Accident; analysis and prevention最新文献

{"title":"Driving against the clock: Investigating the impacts of time pressure on taxi and non-professional drivers’ safety and compliance","authors":"Qinaat Hussain ,&nbsp;Wael K.M. Alhajyaseen","doi":"10.1016/j.aap.2024.107864","DOIUrl":"10.1016/j.aap.2024.107864","url":null,"abstract":"<div><div>Drivers often encounter time pressure, which can lead to riskier driving habits, decreased safety margins, and a higher chance of accidents. Given that taxi drivers frequently experience these conditions, this study examines how time pressure impacts the driving behaviors of both taxi and non-professional drivers. In this regard, a driving simulator experiment was carried out to assess the driving behaviors of both groups under time pressure. The simulation drive included different scenarios such as a stop sign, a pedestrian crosswalk, four intersections, a school zone, a slow bus and a drop-off location. The study recruited 55 taxi drivers and 55 non-professional drivers to take part in the experiment. Each participant completed the simulation drive twice, with the second drive conducted after they were informed that a reward would be given for finishing the trip more quickly. The findings reveal that drivers exhibited significantly riskier behaviors under time pressure, including higher speeds and reduced adherence to traffic rules. When comparing both groups, non-professional drivers displayed higher speeds and riskier behaviors across various scenarios, whereas taxi drivers were more likely to commit violations associated with drop-offs. These findings call for targeted awareness campaigns and stricter enforcement to reduce risky behaviors under time pressure. Flexible scheduling for non-professional drivers and incentive programs for taxi drivers can further promote safer practices. Policymakers can use these insights to design strategies that address the risks associated with time pressure.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"210 ","pages":"Article 107864"},"PeriodicalIF":5.7,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723794","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":"Spatiotemporal analysis of roadway terrains impact on large truck driver injury severity outcomes using random parameters with heterogeneity in means and variances approach","authors":"Muhammad Faisal Habib ,&nbsp;Nawaf Alnawmasi ,&nbsp;Diomo Motuba ,&nbsp;Ying Huang","doi":"10.1016/j.aap.2024.107849","DOIUrl":"10.1016/j.aap.2024.107849","url":null,"abstract":"<div><div>This study employs a partially temporally constrained modeling approach to examine spatiotemporal variations in driver injury severity in single-vehicle large truck crashes across different terrains in California, allowing for a nuanced understanding of how specific factors influencing injury outcomes may change over time. Utilizing crash data from January 1st, 2015, to December 31st, 2017, obtained from the Highway Safety Information System, this study categorizes terrains as flat, rolling, and mountainous terrain and employs a random parameter multinomial logit model with heterogeneity in means and variance to account for potential heterogeneity in crash injury outcomes. This approach helps understand how different terrains influence injury severities while allowing for parameter variability across observations. The analysis is further enriched by likelihood ratio tests to verify the stability and temporal transferability of the model estimates across different terrains and years. Notably, the study identifies truck overturning as the first and second event in a crash as a consistent parameter influencing injury severity across all years, emphasizing its importance regardless of terrain or time in single-vehicle large truck crashes. Furthermore, this study takes into account a wide range of variables, including driver characteristics, crash attributes, roadway characteristics, vehicle features, and environmental and temporal aspects. The findings highlight the importance of terrain-specific elements in traffic safety assessments and the need for focused measures to reduce serious injuries in truck crashes. The out-of-sample simulation revealed a significant increase in minor and severe injuries when flat terrain parameters were replaced with those from rolling or mountainous terrains. This research not only contributes to the existing literature by detailing the dynamics of injury severity in single-vehicle large truck crashes but also announces the utility of partially temporally constrained models in enhancing traffic safety management strategies.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"210 ","pages":"Article 107849"},"PeriodicalIF":5.7,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723768","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":"Evaluating the safety impact of mid-block pedestrian signals (MPS)","authors":"Md Jamil Ahsan,&nbsp;Mohamed Abdel-Aty,&nbsp;Ahmed S. Abdelrahman","doi":"10.1016/j.aap.2024.107847","DOIUrl":"10.1016/j.aap.2024.107847","url":null,"abstract":"<div><div>The Florida Department of Transportation (FDOT) has recently started implementing a new signal system at mid-blocks called Mid-block Pedestrian Signals (MPS). This study aims to evaluate the effectiveness of these newly implemented MPSs. A total of 260 h of video data were collected from five locations across Florida, with 130 h recorded before MPS installation and 130 h after installation, including both weekdays and weekends. State-of-the-art computer vision technology was employed to detect and track various road users. A random parameters multinomial logit model with heterogeneity in the means was implemented to assess safety of vehicle–pedestrian interaction by three conflict categories: No Conflict, Moderate Conflict, and Serious Conflict. Relative-Time-to-Collision (RTTC) values were utilized to classify these level of conflicts. The analysis demonstrates that the presence of MPS significantly enhances safety outcomes by increasing the likelihood of avoiding conflicts and reducing the probabilities of both moderate and serious conflicts. Key factors influencing conflict probabilities were identified, including pedestrian and vehicle counts, average leading vehicle speed, standard deviation of leading vehicle speeds, and land-use mix, all of which increase the probability of serious conflicts. Interestingly, the analysis identified three significant interaction variables with MPS: average leading vehicle speed, standard deviation of leading vehicle speeds, and land-use mix. While these factors individually had a higher probability of leading to serious conflicts, the presence of MPS effectively mitigates these risks by moderating their adverse effects, increasing the likelihood of no conflicts. These results underscore the importance of MPS as an effective measure to improve safety at mid-block crossings.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"210 ","pages":"Article 107847"},"PeriodicalIF":5.7,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723767","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":"Investigating streetscape environmental characteristics associated with road traffic crashes using street view imagery and computer vision","authors":"Han Yue","doi":"10.1016/j.aap.2024.107851","DOIUrl":"10.1016/j.aap.2024.107851","url":null,"abstract":"<div><div>Examining the relationship between streetscape features and road traffic crashes is vital for enhancing roadway safety. Traditional field surveys are often inefficient and lack comprehensive spatial coverage. Leveraging street view images (SVIs) and deep learning techniques provides a cost-effective alternative for extracting streetscape features. However, prior studies often rely solely on semantic segmentation, overlooking distinctions in feature shapes and contours. This study addresses these limitations by combining semantic segmentation and object detection networks to comprehensively measure streetscape features from Baidu SVIs. Semantic segmentation identifies pixel-level proportions of features such as roads, sidewalks, buildings, fences, trees, and grass, while object detection captures discrete elements like vehicles, pedestrians, and traffic lights. Zero-inflated negative binomial regression models are employed to analyze the impact of these features on three crash types: vehicle-vehicle (VCV), vehicle–pedestrian (VCP), and single-vehicle crashes (SVC). Results show that incorporating streetscape features from combined deep learning methods significantly improves crash prediction. Vehicles have a significant impact on VCV and SVC crashes, whereas pedestrians predominantly affect VCP crashes. Road surfaces, sidewalks, and plants are associated with increased crash risks, while buildings and trees correlate with reduced vehicle crash frequencies. This study highlights the advantages of integrating semantic segmentation and object detection for streetscape analysis and underscores the critical role of environmental characteristics in road traffic crashes. The findings provide actionable insights for urban planning and traffic safety strategies.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"210 ","pages":"Article 107851"},"PeriodicalIF":5.7,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142708947","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":"An emergency operation strategy and motion planning method for autonomous vehicle in emergency scenarios","authors":"Tianyang Gong ,&nbsp;Xiumin Yu ,&nbsp;Qunli Zhang ,&nbsp;Zilin Feng ,&nbsp;Shichun Yang ,&nbsp;Yaoguang Cao ,&nbsp;Jingyun Xu ,&nbsp;Xinjie Feng ,&nbsp;Zhaowen Pang ,&nbsp;Yu Wang ,&nbsp;Peng Wang","doi":"10.1016/j.aap.2024.107842","DOIUrl":"10.1016/j.aap.2024.107842","url":null,"abstract":"<div><div>Ensuring driving operational safety in emergency scenarios is paramount for autonomous vehicles to prevent accidents, particularly when vehicle motion completely depends on autonomous systems. Numerous factors must be evaluated when designing emergency collision avoidance strategies for critical situations, such as trajectory feasibility, vehicle motion stability, and driver comfort. Therefore, this study proposes a framework for emergency operation that uses collision-free area calculations to inform maneuver decisions and facilitate collision avoidance trajectory planning, preventing vehicle collisions. In case of danger, the emergency maneuver decision module evaluates the safety level and selects safety terminal state by considering a pre-specified cluster of candidate maneuvers before generating trajectories. This process avoids infeasible trajectories and selects maneuvers for greater driver comfort when available. Subsequently, the dynamic trajectory planning module converts the collision-free area into mixed-integer constraints, utilizing time-varying Nonlinear Model Predictive Control (NMPC) for trajectory planning and ensuring vehicle motion stability by integrating dynamic and collision-free constraints throughout the motion planning process. Eventually, simulations and field testing validate the framework’s effectiveness, mitigating collisions in emergency scenarios with prompt and safe operations. The framework is designed to function autonomously, independent of the intelligent driving system, engaging only during risk events and restoring control to the driver or the intelligent system after the event.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"210 ","pages":"Article 107842"},"PeriodicalIF":5.7,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142708936","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":"Assessment of the collision risk on the road around schools during morning peak period","authors":"Xiaojian Hu ,&nbsp;Haoran Deng ,&nbsp;Huasheng Liu ,&nbsp;Jiayi Zhou ,&nbsp;Hongyu Liang ,&nbsp;Long Chen ,&nbsp;Li Zhang","doi":"10.1016/j.aap.2024.107854","DOIUrl":"10.1016/j.aap.2024.107854","url":null,"abstract":"<div><div>Road traffic injury is a leading cause of death among pupils worldwide, particularly around primary schools during rush hours, where heavy traffic, frequent parking, and unpredictable patterns increase accident risk. To mitigate these risks, this study employs the peak-over-threshold method with the generalized pareto distribution to evaluate the spatial–temporal collision risk near primary schools during rush hours. Specifically, the research quantifies collision risks spatially across different road segments (upstream, midstream, and downstream) and lanes (outside, middle, and inside). Temporally, it assesses risks during vehicle gathering, peak vehicle concentration, and vehicle dissipation phases. Results show that collision risk decreases from upstream to downstream but increases from the outside lane to the inside lane. Moreover, collision risks are highest in the middle and outside lanes during the gathering and peak periods in upstream and midstream sections, and in the middle lanes during the dissipation phase. These findings recommend adding parking spaces, minimizing lane changes, reducing speed limits in upstream and midstream, and increasing speed limits in downstream and inside lanes. These measures aim to improve road traffic management policies around schools.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"210 ","pages":"Article 107854"},"PeriodicalIF":5.7,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142708941","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":"Gender disparities in rural motorcycle accidents: A neural network analysis of travel behavior impact","authors":"Ittirit Mohamad","doi":"10.1016/j.aap.2024.107840","DOIUrl":"10.1016/j.aap.2024.107840","url":null,"abstract":"<div><div>Rural road accidents involving motorcycle riders present a formidable challenge to road safety globally. This study offers a comprehensive gender-based comparative analysis of rural road accidents among motorcycle riders, aimed at illuminating factors contributing to accidents and discerning potential gender disparities in accident rates and severity. Employing a sophisticated Neural Network approach, the research delves into the intricate relationship between various variables and accident outcomes, with a specific emphasis on identifying gender-specific patterns. For female riders, the ANN model demonstrates impressive overall accuracy (CA) of 92 %, indicating its capability to correctly classify accident outcomes. Precision, which measures the model’s ability to avoid false positives, stands at a commendable 90.8 %. Moreover, the model exhibits high recall (92 %) and F1 score (88.4 %), indicating its effectiveness in identifying both fatal and non-fatal accidents among female riders. Additionally, the Matthews Correlation Coefficient (MCC) of 0.132 suggests a moderate level of agreement between the predicted and actual outcomes. Upon further examination, it is evident that the model performs exceptionally well in predicting non-fatal accidents for female riders, achieving a precision, recall, and F1 score of 92 %, 99.9 %, and 95.8 %, respectively. However, its performance in predicting fatalities is relatively lower, with a precision of 75.6 % and recall of 2.6 %, resulting in a lower F1 score of 5.0 %. Despite this disparity, the MCC remains consistent at 0.132, indicating a balanced performance across both classes. The findings reveal valuable insights for policymakers and road safety practitioners, providing avenues for the development of targeted interventions and the enhancement of safety measures for motorcycle riders on rural roads. By addressing the gap in understanding gender-related differences in travel habits and accident risks, this research contributes to ongoing efforts to mitigate the impact of road accidents and promote safer travel environments for all road users.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"210 ","pages":"Article 107840"},"PeriodicalIF":5.7,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142695121","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":"One-pedal or two-pedal: Does the regenerative braking system improve driving safety?","authors":"Jun Ma ,&nbsp;Xu Zhang ,&nbsp;Wenxia Xu ,&nbsp;Jiateng Li ,&nbsp;Zaiyan Gong ,&nbsp;Jingyi Zhao","doi":"10.1016/j.aap.2024.107832","DOIUrl":"10.1016/j.aap.2024.107832","url":null,"abstract":"<div><div>Electric vehicles equipped with regenerative braking systems provide drivers a new driving mode, the one-pedal mode, which enables drivers to accelerate and decelerate with the throttle alone. However, there is a lack of systematic research on driving behavior in one-pedal mode, and whether it actually enhances or reduces safety remains to be validated. A driving simulator was used to analyze driving behavior and safety in the one-pedal mode in situations with different urgency level, with the two-pedal mode (the traditional driving mode in internal combustion engine vehicles) serving as a comparative group. The driver’s perception times, initial and final throttle release times, throttle to brake transition times, maximum brake pedal forces, collision ratios, and time-to-collision (TTC) were measured under the lead vehicle decelerating at 0.1 g, 0.2 g, 0.5 g, 0.75 g, as well as uncertainty (decelerating at 0.2 g to 25 km/h, then decelerating at 0.75 g to 0), and under headways of 1.5 s and 2.5 s. Results showed: 1) The regenerative braking system did not affect driver perception and reaction of the lead vehicle braking event and drivers extended throttle release to avoid rapid speed drops when the lead vehicle braked slowly; 2) the one-pedal mode exhibited a longer throttle to brake transition time and increased uncertainty in timing of brake pedal application; 3) the one-pedal mode was safer than the two-pedal mode in low urgency situations but became unsafe in high urgency or uncertain situations due to delayed braking. The implications of this research include enhancing regenerative braking systems and developing forward collision warning systems.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"210 ","pages":"Article 107832"},"PeriodicalIF":5.7,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142692537","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":"Driving characteristics of static obstacle avoidance by drivers in mountain highway tunnels − A lateral safety distance judgement","authors":"Ying Chen ,&nbsp;Zhigang Du ,&nbsp;Jin Xu ,&nbsp;Shuang Luo","doi":"10.1016/j.aap.2024.107845","DOIUrl":"10.1016/j.aap.2024.107845","url":null,"abstract":"<div><div>Static obstacles (tunnel sidewalls, barricades, etc.) on the side of mountainous highways change the spatial range of the road during driving, restricting the driver’s freedom of driving while possibly triggering the driver’s shy away effect, which poses a specific potential safety hazard. To understand the characteristics of driving behaviour in mountain highway tunnels with different tunnel lengths and lateral obstacles, nine tunnels in Chongqing were selected for real-vehicle tests, and data on driving trajectories, speeds and other metrics were collected from 40 drivers. Analyse the driver’s need for lateral safety distance in different scenarios, defines the conditions and scope of the shy away effect, and establishes a multi-scenario “distance-trajectory” offset prediction model to adjust the offset under varying lateral environments by setting different facilities. The results show that drivers exhibit some avoidance behavior towards lateral static obstacles, but the extent of the shy-away effect varies based on tunnel length. By widening the lateral clearance to 0.925 m on the left side and 1.450 m on the right side of the road to meet the driver’s requirements for lateral safety distances, unreasonable avoidance behaviour can be reduced. Combined with the trajectory fluctuation characteristics of drivers in different tunnels, it is proposed to set up the traffic safety facilities in a manner more aligned with driver behavioral habits, with a place set up 110 m before the entrance of the short tunnel, two places set up in the medium tunnel at <em>L</em>/2 − 200 m, <em>L</em>/2 + 100 m (where <em>L</em> is the length of the tunnel), and three places for long tunnels at <em>L</em>/2 − 400 m, <em>L</em>/2 m, and <em>L</em>/2 + 300 m. For extra-long tunnels, facilities are to be set up in cycles of 500 m, 1000 m, and 1500 m intervals. In the cross-section where different drivers are prone to apparent trajectory offsets, a driving behavior prompt sign is added to help correct the driving trajectory.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"210 ","pages":"Article 107845"},"PeriodicalIF":5.7,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142685734","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":"Revisiting the correlation between simulated and field-observed conflicts using large-scale traffic reconstruction","authors":"Ao Qu,&nbsp;Cathy Wu","doi":"10.1016/j.aap.2024.107808","DOIUrl":"10.1016/j.aap.2024.107808","url":null,"abstract":"<div><div>Safety is a critical aspect of traffic systems. However, traditional crash data-based methods suffer from scalability and generalization issues. Although SSMs offer a proactive alternative for safety evaluation, their validation in simulated settings remains inconsistent, especially with emerging mobility technologies like autonomous driving. Our study critiques existing methodologies in SSM validation and introduces a novel framework integrating micro-level driver models with macro-level traffic states. This approach accounts for diverse external factors, including weather and geographical variations. Utilizing the Caltrans Performance Measurement System (PeMS) data, we conduct a large-scale analysis, merging traffic simulation with real-world data to extract SSMs and correlate them with crash statistics. Our results indicate a significant correlation between SSM counts and crash numbers but no clear trend with varying SSM thresholds. This suggests limitations in current public data for establishing robust links between simulated SSMs and real-world crashes. Our study highlights the need for improved data collection and simulation techniques, paving the way for more accurate and meaningful roadway safety analysis in the era of advanced mobility systems.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"210 ","pages":"Article 107808"},"PeriodicalIF":5.7,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142685735","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}