Accident; analysis and prevention最新文献

{"title":"A sequel to “Comprehensive analysis of single- and multi-vehicle large truck at-fault crashes on rural and urban roadways in Alabama”: Accounting for temporal instability in crash factors","authors":"Sharareh Biglari ,&nbsp;Emmanuel Kofi Adanu ,&nbsp;Steven Jones","doi":"10.1016/j.aap.2024.107723","DOIUrl":"10.1016/j.aap.2024.107723","url":null,"abstract":"<div><p>This exploratory study is a follow-up to a 2014 study that investigated factors associated with large truck at-fault crash outcomes in Alabama. To assess unobserved temporal changes in the effects of the crash factors, this study re-creates the original crash models developed in the 2014 study using crash data from 2017 to 2019. Four mixed logit models were re-created using the same variables used in the previous study to analyze contributing crash factors to injury severity of single-vehicle (SV) and multi-vehicle-involved (MV) large truck at-fault crashes in urban and rural settings. It was found that there have been temporal changes in how many of the factors influenced crash severity with some of them no longer showing any significant association with crash outcomes, while others remained significant. Further, it was observed that some of the variables that remained significant had different relationships with crash injury severity in the newer severity models. For instance, while factors such as fatigued driver (in rural crashes), clear weather (in urban crashes), single-unit truck (in rural SV crashes), truck rollover (in urban SV crashes) maintained consistent significance over time, the effects of variables such as at-fault male drivers (in urban MV crashes), at-fault female drivers (in urban MV crashes), and hitting fixed object (in rural MV crashes) have changed. One such notable difference is the variable for absence of traffic control which increased the probability of major injury in rural SV crashes by 49.50% in the 2014 model but decreased the probability of recording major injuries by 108.90% using the 2017–2019 data. Considering the temporal changes that were observed in the recreated models, newer models were developed, revealing the emergence of new variables such as truck age that are significantly associated with truck crash severity. The findings of this study provide evidence to suggest that some crash severity factors for at-fault large truck collisions vary over time, with newer ones also emerging over time. These findings can also help trucking companies, transportation engineers, and other industry experts in developing measures to reduce large truck crashes.</p></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"206 ","pages":"Article 107723"},"PeriodicalIF":5.7,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141854495","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":"Wait or Pass? Promoting intersection’s cooperation via identifying vehicle’s social behavior","authors":"Yubin Xie ,&nbsp;Yue Liu ,&nbsp;Ronggang Zhou ,&nbsp;Xuezun Zhi ,&nbsp;Alan H.S. Chan","doi":"10.1016/j.aap.2024.107724","DOIUrl":"10.1016/j.aap.2024.107724","url":null,"abstract":"<div><p>Lack of communication between road users can reduce traffic efficiency and cause safety issues like traffic accidents. Researchers are exploring how intelligent vehicles should communicate with the environment, other vehicles, and road users. This study explores the impact of social information communication on traffic safety and efficiency at intersections through vehicle-to-vehicle (V2V) communication. The research examines how these factors influence drivers’ decision-making and cooperative behavior by incorporating social value orientation (SVO) and driving agent identity into V2V systems and automated vehicle (AV) decision-support systems. An experimental platform simulating intersection conflict scenarios was developed, and three studies involving 334 participants were conducted. The findings reveal that providing drivers with social information about opposing vehicles significantly promotes cooperative behavior and safer driving strategies. Specifically, the waiting rate for people facing proself vehicles (Mean = 0.22) is significantly higher than when facing prosocial vehicles (Mean = 0.79). When SVO is unknown, the waiting rate is around 0.5. Participants behaved more waiting when confronted with an AV than human-driven vehicles. With AV recommendations based on SVO, participants’ final waiting rate increases as the recommended waiting rate increases. The optimal recommended waiting rate for AV is most acceptable when it matches the average waiting rate of the other vehicle. This research underscores the importance of integrating social information into V2V communication to improve road safety, aiding in designing automated decision-making strategies for AV and enhancing user satisfaction.</p></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"206 ","pages":"Article 107724"},"PeriodicalIF":5.7,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141854510","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":"Examining driver injury severity in motor vehicle crashes: A copula-based approach considering temporal heterogeneity in a developing country context","authors":"Shahrior Pervaz ,&nbsp;Tanmoy Bhowmik ,&nbsp;Naveen Eluru","doi":"10.1016/j.aap.2024.107721","DOIUrl":"10.1016/j.aap.2024.107721","url":null,"abstract":"<div><p>Using data from a developing country, the current study develops a copula-based joint modeling framework to study crash type and driver injury severity as two dimensions of the severity process. To be specific, a copula-based multinomial logit model (for crash type) and generalized ordered logit model (for driver severity) is estimated in the study. The data for our analysis is drawn from Bangladesh for the years of 2000 to 2015. Given the presence of multiple years of data, we develop a novel spline variable generation approach that facilitates easy testing of variation in parameters across time in crash type and severity components. A comprehensive set of independent variables including driver and vehicle characteristics, roadway attributes, environmental and weather information, and temporal factors are considered for the analysis. The model results identify several important variables (such as driving under the influence of drug and alcohol, speeding, vehicle type, maneuvering, vehicle fitness, location type, road class, road geometry, facility type, surface quality, time of the day, season, and light conditions) affecting crash type and severity while also highlighting the presence of temporal instability for a subset of parameters. The superior model performance was further highlighted by testing its performance using a holdout sample. Further, an elasticity exercise illustrates the influence of the exogenous variables on crash type and injury severity dimensions. The study findings can assist policy makers in adopting appropriate strategies to make roads safer in developing countries.</p></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"206 ","pages":"Article 107721"},"PeriodicalIF":5.7,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141764806","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":"Analyzing fatal crash patterns of recidivist drivers across genders and age Groups: A hazard-based duration approach","authors":"Richard Dzinyela ,&nbsp;Emmanuel Kofi Adanu ,&nbsp;Hardik Gupta ,&nbsp;Pranik Koirala ,&nbsp;Nawaf Alnawmasi ,&nbsp;Subasish Das ,&nbsp;Dominique Lord","doi":"10.1016/j.aap.2024.107713","DOIUrl":"10.1016/j.aap.2024.107713","url":null,"abstract":"<div><p>Identifying factors that significantly affect drivers that are repeatedly involved in traffic violations or non-fatal crashes (defined here as recidivist drivers) is very important in highway safety studies. This study sought to understand the relationship between a set of variables related to previous driving violations and the duration between a previous non-fatal crash and a subsequent fatal crash, taking into account the age and gender of the driver. By identifying the characteristics of this unique driver population and the factors that influence the duration between their crash events strategies can be put in place to prevent the occurrence of future and potentially fatal crashes. To do this, a five-year (2015–2019) historical fatal crash data from the United States was used for this study. Out of 15,956 fatal crashes involving recidivist drivers obtained, preliminary analysis revealed an overrepresentation of males (about 75%). It was also found that the average duration between the two crash events was about a year and a half, with only an average of one month difference between male and female drivers. Using hazard-based duration models, factors such as number of previous crashes, previous traffic violations, primary contributing factors and some driver demographic characteristics were found to significantly be associated with the duration between the two crash events. The duration between the two events increased with driver’s age for drivers who were involved in only one previous crash and the duration was shorter for those that were previously involved in multiple crashes. Previous DUI violations, license suspensions, and previous speeding violations were found to be associated with shorter durations, at varying degrees depending on the driver’s age and gender. The duration was also observed to be longer if the fatal crash involved alcohol or drug use among younger drivers but shorter among middle-aged male drivers. These findings reveal interesting dynamics that may be linked to recidivist tendencies among some drivers involved in fatal crashes. The factors identified from this study could help identify crash countermeasures and programs that will help to reform such driver behaviors.</p></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"206 ","pages":"Article 107713"},"PeriodicalIF":5.7,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141756496","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":"Exploring the impact of right-turn safety measures on E-bike-heavy vehicle conflicts at signalized intersections","authors":"Chenxiao Zhang ,&nbsp;Yongfeng Ma ,&nbsp;Tarek Sayed ,&nbsp;Yanyong Guo ,&nbsp;Shuyan Chen ,&nbsp;Yuanhang Fu","doi":"10.1016/j.aap.2024.107722","DOIUrl":"10.1016/j.aap.2024.107722","url":null,"abstract":"<div><p>A major safety hazard for e-bike riders crossing an intersection is encountering heavy vehicles turning right in the same direction, which often results in severe casualties. Recently, some cities in China have implemented right-turn safety improvement treatments (i.e., right-turn yielding rules and right-turn warning facilities) at intersections to reduce the occurrence of such accidents. However, the risk perception and behavior of e-bike riders and heavy vehicle drivers dynamically change during the right-turn interaction process, and the safety effects of different right-turn safety measures remain unclear. This study aims to investigate the safety effect of right-turn safety measures on E-Bike-Heavy Vehicle (EB-HV) right-turn conflicts at signalized intersections. The right-turn conflicts and potential influencing factors are extracted from aerial video data, including characteristics of right-turn warning facilities, characteristics and behavior of e-bike riders and heavy vehicle drivers, environmental factors, and traffic-related factors. Moreover, traffic conflict indicators such as the Time to Collision (TTC), Post Encroachment Time (PET), and Jerk are selected and calculated. Multinomial and binary logit models are used to estimate and analyze the EB-HV right-turn conflict severity and drivers yielding behavior. The results reveal that: (a) right-turn warning facilities can decrease the probability of slight and severe EB-HV right-turn conflicts, while the presence of law enforcement cameras could prompt heavy vehicle drivers to comply with the yielding rules and adopt more cautious behavior; (b) increased heavy vehicle speed and acceleration before turning right have strong correlation to illegitimate yielding behavior of the driver and higher EB-HV right-turn conflict severity; and (c) aggressive behavior of e-bike rider increases the severe conflict probability, especially at intersections without right-turn warning facilities. Based on the study findings, several practical implications are suggested to reduce the risk of EB-HV right-turn conflicts, enhance the effectiveness of right-turn safety measures, and improve crossing safety for e-bike riders.</p></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"206 ","pages":"Article 107722"},"PeriodicalIF":5.7,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141732123","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":"Exploratory analysis of injury severity under different levels of driving automation (SAE Levels 2 and 4) using multi-source data","authors":"Shengxuan Ding,&nbsp;Mohamed Abdel-Aty,&nbsp;Natalia Barbour,&nbsp;Dongdong Wang,&nbsp;Zijin Wang,&nbsp;Ou Zheng","doi":"10.1016/j.aap.2024.107692","DOIUrl":"10.1016/j.aap.2024.107692","url":null,"abstract":"<div><p>Vehicles equipped with automated driving capabilities have shown potential to improve safety and operations. Advanced driver assistance systems (ADAS) and automated driving systems (ADS) have been widely developed to support vehicular automation. Although the studies on the injury severity outcomes that involve automated vehicles are ongoing, there is limited research investigating the difference between injury severity outcomes for the ADAS and ADS equipped vehicles. To ensure a comprehensive analysis, a multi-source dataset that includes 1,001 ADAS crashes (SAE Level 2 vehicles) and 548 ADS crashes (SAE Level 4 vehicles) is used. Two random parameters multinomial logit models with heterogeneity in the means of random parameters are considered to gain a better understanding of the variables impacting the crash injury severity outcomes for the ADAS (SAE Level 2) and ADS (SAE Level 4) vehicles. It was found that while 67 percent of crashes involving the ADAS equipped vehicles in the dataset took place on a highway, 94 percent of crashes involving ADS took place in more urban settings. The model estimation results also reveal that the weather indicator, driver type indicator, differences in the system sophistication that are captured by both manufacture year and high/low mileage as well as rear and front contact indicators all play a role in the crash injury severity outcomes. The results offer an exploratory assessment of safety performance of the ADAS and ADS equipped vehicles using the real-world data and can be used by the manufacturers and other stakeholders to dictate the direction of their deployment and usage.</p></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"206 ","pages":"Article 107692"},"PeriodicalIF":5.7,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141732124","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":"Gap acceptance behaviour and crash risks of mobile phone distracted young drivers at roundabouts: A random parameters survival model","authors":"Esther Memeh ,&nbsp;Yasir Ali ,&nbsp;Francisco Javier Rubio ,&nbsp;Craig Hancock ,&nbsp;Md Mazharul Haque","doi":"10.1016/j.aap.2024.107720","DOIUrl":"10.1016/j.aap.2024.107720","url":null,"abstract":"<div><p>Navigating through complex road geometries, such as roundabouts, poses significant challenges and safety risks for drivers. These challenges may be exacerbated when drivers are distracted by mobile phone conversations. The interplay of road geometry, driving state, and driver characteristics in creating compound risks remains an underexplored area in existing literature. Proper understanding of such compound crash risk is not only crucial to improve road geometric design but also to educate young drivers, who are particularly risk-takers and to devise strict penalties for mobile phone usage whilst driving. To fill this gap, this study examines crash risks associated with gap acceptance manoeuvres at roundabouts in the simulated environment of the CARRS-Q driving simulators, where 32 licenced young drivers were exposed to a gap acceptance scenario in three phone conditions: baseline (no phone conversation), handheld, and hands-free. A parametric random parameters survival modelling approach is adopted to understand safety margins—characterised by gap times—during gap acceptance scenarios at roundabouts, concurrently uncover driver-level heterogeneity with mobile phone distraction and capture repeated measures of experiment design. The model specification includes the handheld phone condition as a random parameter and hands-free phone condition, acceleration noise, gap size, crash history, and gender as non-random parameters. Results suggest that the majority of handheld distracted drivers have smaller safety margins, reflecting the negative consequences of engaging in handheld phone conversations. Interestingly, a group of drivers in the same handheld phone condition have been found to exhibit cautious/safer behaviour, as evidenced by longer gap times, reflecting their risk compensation behaviour. Female distracted drivers are also found to exhibit safer gap acceptance behaviour compared to distracted male drivers. The findings of this study shed light on the compound risk of mobile phone distraction and gap acceptance at roundabouts, requiring policymakers and authorities to devise strict penalties and laws for distracted driving.</p></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"206 ","pages":"Article 107720"},"PeriodicalIF":5.7,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0001457524002653/pdfft?md5=99419d3630030cf2700befd259dc9772&pid=1-s2.0-S0001457524002653-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141638444","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":"Analysis of pedestrian-two-wheeler conflicts at green light digital countdown signals: A random parameter ordered logit model approach","authors":"Jianrong Liu,&nbsp;Xinyu Chen","doi":"10.1016/j.aap.2024.107716","DOIUrl":"10.1016/j.aap.2024.107716","url":null,"abstract":"<div><p>The rising prevalence of e-bikes and shared bikes in transportation modes adds complexity to pedestrian movement at intersections. The conflict technique is a substitute for collisions in analyzing pedestrian safety at digital countdown signal intersections. Pedestrian and two-wheeler trajectories were obtained using Unmanned Aerial Vehicle (UAV) and T-Analyst software. The severity of pedestrian-two-vehicle conflicts was assessed using indicators such as Time to Collision (TTC), Post Encroachment Time (PET), and Yaw Rate Ratio (YRR), along with the fuzzy C-mean clustering method. An analysis of the impact of pedestrian characteristics, cyclist characteristics, and road conflict factors on severity was conducted using a random parameter ordered logit model. A total of 630 valid conflicts were identified, comprising 105 potential conflicts, 242 minor conflicts, and 283 serious conflicts. More minor and serious conflicts occurred in Signal 1 and Signal 2. Serious conflicts mainly occurred in road Zone 2, Zone 3, and Zone 5, while minor conflicts were more frequent in Zone 4 and Zone 5. Pedestrian crossing at Signal 2 increased the conflict severity, and the refuge island had a similar effect. Cyclists passing the conflict point first reduced the probability of serious conflicts. Older adults are safer at countdown signal intersections than young people. It is essential to enhance the awareness of digital countdown signals among youth. Managers should consider diverting two-wheelers during peak hours and encourage cyclists to walk through crosswalks.</p></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"206 ","pages":"Article 107716"},"PeriodicalIF":5.7,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141629824","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":"Safety assessment for autonomous vehicles: A reference driver model for highway merging scenarios","authors":"Cheng Wang ,&nbsp;Fengwei Guo ,&nbsp;Shuaijie Zhao ,&nbsp;Zhongpan Zhu ,&nbsp;Yuxin Zhang","doi":"10.1016/j.aap.2024.107710","DOIUrl":"10.1016/j.aap.2024.107710","url":null,"abstract":"<div><p>Driver models are crucial for the safety assessment of autonomous vehicles (AVs) because of their role as reference models. Specifically, an AV is expected to achieve at least the same level of safety performance as a careful and competent driver model. To make this comparison possible, quantitative modeling of careful and competent driver models is essential. Thus, the UNECE Regulation No. 157 proposes two driver models as benchmarks for AVs, enabling safety assessment of AV longitudinal behaviors. However, these two driver models are unable to be applied in non-car-following scenarios, limiting their applications in scenarios such as highway merging. To this end, we propose a careful and competent driver model for highway merging (CCDM2) scenarios using interpretable reinforcement learning-based decision-making and safety constraint control. We compare our model’s safe driving capabilities with human drivers in challenging merging scenarios and demonstrate the ”careful” and ”competent” characteristics of our model while ensuring its interpretability. The results indicate the model’s capability to handle merging scenarios with even better safety performance than human drivers. This model is of great value for AV safety assessment in merging scenarios and contributes to future reference driver models to be included in AV safety regulations.</p></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"206 ","pages":"Article 107710"},"PeriodicalIF":5.7,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141629825","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":"Estimating the effectiveness of marked sidewalks: An application of the spatial causality approach","authors":"I. Gede Brawiswa Putra ,&nbsp;Pei-Fen Kuo ,&nbsp;Dominique Lord","doi":"10.1016/j.aap.2024.107699","DOIUrl":"10.1016/j.aap.2024.107699","url":null,"abstract":"<div><p>Various safety enhancements and policies have been proposed to enhance pedestrian safety and minimize vehicle–pedestrian accidents. A relatively recent approach involves marked sidewalks delineated by painted pathways, particularly in Asia’s crowded urban centers, offering a cost-effective and space-efficient alternative to traditional paved sidewalks. While this measure has garnered interest, few studies have rigorously evaluated its effectiveness. Current before-after studies often use correlation-based approaches like regression, lacking effective consideration of causal relationships and confounding variables. Moreover, spatial heterogeneity in crash data is frequently overlooked during causal inference analyses, potentially leading to inaccurate estimations.</p><p>This study introduces a geographically weighted difference-in-difference (GWDID) method to address these gaps and estimate the safety impact of marked sidewalks. This approach considers spatial heterogeneity within the dataset in the spatial causal inference framework, providing a more nuanced understanding of the intervention’s effects. The simplicity of the modeling process makes it applicable to various study designs relying solely on pre- and post-exposure outcome measurements. Conventional DIDs and Spatial Lag-DID models were used for comparison.</p><p>The dataset we utilized included a total of 13,641 pedestrian crashes across Taipei City, Taiwan. Then the crash point data was transformed into continuous probability values to determine the crash risk on each road segment using network kernel density estimation (NKDE). The treatment group comprised 1,407 road segments with marked sidewalks, while the control group comprised 3,097 segments with similar road widths. The pre-development program period was in 2017, and the post-development period was in 2020.</p><p>Results showed that the GWDID model outperformed the spatial lag DID and traditional DID models. As a local causality model, it illustrated spatial heterogeneity in installing marked sidewalks. The program significantly reduced pedestrian crash risk in 43% of the total road segments in the treatment group. The coefficient distribution map revealed a range from –22.327 to 2.600, with over 95% of the area yielding negative values, indicating reduced crash risk after installing marked sidewalks. Notably, the impact of crash risk reduction increased from rural to urban areas, emphasizing the importance of considering spatial heterogeneity in transportation safety policy assessments.</p></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"206 ","pages":"Article 107699"},"PeriodicalIF":5.7,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141623517","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}