<div><p>Given the ongoing climate crisis and the need for environmentally friendly communities, there has been an increasing interest in sustainable mobility solutions such as cycling. This study seeks to incorporate an equitable component to studying cycling safety and uses one full year’s data of 4,457 single bicycle-single motor vehicle crashes that took place in 2022 in the state of Florida to estimate a series of random parameters multinomial logit models with heterogeneity in the means and variances to capture gender differences in outcome severities. A comparison of advanced statistical models such as unconstrained and partially constrained approaches, that were previously employed in the literature to test for temporal stability, is undertaken in a new application. A partially constrained model is estimated to best identify gender specific factors and argue the need to evaluate and promote safety of female and male cyclists separately. The study finds substantial differences between how the contributing factors and crash circumstances impact the crash injury severity of women and men cyclists. It evaluates factors such as age, location, cyclist behavior, weather, and road design as well as performs out-of-sample simulation to gain additional insights. The findings of this research emphasize the need for targeted approaches in designing our cities and policy making that account for the collective differences in behavior and experience of women and men cyclists.</p></div>","PeriodicalId":47520,"journal":{"name":"Analytic Methods in Accident Research","volume":"44 ","pages":"Article 100349"},"PeriodicalIF":12.5,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142049357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A nonlinear mixed logit model of occupant severity in autonomous vehicle crashes","authors":"Lan Ventura ,&nbsp;Rohan Shrestha ,&nbsp;Narayan Venkataraman ,&nbsp;Venkataraman Shankar ,&nbsp;Nardos Feknssa","doi":"10.1016/j.amar.2024.100348","DOIUrl":"10.1016/j.amar.2024.100348","url":null,"abstract":"<div><p>This paper presents a nonlinear mixed logit to capture heterogeneous effects of contributing factors on autonomous involved occupant severity. Autonomous level information to this point has been quite sparse in the context of real-world crash scenarios and police reporting. However, the Texas Department of Transportation (TxDOT) began reporting autonomous involvement in April of 2023. With reporting still in its early stages, this analysis incorporated three distinct vehicle technologies: non-autonomous internal combustion engine (ICE) vehicles; ICE and hybrid electric autonomous vehicles; and fully electric autonomous vehicles. Crash data included any crash in Texas from April to December of 2023 that involved at least one autonomous-indicated vehicle (either the second or third distinct vehicle technology). Random parameters were found with respect to: an indicator for occupant involvement in the first harmful crash sequence event, with that event being collision with a fixed object, for no injury; proportion of autonomous vehicles for no injury; an intersection related indicator for possible injury; total occupant count for possible injury; and total vehicle count for injury. The count and proportion variables were expressed as nonlinear relationships, for which random parameters improved prediction accuracy by 37.50 % and 30.00 %, respectively, for possible injury and injury outcomes, as compared to fixed parameters. The findings in this study highlight the applicability of the nonlinear mixed logit for severity analysis with respect to complex autonomous interactions in crashes.</p></div>","PeriodicalId":47520,"journal":{"name":"Analytic Methods in Accident Research","volume":"44 ","pages":"Article 100348"},"PeriodicalIF":12.5,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stochastic method based on copulas for predicting severe road traffic interactions","authors":"Zhankun Chen,&nbsp;Oksana Yastremska-Kravchenko,&nbsp;Aliaksei Laureshyn,&nbsp;Carl Johnsson,&nbsp;Carmelo D’Agostino","doi":"10.1016/j.amar.2024.100347","DOIUrl":"10.1016/j.amar.2024.100347","url":null,"abstract":"<div><p>A major difficulty in assessing road traffic safety is the scarcity of historical accident data. xxThis is a common problem in contexts where a certain level of safety has been reached or where exposure is low, such as mixed traffic conditions with different levels of transport automation. Recent studies have demonstrated how severe interactions between road users and/or road users and infrastructure can be a direct measure of safety. However, limiting the investigation to only the most extreme events may lead to inconclusive results considering the lack of prediction robustness and the possible selection bias. In this context, extreme value theory (EVT) is commonly used to extrapolate crashes from road traffic interactions, even combining several indicators. The present work extends the EVT paradigm by proposing a method based on copula functions and EVT, which enables a more specific and continuous evaluation of interaction severity. Compared with pure EVT, this new approach extends the boundary to interactions of all severities while implicitly assuming that the relationship between safety-relevant events and road casualties is stochastic. This EVT-copula approach was also compared with bivariate peaks over threshold (BPOT). It was found that the two approaches yield similar prediction results for crash probabilities. Furthermore, the proposed approach applies to events not properly defined in BPOT and provides more accurate predictions for severe (and less severe) interactions compared with BPOT, when benchmarked against observations.</p></div>","PeriodicalId":47520,"journal":{"name":"Analytic Methods in Accident Research","volume":"44 ","pages":"Article 100347"},"PeriodicalIF":12.5,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2213665724000319/pdfft?md5=32e39c35f91b2aa9db0b85ad1053c599&pid=1-s2.0-S2213665724000319-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141732062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incorporating inconsistency patterns on road networks into crash modeling","authors":"R.N. Shilpa,&nbsp;B.K. Bhavathrathan","doi":"10.1016/j.amar.2024.100340","DOIUrl":"https://doi.org/10.1016/j.amar.2024.100340","url":null,"abstract":"<div><p>This paper expands the scope of geometric design inconsistency analysis from corridor scales to network-wide perspectives, exploring the impact of inconsistencies’ spatial-patterns on crashes, which remains largely under-explored. We define spatial-patterns of segment-level inconsistencies, focusing on their spread, contiguity, frequency, density, and magnitude. We devise a new method to measure inconsistency-contiguity and inconsistency-frequency based on adjacent segment-triplets within regions. Through micro–macro integrated models, we reveal the scalable influence of inconsistency which remain significant at the segment-level but gets modulated by spatial-patterns at the regional-level. The integrated models consistently outperform their non-integrated counterparts, emphasizing the importance of this integrated approach. This study highlights that regions with rare inconsistency occurrences demonstrate higher crash counts, while regions with uniform inconsistency occurrences exhibit lower crash rates, unveiling insights into the road conditions’ impact on driver behavior. Finally, we also propose a novel tool - vulnerability contours on <em>frequency-hyperplane</em> to map regions’ relative safety.</p></div>","PeriodicalId":47520,"journal":{"name":"Analytic Methods in Accident Research","volume":"43 ","pages":"Article 100340"},"PeriodicalIF":12.5,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141487182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A non-stationary bivariate extreme value model to estimate real-time pedestrian crash risk by severity at signalized intersections using artificial intelligence-based video analytics","authors":"Hassan Bin Tahir,&nbsp;Md Mazharul Haque","doi":"10.1016/j.amar.2024.100339","DOIUrl":"10.1016/j.amar.2024.100339","url":null,"abstract":"<div><p>Vehicle-pedestrian crashes are generally severe due to the vulnerability of pedestrians compared to the occupants of vehicles. However, the estimation of pedestrian crash risk by severity has not been given adequate attention in the field of proactive safety assessments applying traffic conflict techniques. This study proposes a novel analytical framework to estimate real-time pedestrian crash risk by severity at the signal cycle level while incorporating the effect of time-varying exogenous variables. Specifically, the study applies a non-stationary bivariate extreme value model to jointly model the post encroachment time and Delta-V for estimating real-time pedestrian crash risk by severity at individual signal cycles. The proposed framework is tested on 144 h of video data collected from three signalized intersections in Queensland, Australia. The developed bivariate extreme value model has been found to reliably predict severe and non-severe pedestrian crash frequencies compared to the historical crash records of severe and non-severe pedestrian crashes at those signalized intersections. Results suggest that the frequency of pedestrian conflicts per signal cycle and average pedestrian speed in a signal cycle are associated with real-time pedestrian crash risks. In addition, pedestrian conflicts per signal cycle and average vehicle speed per cycle were associated with the interaction severity component of the non-stationary bivariate extreme value model. The proposed proactive estimation of pedestrian crash risk by severity levels can help design time-sensitive countermeasures for vulnerable road users.</p></div>","PeriodicalId":47520,"journal":{"name":"Analytic Methods in Accident Research","volume":"43 ","pages":"Article 100339"},"PeriodicalIF":12.9,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S221366572400023X/pdfft?md5=2b570c37c91d6d914d3b67f43dc45031&pid=1-s2.0-S221366572400023X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141282106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A temporal statistical assessment of the effectiveness of bicyclist safety helmets in mitigating injury severities in vehicle/bicyclist crashes","authors":"Nawaf Alnawmasi ,&nbsp;Asim Alogaili ,&nbsp;Rakesh Rangaswamy ,&nbsp;Oscar Oviedo-Trespalacios","doi":"10.1016/j.amar.2024.100338","DOIUrl":"https://doi.org/10.1016/j.amar.2024.100338","url":null,"abstract":"<div><p>This study estimates mixed logit models taking into account heterogeneity in means and partially constrained parameters in order to explore possible shifts within parameters over time to study factors influencing bicyclist injury severity outcomes. Separate statistical models are estimated for two bicyclist helmet-wearing scenarios (helmet and non-helmet) using a comprehensive dataset from Florida covering a three-year period to assess COVID-19 effects from the 1st of January 2019 to the 31st of December 2021. This research evaluates several factors influencing helmeted and non-helmeted bicyclist injury severity, encompassing the attributes of drivers and cyclists, the environment and weather, the features of the roads and their temporal aspects, and the different types of vehicles. The performed analysis further enhances model robustness by assessing the temporal stability and transferability across different contexts through likelihood ratio tests, alongside an in-depth examination of the temporal consistency of explanatory variables via marginal effects analysis, confirming significant variations between non-helmeted and helmeted bicyclist models and revealing temporal shifts in factors affecting injury severity during the study period. Findings from the model estimations identify several significant variables with consistent parameter estimates across years. Stop signs, cycling with traffic, and dark, unlit conditions increase severe injury risk in non-helmet models, while the stop sign indicator consistently reduces severe injury risk in helmet models. Statistically significant random parameters are identified across different years and helmet-wearing scenarios, including the male driver indicator, which exhibits varying effects on injury severity. Out-of-sample prediction analysis suggests helmets reduce severe injury probability but may increase minor injuries and decrease no-injury accidents, indicating potential risk compensation behavior among helmeted bicyclists. Although helmets offer protection against severe injuries for bicyclists, it is crucial to adopt a comprehensive safety approach, particularly given the evolving demographics of bicyclists amid the COVID-19 outbreak. This entails considering factors like bicyclist and driver behavior, environmental conditions, and infrastructure enhancements. Policymakers, road safety professionals, and advocacy groups should collaborate to develop holistic strategies to address the determinants of bicycle crash severity outcomes and enhance safety measures for bicyclists across diverse road environments.</p></div>","PeriodicalId":47520,"journal":{"name":"Analytic Methods in Accident Research","volume":"43 ","pages":"Article 100338"},"PeriodicalIF":12.9,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141242134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of walking accessibility for metro system on pedestrian safety: A multiple membership multilevel model","authors":"Manman Zhu ,&nbsp;N.N. Sze ,&nbsp;Haojie Li","doi":"10.1016/j.amar.2024.100337","DOIUrl":"https://doi.org/10.1016/j.amar.2024.100337","url":null,"abstract":"<div><p>In the past decades, many cities have adopted transit-oriented development approach for urban planning. Studies have explored the effects of built environment, street network and accessibility on the perception and behaviour of pedestrians. However, the relationship between pedestrian safety and walking accessibility is less studied. In this study, influences of land use, socio-demographics, pedestrian network, and transport facilities on pedestrian crash frequencies in the areas around metro stations would be evaluated. Additionally, walking accessibility for individuals with and without physical disabilities would be accounted for. Since data at different spatial scales, i.e., zone level (individual) versus catchment area level (group), are used, the hierarchical approach is adopted for the crash frequency model. Furthermore, some zones are nested within the catchment areas of more than one metro station, the multiple membership approach should be adopted, accounting for the possible correlation. Different from the conventional multiple membership multilevel model, multiple membership weights would be assigned in accordance with the walking distances between zones and stations. Last but not least, temporal instability in the parameter estimation is also explored. Results indicate that pedestrian crash frequencies increase with population density, working population, traffic volume, walking trip, footpath density, node density, barrier-free facilities, bus stop, residential area, commercial area, and government and utility area. In contrast, pedestrian crash frequencies decrease with average gradient and walking accessibility. Findings should shed light on the street design that can enhance walking accessibility and public transport use, without compromising pedestrian safety. Moreover, issues of spatial crash analysis, including hierarchical data structure, and between- and within-group variances, are addressed.</p></div>","PeriodicalId":47520,"journal":{"name":"Analytic Methods in Accident Research","volume":"43 ","pages":"Article 100337"},"PeriodicalIF":12.9,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141242133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling the determinants of injury severities across age groups and time: A deep dive into the unobserved heterogeneity among pedestrian crashes","authors":"Qingli Liu,&nbsp;Fan Li,&nbsp;Kam K.H. Ng","doi":"10.1016/j.amar.2024.100336","DOIUrl":"10.1016/j.amar.2024.100336","url":null,"abstract":"<div><p>Pedestrians, particularly susceptible to road traffic crashes, experience varying injury severities influenced by age and time shifts. This research aims to investigate the differences and temporal shifts in factors influencing pedestrian injury severities across different age groups. To achieve this, three random parameters binary logit models with heterogeneity in the means (and variances) were employed. Four years of pedestrian crash data in Hong Kong were utilized in this study. According to United Nations’ definitions of the young and elderly, pedestrians were categorized into three groups: young (under 25 years old), middle-aged (25–65 years old), and elderly (over 65 years old). Initial likelihood ratio tests indicated temporal stability in the young group between 2019 and 2021, with further tests confirming age transferability and overall temporal stability after integrating the three years of young data. The partially constrained temporal stability approach was then developed to further capture the temporal stability of individual variables and simplify model results. Model results identified factors impacting pedestrian injury severities, encompassing pedestrian, driver, vehicle, temporal, and light condition characteristics. Some contributing variables exhibit age-transferability or temporal stability, such as controlled crossing, near controlled crossing, inattentive driver and private car. However, the significance of most contributors varies across age groups and years, with certain factors being age-specific or year-specific. Out-of-sample predictions underscore the cumulative likelihood of fatal or severe injuries with advancing age, and the middle-aged models showed the highest level of temporal stability regarding the risk of injury severity compared to the other two age models. Moreover, middle-aged pedestrians in Hong Kong faced the highest risk of fatal or severe injuries during the first year of the COVID-19 lockdown (2020), but the risk significantly declined for pedestrians of all age groups in the subsequent year. Based on these findings, targeted preventive measures that take into account age differences have been proposed to effectively enhance pedestrian safety.</p></div>","PeriodicalId":47520,"journal":{"name":"Analytic Methods in Accident Research","volume":"43 ","pages":"Article 100336"},"PeriodicalIF":12.9,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141134305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic unified approach for addressing temporal instability in road safety analysis","authors":"Kazi Redwan Shabab ,&nbsp;Tanmoy Bhowmik ,&nbsp;Mohamed H. Zaki ,&nbsp;Naveen Eluru","doi":"10.1016/j.amar.2024.100335","DOIUrl":"https://doi.org/10.1016/j.amar.2024.100335","url":null,"abstract":"<div><p>Multivariate models are widely employed for crash frequency analysis in traffic safety literature. In the context of analyzing data for multiple instances (such as years), it becomes essential to evaluate the stability of parameters over time. The current research proposes a novel approach, labelled the mixed spline indicator pooled model, that offers significant enhancement relative to current approaches employed for capturing temporal instability. The proposed approach entails carefully creating independent variables that allow us to measure parameter slope changes over time and can be easily integrated into existing methodological frameworks. The current research effort compares four multivariate model systems: year specific negative binomial model, year indicator pooled model, spline indicator pooled model, and mixed spline indicator pooled model. The model performance is compared using log-likelihood and Bayesian Information Criterion. The empirical analysis is conducted using the Traffic Analysis Zone (TAZ) level crash severity records from Central Florida for the years from 2011 to 2019. The comparison results indicate that the proposed mixed spline indicator pooled model outperforms the other models providing superior data fit while optimizing the number of parameters. The proposed mixed spline model can allow a piece-wise linear functional form for the parameter and is suitable to forecast crashes for future years as illustrated in our predictive performance analysis.</p></div>","PeriodicalId":47520,"journal":{"name":"Analytic Methods in Accident Research","volume":"43 ","pages":"Article 100335"},"PeriodicalIF":12.9,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141083493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}