IATSS Research最新文献_第7页

Do mobile phone addiction, boredom proneness, and self-reported mindfulness predict pedestrian beliefs on distracted walking? 手机成瘾、无聊倾向和自我报告的正念能预测行人对分心步行的看法吗？

IF 3.2

IATSS Research Pub Date : 2023-10-01 DOI: 10.1016/j.iatssr.2023.08.001

Ankit Kumar Yadav , Nishant Mukund Pawar , Nagendra R. Velaga

{"title":"Do mobile phone addiction, boredom proneness, and self-reported mindfulness predict pedestrian beliefs on distracted walking?","authors":"Ankit Kumar Yadav , Nishant Mukund Pawar , Nagendra R. Velaga","doi":"10.1016/j.iatssr.2023.08.001","DOIUrl":"10.1016/j.iatssr.2023.08.001","url":null,"abstract":"<div><p>Pedestrian distraction is a major causal factor reported in pedestrian fatalities worldwide. Even though many observational studies and laboratory-based research have been conducted to examine the influence of pedestrian distraction on road safety, there is little understanding of the determinants of pedestrian beliefs that influence distracted walking behaviour. The present study examines the associations of pedestrian beliefs related to engagement in mobile phone distraction with psychological factors such as mobile phone addiction, boredom proneness, and mindfulness. Five hundred and fifty-one participants completed a questionnaire about their distraction beliefs (behavioural, normative, and control), mobile phone addiction, boredom proneness, and mindfulness. A Structural Equation Model (SEM) was developed to investigate the influence of mobile phone addiction, boredom proneness, and mindfulness on the three types of beliefs. Mobile phone addiction was significantly associated with behavioural beliefs (factor loading = 0.38) and control beliefs (factor loading = 0.23) but not with normative beliefs. Further, significant associations of boredom proneness were observed with all three types of beliefs: behavioural (factor loading = 0.15), normative (factor loading = 0.13), and control (factor loading = 0.15). Mindfulness showed significant relationships with normative beliefs (factor loading = 0.13) and control beliefs (factor loading = 0.11) but not with behavioural beliefs. This study is the first attempt to investigate the predictors of pedestrian distraction beliefs in the Indian context. The findings can assist the policymakers in understanding the pedestrian psychology behind their distracted walking behaviour.</p></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44064079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimating injury severity for motorized and non-motorized vehicle-involved crashes: Insights from random-parameter ordered probit model with heterogeneity in means and variances 估计机动车和非机动车碰撞的伤害严重程度:从均值和方差异质性的随机参数有序probit模型的见解

IF 3.2

IATSS Research Pub Date : 2023-10-01 DOI: 10.1016/j.iatssr.2023.09.003

Charles Atombo , Richard Fiifi Turkson , Maxwell Selase Akple

{"title":"Estimating injury severity for motorized and non-motorized vehicle-involved crashes: Insights from random-parameter ordered probit model with heterogeneity in means and variances","authors":"Charles Atombo , Richard Fiifi Turkson , Maxwell Selase Akple","doi":"10.1016/j.iatssr.2023.09.003","DOIUrl":"https://doi.org/10.1016/j.iatssr.2023.09.003","url":null,"abstract":"<div><p>The use of advanced models to investigate the determinants of injury severity outcomes for motorized and non-motorized-involved crashes are sparse. Therefore, random-parameter ordered probit models with heterogeneity in means and variances were developed to estimate factors affecting injury severity for motorized and non-motorized-involved crashes. Data covering a five-year period comprising 5976 and 634 cases for motorized and non-motorized-involved crashes respectively, was retrieved from the database of the National Road Safety Authority, State Insurance Company and Driver and Vehicle Licensing Authority in Ghana and used for model estimation. The results show that factors have varying significant effects on injury severity outcomes for motorized and non-motorized models. Marginal effects indicate that old age occupants, head-on-collision, exceeding a posted speed limit of 100 km/h and crash during weekends contributed greatly to the likelihood of severe injury outcomes in motorized model. Additionally, male non-motorists, non-use of helmet, rear-end collision, right-angle collision and crash on urban roads and during weekends, contributed significantly to the severe injury outcomes of non-motorized models. The direction of effect of the factors on severe injury was observed to have varying degrees of estimated coefficients. The difference in estimated coefficients shows that crashes involving non-motorized vehicles were more likely to result in severe injury compared to motorized vehicles. The motorized model had heterogeneity in means of five (5) random parameters observed, while the non-motorized model had heterogeneity in means of four (4) random parameters observed with two variables affecting the variance of three random parameters. Based on the results, various countermeasures were proposed to enhance road traffic safety.</p></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49722674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Crash severity analysis of single-vehicle rollover crashes in Namibia: A mixed logit approach 纳米比亚单车辆侧翻事故的严重程度分析:混合logit方法

IF 3.2

IATSS Research Pub Date : 2023-10-01 DOI: 10.1016/j.iatssr.2023.07.002

Cailis Bullard, Steven Jones, E. Adanu, Jun Liu

引用次数: 0

Pedestrian delay models for compliant & non-compliant behaviour at signalized midblock crosswalks under mixed traffic conditions 混合交通条件下信号化街区中间人行横道顺从与不服从行为的行人延迟模型

IF 3.2

IATSS Research Pub Date : 2023-10-01 DOI: 10.1016/j.iatssr.2023.08.003

Sandeep Manthirikul , Udit Jain , Sankaran Marisamynathan

{"title":"Pedestrian delay models for compliant & non-compliant behaviour at signalized midblock crosswalks under mixed traffic conditions","authors":"Sandeep Manthirikul , Udit Jain , Sankaran Marisamynathan","doi":"10.1016/j.iatssr.2023.08.003","DOIUrl":"10.1016/j.iatssr.2023.08.003","url":null,"abstract":"<div><p>The present study aimed to propose new pedestrian delay models for Signalized Midblock Crosswalks (SMC) for mixed traffic conditions. A detailed study of the literature revealed that most of the existing pedestrian delay models were developed for signalized intersections. Thus, the need for the study was established and data were collected at eight SMC in Hyderabad, one of the most densely populated metropolitan cities in India, using video-graphic technique. Two delay models were developed based on the compliance behaviour and non-compliance behaviour of pedestrians. Both models have two components i.e., waiting delay and crossing delay where the latter has two subset components i.e., frictional delay and pedestrian-vehicle interaction delay. The bidirectional effect (pedestrian-pedestrian interaction while crossing the road) of pedestrians was addressed as frictional delay while the non-compliance behaviour by pedestrians and vehicles was addressed as pedestrian-vehicle interaction delay in the present models. The waiting delay component was defined by modifying the Webster delay model for non-uniform pedestrian arrivals. The proposed delay models yielded an error of 5% and 7% for compliance behaviour model and non-compliance behaviour model respectively. The proposed models can be used for optimizing the signal timings and defining Level of Service (LOS) of facilities.</p></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44587372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How will Iranian behave in accepting autonomous vehicles? Studying moderating effect on autonomous vehicle acceptance model (AVAM) 伊朗将如何接受自动驾驶汽车?自动驾驶汽车接受模型(AVAM)的调节效应研究

IF 3.2

IATSS Research Pub Date : 2023-09-28 DOI: 10.1016/j.iatssr.2023.09.002

Hossein Naderi, Habibollah Nassiri

{"title":"How will Iranian behave in accepting autonomous vehicles? Studying moderating effect on autonomous vehicle acceptance model (AVAM)","authors":"Hossein Naderi, Habibollah Nassiri","doi":"10.1016/j.iatssr.2023.09.002","DOIUrl":"https://doi.org/10.1016/j.iatssr.2023.09.002","url":null,"abstract":"<div><p>The primary condition for society to benefit from autonomous vehicle (AV) advantages is the acceptance of these vehicles by people. In this regard, the factors which affect the acceptance of these vehicles among different countries should be identified. In previous studies, a major focus has been on developing autonomous vehicle acceptance models, neglecting the moderating variables' effect on these models. The main aim of this research is to investigate the effect of moderating variables including demographic characteristics, psychological characteristics, traffic experience collision, and travel/driving behavior on the autonomous vehicle acceptance model (AVAM). The AVAM was developed via structural equations modeling by participating 553 Tehrani citizens by extending the unified theory of acceptance and use of technology. It was indicated that the negative relationship of the perceived risk on the intention of using AVs has been higher for individualistic people, culprit drivers with a history of more than one property damage-only collision, and those without a driving license. Also, the results showed that emphasis on the advantages and benefits of autonomous vehicles in collectivist people as compared to individualistic people would lead to a greater intention to use these vehicles.</p></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49722725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Safety evaluation of centerline rumble strips on rural two-lane undivided highways: Application of intervention time series analysis 农村两车道不分段公路中心线隆隆带安全性评价:干预时间序列分析的应用

IF 3.2

IATSS Research Pub Date : 2023-07-01 DOI: 10.1016/j.iatssr.2023.05.001

Ahmed Hossain , Xiaoduan Sun , Ashifur Rahman , Sushmita Khanal

{"title":"Safety evaluation of centerline rumble strips on rural two-lane undivided highways: Application of intervention time series analysis","authors":"Ahmed Hossain , Xiaoduan Sun , Ashifur Rahman , Sushmita Khanal","doi":"10.1016/j.iatssr.2023.05.001","DOIUrl":"10.1016/j.iatssr.2023.05.001","url":null,"abstract":"<div><p>Centerline rumble strips are low-cost effective countermeasures installed on the center of the highway segments to reduce crashes, especially roadway departure crashes. For safety evaluation of centerline rumble strips, methodologies such as naïve before-after analysis and cross-sectional study with Empirical Bayes have been widely utilized. The implementation of these methodologies may be limited due to the lack of relevant control groups, and/or other temporal variations in crashes such as seasonality and serial autocorrelation. This study aims to explore Intervention Time Series Analysis approach as an alternative method for the safety evaluation of centerline rumble strips on rural-two-lane undivided highways in Louisiana. Two different methodologies are explored in the intervention time series approach including the Forecast modeling technique and the Auto-regressive Integrated Moving Average intervention model. The forecast models are based on the exponential smoothing technique, state-space framework, and neural network model. The database consists of monthly observations of total and target crashes on 312 highway segments of 1274 miles in length in which centerline rumble strips were installed during the 2010–2012 period. The time frame 2005–2012 is defined as the pre-intervention period whereas the time frame 2013–2017 is defined as the post-intervention period. The analysis revealed that the Auto-regressive Integrated Moving Average intervention model performed better in terms of error estimates including root means square error, mean absolute error, and mean absolute percentage error. The proposed Auto-regressive Integrated Moving Average intervention model reveals a 17.75% total and 40.54% target crash reduction on the selected rural-two-lane undivided highway segments during the post-intervention period. All the findings are found statistically significant at a 95% confidence level.</p></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49242985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Contribution to the analysis of driver behavioral deviations leading to road crashes at work 对分析导致工作中道路碰撞的驾驶员行为偏差的贡献

IF 3.2

IATSS Research Pub Date : 2023-07-01 DOI: 10.1016/j.iatssr.2023.03.003

Heddar Yamina , Djebabra Mébarek , Belkhiri Mohammed , Saaddi Saadia

引用次数: 0

Multivariate analysis of following and filtering manoeuvres of Motorized Two Wheelers in mixed traffic conditions 混合交通条件下电动两轮车跟驰和滤波操纵的多元分析

IF 3.2

IATSS Research Pub Date : 2023-07-01 DOI: 10.1016/j.iatssr.2023.05.004

Jaikishan Damani, Perumal Vedagiri

{"title":"Multivariate analysis of following and filtering manoeuvres of Motorized Two Wheelers in mixed traffic conditions","authors":"Jaikishan Damani, Perumal Vedagiri","doi":"10.1016/j.iatssr.2023.05.004","DOIUrl":"10.1016/j.iatssr.2023.05.004","url":null,"abstract":"<div><p>Mixed traffic conditions present a complex problem for analysis by transportation engineers and policymakers, due to the inherent heterogeneity and lane indiscipline. The chaotic arrangements make it difficult to identify and analyze basic riding behaviour such as following and filtering. Moreover, the smaller lateral dimensions of Motorized Two Wheelers (MTWs) and their higher manoeuvreability add to the difficulty. Presence of different types of vehicles in traffic mix, following the leader with or without obliqueness, filtering through tight pores between leader vehicles, etc. are some of the aspects that require special attention. In this respect, this study is aimed at investigating the attributes related to following and filtering manoeuvres of MTWs in such disordered traffic conditions. Real world data from two Indian cities was used for the analysis, which showed that the behaviour of MTWs is heavily influenced by the type of leader vehicle(s), Clear Lateral Gap (CLG), speed, etc. Safety analysis carried out using Time-To-Collision (TTC) showed that about 8.2% of the interactions were risky. Support Vector Machine (SVM) technique was used to investigate the choice of filtering based on Clear Lateral Gap (CLG) and relative speed. Moreover, analysis of the observed parameters was conducted to obtain their specific distributions based on leader vehicle type, following regime and choice of filtering. The analysis will give directions for further research on developing driving behaviour models of MTWs in mixed traffic. The results will also find potential application in traffic flow theories, safety studies, microsimulation, implementation of MTW infrastructure, etc.</p></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45048136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting child occupant crash injury severity in the United Arab Emirates using machine learning models for imbalanced dataset 使用不平衡数据集的机器学习模型预测阿拉伯联合酋长国儿童乘员碰撞伤害的严重程度

IF 3.2

IATSS Research Pub Date : 2023-07-01 DOI: 10.1016/j.iatssr.2023.05.003

Muhammad Uba Abdulazeez , Wasif Khan , Kassim Abdulrahman Abdullah

{"title":"Predicting child occupant crash injury severity in the United Arab Emirates using machine learning models for imbalanced dataset","authors":"Muhammad Uba Abdulazeez , Wasif Khan , Kassim Abdulrahman Abdullah","doi":"10.1016/j.iatssr.2023.05.003","DOIUrl":"10.1016/j.iatssr.2023.05.003","url":null,"abstract":"<div><p>Road traffic crashes have increased over the years leading to greater injury severity among children who are mostly vehicle occupants in high-income countries. This adversely affects the healthy development of children and might lead to death. However, studies in the literature have focused on predicting crash injuries among adults while children have different crash injury risks as well as crash kinematics compared to adults. To address this gap, this paper presents a new dataset for child occupant crash injury severity prediction collected over 8 years (2012 to 2019) in the United Arab Emirates (UAE). The performance of state-of-the-art machine learning algorithms was then evaluated using the proposed dataset. In addition, feature selection techniques and logistic regression model were employed to extract the most significant features for crash injury severity prediction among child occupants. Furthermore, the impact of data balancing approaches on the prediction performance was analyzed as the dataset is highly imbalanced. The experimental results showed that Adaboost, Bagging REP, ZeroR, OneR, and Decision Table algorithms predicts child occupant injury severity with the highest accuracy. Child occupant seating position, emirate, crash location, crash type and crash cause were observed as significant features that predicts injury severity by both the feature selection and logistic regression models.</p></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45666515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluating perceived safety of autonomous vehicle: The influence of privacy and cybersecurity to cognitive and emotional safety 评估自动驾驶汽车的感知安全：隐私和网络安全对认知和情感安全的影响

IF 3.2

IATSS Research Pub Date : 2023-07-01 DOI: 10.1016/j.iatssr.2023.06.001

Eko Agus Prasetio, Cintia Nurliyana

{"title":"Evaluating perceived safety of autonomous vehicle: The influence of privacy and cybersecurity to cognitive and emotional safety","authors":"Eko Agus Prasetio, Cintia Nurliyana","doi":"10.1016/j.iatssr.2023.06.001","DOIUrl":"10.1016/j.iatssr.2023.06.001","url":null,"abstract":"<div><p>The autonomous vehicle (AV) is predicted to reduce the number of accidents and fatalities on the roads caused by human-related error and lessen traffic congestion caused by stop-and-go behavior. The susceptibility of autonomous vehicles (AVs) to potential hacking and data exploitation has generated significant concerns regarding cybersecurity and privacy risks within the domain of perceived safety. This study aimed to empirically test a comprehensive model of perceived safety in AVs, incorporating cognitive safety, emotional safety, and privacy cybersecurity. The responses of 466 participants were analyzed using a structural equation modeling (SEM) approach. The findings indicated that a significant majority of the respondents expressed their intention to utilize high-level autonomous vehicles (AVs) in the future. Specifically, 31.1% of the participants expressed an intention to use a level 2 AV, while 8.8% indicated their preference for a level 5 AV. In terms of perceived safety, privacy cybersecurity emerged as the most influential predictor, followed by emotional safety and cognitive safety. The analysis of causal relationships between the variables further revealed that privacy cybersecurity had the greatest impact on both emotional safety and cognitive safety, highlighting its critical role in shaping the overall perception of safety in AVs. Finally, this study can provide insight into how the drivers perceives AVs safety, which can be useful for government organizations, transportation agencies, and AV developers in shaping AV safety.</p></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45937324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0