Traffic Injury Prevention最新文献

{"title":"Interaction between multiple convertible child restraint systems and pediatric occupants in oblique impacts","authors":"Jalaj Maheshwari ,&nbsp;Declan A. Patton","doi":"10.1080/15389588.2024.2402929","DOIUrl":"10.1080/15389588.2024.2402929","url":null,"abstract":"<div><h3>Objectives</h3><div>To assess the interaction of multiple rearward-facing (RF) and forward-facing (FF) CRS restrained pediatric occupants on their kinetics in oblique impacts.</div></div><div><h3>Methods</h3><div>A Q3s and a Q1.5 ATD were restrained in 2 CRSs of varying widths—standard (503mm) and slim-fit (425mm)—in the 2 rear outboard seats of a 2023 compact sedan rigidized rear seat bench. A surrogate door structure was mounted at the left outboard location. The Q1.5 was seated in an RF configuration, and the Q3s was seated in RF or FF configurations across tests. The ATDs were restrained as follows: (1) both ATDs in standard CRSs and (2) both ATDs in slim-fit CRSs, switching between the outboard seats for a total of 8 conditions. The condition with the highest head kinetic metrics from these tests was reproduced in a ninth test with the rear seat’s center armrest lowered between CRSs. The entire environment was subjected to an oblique impact at 60° using the FMVSS 213 impact pulse.</div></div><div><h3>Results</h3><div>The Q3s’ head contacted the nearby CRS shell when seated farside. When seated nearside, the Q3s’ head contacted the surrogate door structure in 1 of 4 conditions. The Q1.5’s head contacted the nearby CRS in 2 of 4 conditions when seated farside. The Q3s when seated RF had higher HIC15 and head 3ms clip acceleration (H_3ms), regardless of farside or nearside position. When seated farside, upper neck tensile force (F_z) for the Q3s in FF configuration (2,317.4 and 2,077.9 N) was higher than that in RF configuration (1,850.8 and 1,802.8 N). When seated nearside, the same in FF configuration (701.3 and 1,029.4 N) was lower than that in RF configuration (997.6 and 1,261.7 N). Repeating the condition with the highest head kinetic metrics (HIC15 = 1246; H_3ms = 114.4 <em>g</em>) but lowering the center armrest between the CRSs resulted in lower head kinetic metrics (HIC15 = 916, H_3ms = 93.5 <em>g</em>).</div></div><div><h3>Conclusions</h3><div>In most cases, the farside seated ATD’s head contacted the nearside CRS shell, resulting in elevated injury metric numbers and higher loading in both CRS types. The nearside ATD did not experience detrimental effects of the interaction with the farside occupant and CRS.</div></div>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":"25 1","pages":"Pages S193-S199"},"PeriodicalIF":1.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142562816","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}

{"title":"Comparison of Waymo rider-only crash data to human benchmarks at 7.1 million miles","authors":"Kristofer D. Kusano ,&nbsp;John M. Scanlon ,&nbsp;Yin-Hsiu Chen ,&nbsp;Timothy L. McMurry ,&nbsp;Ruoshu Chen ,&nbsp;Tilia Gode ,&nbsp;Trent Victor","doi":"10.1080/15389588.2024.2380786","DOIUrl":"10.1080/15389588.2024.2380786","url":null,"abstract":"<div><h3>Objectives</h3><div>This article examines the safety performance of the Waymo Driver, an SAE level 4 automated driving system (ADS) used in a rider-only (RO) ride-hailing application without a human driver, either in the vehicle or remotely.</div></div><div><h3>Methods</h3><div>ADS crash data were derived from NHTSA’s Standing General Order (SGO) reporting over 7.14 million RO miles through the end of October 2023 in Phoenix, Arizona, San Francisco, California, and Los Angeles, California, and compared to human benchmarks from the literature.</div></div><div><h3>Results</h3><div>When considering all locations together, the <em>any injury reported</em> crashed vehicle rate was 0.6 incidents per million miles (IPMM) for the ADS vs. 2.80 IPMM for the human benchmark, an 80% reduction or a human crash rate that is 5 times higher than the ADS rate. <em>Police-reported</em> crashed vehicle rates for all locations together were 2.1 IPMM for the ADS vs. 4.68 IPMM for the human benchmark, a 55% reduction or a human crash rate that was 2.2 times higher than the ADS rate. <em>Police-reported</em> crashed vehicle rate reductions for the ADS were statistically significant when compared in San Francisco and Phoenix, as well as combined across all locations and the any-injury-reported reductions were statistically significant in San Francisco and in all locations. The <em>any property damage or injury</em> comparison had statistically significant decreases in 3 comparisons but also nonsignificant results in 3 other benchmarks. When excluding ADS crashes with a delta-V less than 1 mph (a measure of sensitivity to lower reporting threshold), about half of the ADS collisions were excluded, resulting in comparisons that showed a large statistically significant reduction in all comparisons except for one comparison from San Francisco.</div></div><div><h3>Conclusions</h3><div>The statistically significant reductions in <em>police-reported</em> and <em>any injury reported</em> crash rates indicate a promising positive safety impact of ADS. The direction and significance of comparisons in the <em>any property damage or injury</em> outcome group are inconclusive due to difficulties in estimating a matching human benchmark. More research is needed on defining <em>any property damage or injury</em> benchmarks with clear lower reporting thresholds to reduce the systematic uncertainty in the benchmark rates. Together, these crash rate results contribute to the continuous growth in confidence, together with other methodologies, in a safety case approach.</div></div>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":"25 1","pages":"Pages S66-S77"},"PeriodicalIF":1.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142562663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"How the cognitive load of simulated driving affects the brain dynamics underlying auditory attention","authors":"Barbara C. Banz ,&nbsp;Jia Wu ,&nbsp;Deepa R. Camenga ,&nbsp;Linda C. Mayes ,&nbsp;Michael J. Crowley ,&nbsp;Federico E. Vaca","doi":"10.1080/15389588.2024.2373950","DOIUrl":"10.1080/15389588.2024.2373950","url":null,"abstract":"<div><h3>Objective</h3><div>Distracted driving is a primary contributor to for motor vehicle crashes, the leading cause for injuries and fatalities for youth. Although attention and working memory clearly underlie driving abilities, few studies explore these functions on the brain-level under the cognitive load of driving. To understand the load driving has on auditory attention processing, we examined the differences in dynamic brain response to auditory stimuli during LOAD (while driving in a high-fidelity driving simulator) and No-LOAD conditions (seated in simulator, parked on the side of the road).</div></div><div><h3>Methods</h3><div>Twenty-seven young adult drivers (18–27 y/o; 15 = women) completed a Selective Auditory Attention Task during both a LOAD (driving) and No-LOAD condition in a ½ cab miniSim^® high-fidelity driving simulator. During the task, participants responded by pressing the volume control button on the steering wheel when a target tone was presented to a target ear. Electroencephalography-recorded event-related brain responses to the target tones were evaluated through alpha and theta oscillations for two response windows (early: 150–330ms; late: 350–540ms).</div></div><div><h3>Results</h3><div>During an early time window, we observed a significant interaction between attended/unattended and LOAD/No-LOAD theta power in the right frontal cortical region (<em>F</em>(1, 24)= 5.4, <em>p</em>=.03, partial <em>η</em>²=.18). During the later window, we observed a significant interaction between attended/unattended and LOAD/No-LOAD alpha response in the posterior cortical region (<em>F</em>(1, 24)=11.81, <em>p</em>=.002, partial <em>η</em>²=.15) and in the right temporal cortical region during the window (<em>F</em>(1, 24)=4.3, <em>p</em>=.05, partial <em>η</em>²=.33).</div></div><div><h3>Conclusions</h3><div>Our data provide insight into the demand that driving has on cognitive faculties and how dual task engagement may draw resources away from driving. We suggest future research directly incorporate vehicle control abilities into study design to understand how brain-based measures relate to driving behaviors.</div></div>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":"25 1","pages":"Pages S167-S174"},"PeriodicalIF":1.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142562666","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}

{"title":"Interactions between rearward-facing child restraint systems and the center console in frontal impact sled tests","authors":"D. A. Patton ,&nbsp;J. Maheshwari ,&nbsp;J. A. Mansfield ,&nbsp;K. B. Arbogast","doi":"10.1080/15389588.2024.2371522","DOIUrl":"10.1080/15389588.2024.2371522","url":null,"abstract":"<div><h3>Objective</h3><div>To quantify the head and chest injury metrics associated with a pediatric anthropomorphic test device (ATD) in rearward-facing infant child restraint system (CRS) models positioned directly behind a center console during frontal impact sled tests.</div></div><div><h3>Methods</h3><div>Sled tests using the Federal Motor Vehicle Safety Standard (FMVSS) 213 frontal crash pulse were performed. The test buck comprised a second row middle seat and center console from the same 2023 model mid-size SUV spaced as per the in-vehicle relative dimensions, a force plate covered with an automotive floor mat, a post-mounted shoulder belt simulating the in-vehicle roof-mounted seatbelt and an array of high-speed cameras. The 12-month-old Child Restraint/Air Bag Interaction (CRABI-12) ATD was seated in one of two rearward-facing infant CRS models (model A, rigid lower anchors; model B, flexible lower anchors), which was installed with either the base (support leg or no support leg; attached using lower anchors or the seatbelt) or without the base (attached using the European or US belt path). Conductive foil was attached to the rear surface of the center console and to the shell of the CRS and/or base to quantify contact. The vehicle seat was replaced every second test and the center console was replaced when damaged.</div></div><div><h3>Results</h3><div>For sled tests of the CRS models with a base attached using lower anchors, there was no contact of the CRS with the center console when the support leg was used, and all head and chest injury metrics were reduced compared to the tests of CRS with no support leg. However, there was contact between the CRS and the center console when the base of the CRS models was attached using the seatbelt, which typically increased head and chest injury metrics compared to the lower anchor attachment method. For CRS model B with the base attached using either the lower anchors or the seatbelt but no support leg, head acceleration 3 ms clip exceeded the injury assessment reference value (IARV) of 80 <em>g</em>. All tests resulted in HIC36 values below the IARV of 1000. The tests of the CRS models without a base using the European belt path did not result in contact and had the lowest head and chest injury metrics of all tests, which were all below IARVs. For the tests of the CRS models with the base attached using the seatbelt and tests using the US belt path, chest acceleration 3 ms clip values exceeded the IARV of 60 <em>g</em>. Peak normal support leg reaction forces in this study ranged from 3.6 to 4.3 kN.</div></div><div><h3>Conclusions</h3><div>The rearward-facing CRS models with a base and a support leg attached using lower anchors, or without a base using the European belt path, resulted in the lowest head and chest injury metrics due to not contacting the center console.</div></div>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":"25 1","pages":"Pages S200-S207"},"PeriodicalIF":1.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142562771","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}

{"title":"Self-reported drink driving, enforcement, crashes, and crash reporting: A 6-country comparison","authors":"Ted R. Miller ,&nbsp;Deborah A. Fisher ,&nbsp;Joel W. Grube ,&nbsp;Bruce A. Lawrence ,&nbsp;Christopher L. Ringwalt ,&nbsp;Tom Achoki","doi":"10.1080/15389588.2024.2387709","DOIUrl":"10.1080/15389588.2024.2387709","url":null,"abstract":"<div><h3>Objective</h3><div>The objective of this study was to compare drink driving and related road safety issues in 2 urban areas of 6 countries and develop an equation for estimating the rate of crash underreporting to the police in urban areas of countries that lack this information.</div></div><div><h3>Methods</h3><div>This study is a secondary analysis of 1 to 2 waves of surveys in pairs of matched medium-sized cities in Belgium, Brazil, China, Mexico, South Africa, and Ohio, United States; the surveys supported evaluation of local alcohol harm reduction efforts. Data were from 2017 to 2019 except 2023 for Mexico. Mailed surveys in Ohio and household interviews elsewhere of quota samples matched to census data yielded 23,240 completed interviews. Relevant questions covered drinking, driving under the influence of alcohol (DUI), DUI enforcement, and, except in South Africa, road crashes. GLM regression provided an equation for estimating police reporting rates of urban injury and no-injury crashes from a country’s purchasing-power parity–adjusted gross domestic product (GDP) per capita.</div></div><div><h3>Results</h3><div>The percentage of drivers driving unlicensed was 30% in Mexico and South Africa, 15% in Brazil, 8% in China, and &lt;1% elsewhere. Among adults who both drove and drank, self-reported urban DUI rates ranged from 12% in China to 53% in South Africa, with 4 countries between 18% and 26%. Among those reporting DUI, the percentage stopped by police for doing so was 14% in Belgium, 15% in Brazil, 25% in China, 31% in Mexico, 45% in South Africa, and only 3% in Ohio. The surveys yielded data on 380 urban crashes. Past-year crash involvement was 2% to 3% in Belgium and China and 5% to 6% elsewhere. The 10% injury rate in Ohio crashes was significantly below the 24% to 35% rates elsewhere. Injury crashes were almost universally reported except in Brazil (60% reported). Only 49% to 56% of non-injury crashes were reported, except in Ohio (73%). Perceived alcohol-involved crash rates of 18% to 19% in Belgium and Ohio were significantly lower than the 32% reported in Brazil, 41% in China, and 57% in Mexico. In the regression, GDP per capita and injury involvement were positively associated with police crash reporting.</div></div><div><h3>Conclusions</h3><div>Our equation more closely approximates urban police crash reporting rates than prior studies that assumed that they matched U.S. data. DUI enforcement is weak/ineffective in urban Ohio. With suggested adjustments, our survey questions should be usable in other international road safety and DUI studies.</div></div>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":"25 1","pages":"Pages S86-S93"},"PeriodicalIF":1.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142570072","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}

{"title":"Estimation and modeling of pedestrian dilemma zone at uncontrolled intersections under mixed traffic conditions.","authors":"Govinda Lalam, Ravishankar K V R","doi":"10.1080/15389588.2024.2409382","DOIUrl":"https://doi.org/10.1080/15389588.2024.2409382","url":null,"abstract":"<p><strong>Objectives: </strong>Pedestrian gap acceptance (PGA) theory is the basic concept for pedestrian dilemma zone (PDZ) analysis and modeling and their gap acceptance behavior depends on dilemma behavior also. Uncontrolled intersections are one of the major locations where pedestrians have more dilemma and there is a possibility of an interaction between the pedestrian and vehicle due to the incorrect decision taken by the pedestrian when the vehicle lies within the limits of PDZ. Elimination and modeling of spatial boundaries of pedestrian dilemma stage improve the PGA.</p><p><strong>Methods: </strong>The present study is intended to quantify and model the pedestrian dilemma zone (PDZ) boundaries at uncontrolled X-intersections under mixed traffic conditions. Video data were collected from four four-legged uncontrolled intersections in India. Pedestrian and vehicle information was extracted using DataFromSky software and manually from video. The Cumulative Gap Distribution (GCD) and Support Vector Machine (SVM) methods were used to estimate the boundaries of PDZ and developed a binary logistic regression model to estimate the PDZ boundary limits.</p><p><strong>Results: </strong>The lower boundary limits of PDZ using GCD and SVM methods are 9.0 m and 6.0, respectively, and the upper boundary limits of PDZ using GCD and SVM methods are 16.5 and 18.5 m, respectively. The GCD method overestimated the lower limit and underestimated the upper limit compared with the SVM method. The binary logistic regression model results confirmed that pedestrian age, gender and crossing speed have a negative correlation and location of pedestrian crossing, vehicle type, and approaching speed have a positive correlation with the boundary limits of PDZ.</p><p><strong>Conclusions: </strong>From the present study, it is concluded that SVM better estimated the PDZ boundary limits with the largest margin compared to the GCD method. It is concluded that the boundary limits shift away from the intersection in the case of female and old-age pedestrians compared to male and young-age pedestrians, respectively. The size benefit in the case of 2Ws is the reason for shifting the PDZ boundary limits close to the crosswalk. The lower approaching speeds of the vehicles at uncontrolled intersections are the reason for pedestrians accept the gap at shorter distances.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-9"},"PeriodicalIF":1.6,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481010","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}

{"title":"Five-year trend analysis of drug use among individuals 16 years of age and older injured in non-fatal motor vehicle crashes in the US.","authors":"Nae Y Won, Kelly K Gurka, Linda B Cottler","doi":"10.1080/15389588.2024.2405038","DOIUrl":"https://doi.org/10.1080/15389588.2024.2405038","url":null,"abstract":"<p><strong>Objective: </strong>To examine the prevalence of drug use among individuals (age 16+) injured in non-fatal motor vehicle crashes (MVCs) from 2019 to 2023 and assess regional differences based on US Census regions (i.e., West, Midwest, Northeast, and South), and thereby contribute to a comprehensive understanding of drug-related MVCs.</p><p><strong>Methods: </strong>We examined emergency medical services data from 19 US states (January 2019 to December 2023) to determine the annual mean drug use prevalence among individuals (age 16+) injured in non-fatal MVCs. Differences in drug use prevalence were assessed using ANOVA with the Tukey-Kramer test for year-to-year comparisons. Adjusted Poisson regression models with random effect for states were used to compare trends to the baseline (i.e., 2019) and to assess regional differences.</p><p><strong>Results: </strong>Among individuals (age 16+) injured in non-fatal MVCs, 62,310 had reported drug use. ANOVA results showed significant year-to-year differences in the prevalence of drug use among individuals injured in non-fatal MVCs, with an increase from 2019 to 2020 and a subsequent decrease from 2020 to 2023 (<i>p</i> < 0.05). Compared to the baseline year of 2019, the prevalence in 2020 was 1.34 times (95% confidence interval [CI]: 1.12, 1.61) the prevalence in 2019. The prevalence in 2022 and 2023 were similar to the 2019 prevalence. Although no significant associations were found between US regions and the overall mean prevalence from 2019 to 2023; there was a difference in the average annual rate of change in prevalence by region, with a 4.0% lower rate in the Midwest compared to the Northeast (<i>p</i> < 0.001). This signifies a need to monitor future trends for potential regional differences.</p><p><strong>Conclusions: </strong>Drug use prevalence among individuals (age 16+) injured in non-fatal MVCs increased from 2019 to 2020; then decreased to levels reflecting baseline prevalence in 2019; with no significant regional differences in the overall mean crash-related drug use prevalence. These findings highlight the need for continuous surveillance across the US over an extended period. They also underscore the potential impact of environmental risk factors, such as the COVID-19 pandemic, and the necessity to monitor how drug use prevalence related to non-fatal MVCs changes in the coming years.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-8"},"PeriodicalIF":1.6,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481011","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}

{"title":"Development of hazard prediction test and interventions for two-wheeled electric vehicle riders in China.","authors":"Yanqun Yang, Xinli Wu, Yang Feng, Said M Easa, Xinyi Zheng","doi":"10.1080/15389588.2024.2410417","DOIUrl":"https://doi.org/10.1080/15389588.2024.2410417","url":null,"abstract":"<p><strong>Objective: </strong>This paper aimed to develop a hazard prediction test and enhance two-wheeled electric vehicle (TWEV) riders' hazard perception and prediction capabilities <i>via</i> interventions by executing two distinct studies. Study 1 aimed to develop and validate a hazard prediction test. Study 2 evaluated the efficacy of two interventions, self-commentary and what happens next (WHN), integrating expert commentary.</p><p><strong>Method: </strong>For Study 1, a video-based hazard prediction test was developed through video recording and clipping, with participants categorized into high and low prediction ability groups for experimentation. Data analysis employed the receiver operating characteristic (ROC) curve. Study 2 categorized participants into four groups: self-commentary with licenses (SCL), self-commentary without licenses (SCNL), WHN with licenses (WHNL), and WHN without licenses (WHNNL), for conducting a one-week intervention experiment. Data collected from participants' pre-intervention, post-intervention, and aftereffect tests were subjected to repeated measures analysis of variance (ANOVA).</p><p><strong>Results: </strong>Analysis of the ROC curve indicated the test can distinguish the riders with different hazard prediction levels. ANOVA results demonstrated that the measurement time had a significant positive effect on scores (<i>p</i> < 0.001). Both interventions significantly improved hazard prediction ability (<i>p</i> < 0.05), and the effect persisted one week after administration. The effect of the WHN intervention was significantly greater than the self-commentary method across all time points.</p><p><strong>Conclusion: </strong>The hazard prediction test developed in this study could assess riders' hazard prediction ability, with the identified interventions demonstrating effectiveness in enhancing this ability. These findings suggested potential application in future qualification tests for TWEV riders, contributing to enhanced traffic safety awareness among TWEV riders in China, thus advancing overall traffic safety.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-10"},"PeriodicalIF":1.6,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481009","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}

{"title":"Quantifying perceived risk in driving: A Monte Carlo approach for obstacle avoidance.","authors":"Zhen Yang, Zhe Gong, Yimei Qin, Ruiping Zheng","doi":"10.1080/15389588.2024.2405647","DOIUrl":"https://doi.org/10.1080/15389588.2024.2405647","url":null,"abstract":"<p><strong>Objective: </strong>This study aims to develop a model for quantifying perceived risk in obstacle avoidance, emphasizing how drivers' perceived risk characteristics influence their driving decisions. The research addresses the lack of attention given to modeling risk from the perspective of drivers' risk perceptions.</p><p><strong>Methods: </strong>Monte Carlo methods are employed to account for the uncertainties and complexities of driving behavior, restoring the probabilistic nature of risk. The proposed method quantifies perceived risk by incorporating drivers' fuzzy perceptions, enabling a quantitative evaluation during obstacle avoidance. A logit model is used to link perceived risk with driving decisions, identifying key factors influencing driver behavior in obstacle avoidance scenarios.</p><p><strong>Results: </strong>Experimental data revealed significant variations in vehicle trajectories and speed distributions due to differences in drivers' experience and proficiency. The perceived risk indicator (PRI) values for leftward bypasses were higher compared to rightward bypasses, and the receiver operating characteristic (ROC) curve confirmed the PRI's strong predictive ability with an area under the curve (AUC) of 0.820. The logit model showed that both PRI and speed significantly influenced the probability of choosing a rightward bypass, achieving 90% accuracy. Building on the model, the study predicted and visualized the probability of vehicles turning right to avoid obstacles at different positions and speeds within 200 m of the obstacle.</p><p><strong>Conclusions: </strong>The research offers a framework for traffic professionals to understand driver-perceived risk and decision-making mechanisms. This understanding is beneficial for improving traffic safety and highlights the importance of considering drivers' risk perceptions in modeling driving behavior.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-9"},"PeriodicalIF":1.6,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481016","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}

{"title":"Validation of a generic finite element vehicle buck model for near-side crashes.","authors":"Casey G Costa, Karan Devane, Joel D Stitzel, Johan Iraeus, Ashley A Weaver","doi":"10.1080/15389588.2024.2403717","DOIUrl":"https://doi.org/10.1080/15389588.2024.2403717","url":null,"abstract":"<p><strong>Objective: </strong>Finite element (FE) reconstructions of motor vehicle crashes using human body models are effective tools for developing a better understanding of occupant kinematics and injuries in real-world lateral crash conditions, but current near-side reconstruction methods are limited by the paucity of full-scale FE vehicle models. The objective of this study was to validate a generic vehicle model equipped with left-side airbags and intrusion capability by simulating a series of near-side crash tests for a range of vehicles and assessing model accuracy using objective evaluation methods.</p><p><strong>Methods: </strong>Moving deformable barrier crash tests were reconstructed for five common vehicle classifications (compact passenger, mid-size passenger, sport utility vehicle, pickup truck, and van) using an updated version of a previously developed simplified vehicle model. Unknown vehicle and intrusion properties (pretensioner force, seatback airbag pressure, curtain airbag pressure, door panel stiffness, ratio of dynamic-to-static intrusion, intrusion velocity, and intrusion scaling factor) were estimated by parameterizing them across 224 simulations per crash test using a Latin hypercube design of experiments. Model accuracy was assessed for 13 anthropomorphic test device signals using the Correlation and Analysis (CORA) objective rating method and injury metric comparisons.</p><p><strong>Results: </strong>Maximum ratings of 0.69, 0.67, 0.52, 0.52, and 0.62 were achieved for the compact passenger, midsize passenger, sport utility vehicle, pickup truck, and van classifications, respectively. On average, the abdomen displayed the most accurate behavior (0.51 ± 0.12), followed by the thorax (0.50 ± 0.10) and head (0.50 ± 0.07). The pelvis displayed the least accurate behavior (0.46 ± 0.18) of any region. Reconstructions overpraedicted injury metrics in all cases.</p><p><strong>Conclusions: </strong>All vehicles achieved \"fair\" biofidelity ratings and the compact passenger and midsize passenger vehicles achieved \"good\" biofidelity ratings, validating them for kinematic evaluations with vehicle-to-vehicle nearside crash reconstructions. Regression models were developed for injuries and CORA ratings and can be used to optimize vehicle parameters in future studies.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-11"},"PeriodicalIF":1.6,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481019","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}