{"title":"Signs and Pedestrian Safety in Automated Transportation Systems","authors":"Haiyan Xie, Luke Verplaetse","doi":"10.11648/J.ACIS.20190701.16","DOIUrl":null,"url":null,"abstract":"Motor-vehicle accidents have caused many safety concerns ever since cars have been on the road. With the implementation of cooperative and automated vehicles (CAVs) merging into the current crosswalks, signals, and concrete rules, the vehicle-pedestrian interactions create noteworthy safety issues. Through observational findings, intersections with higher signage and pedestrian signals had less likely of a chance for pedestrians to run into an altercation when compared to intersections with just crosswalks and no pedestrian signals. This research presents an optimization framework and an analytical solution with field observations to study whether the implementation of more pedestrian signals could have a great effect on vehicle/pedestrian incidents. The research implements the integrated methods of case studies, modeling and simulation using mathematical and statistical software on correlations and probabilities. This study adds minimal interference to the observations as they naturally occur. The study setting is non-contrived and maintained as natural environment. The collected data is continuous time series and measured using Chi-Square for analysis. After the identification of possible interactions between CAVs and pedestrians based on the data surveyed around the Illinois State University (ISU), this study finds that the safety of pedestrian relies on the intersection design of signs and signals more than the intelligence of CAVs (significance level = 95%). This paper also discusses law enforcement and autonomous driving as a means of lowering pedestrian incidents at intersections. The developed mathematical analysis model and simulations help to verify the influences of transportation signs and intersection designs. The investigation innovatively demonstrates the feasibilities of different methods to protect the pedestrian safety while they enter intersections. The findings from this research can provide decision support for future transportation design and implementation rules of CAVs.","PeriodicalId":205084,"journal":{"name":"Automation, Control and Intelligent Systems","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automation, Control and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11648/J.ACIS.20190701.16","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Motor-vehicle accidents have caused many safety concerns ever since cars have been on the road. With the implementation of cooperative and automated vehicles (CAVs) merging into the current crosswalks, signals, and concrete rules, the vehicle-pedestrian interactions create noteworthy safety issues. Through observational findings, intersections with higher signage and pedestrian signals had less likely of a chance for pedestrians to run into an altercation when compared to intersections with just crosswalks and no pedestrian signals. This research presents an optimization framework and an analytical solution with field observations to study whether the implementation of more pedestrian signals could have a great effect on vehicle/pedestrian incidents. The research implements the integrated methods of case studies, modeling and simulation using mathematical and statistical software on correlations and probabilities. This study adds minimal interference to the observations as they naturally occur. The study setting is non-contrived and maintained as natural environment. The collected data is continuous time series and measured using Chi-Square for analysis. After the identification of possible interactions between CAVs and pedestrians based on the data surveyed around the Illinois State University (ISU), this study finds that the safety of pedestrian relies on the intersection design of signs and signals more than the intelligence of CAVs (significance level = 95%). This paper also discusses law enforcement and autonomous driving as a means of lowering pedestrian incidents at intersections. The developed mathematical analysis model and simulations help to verify the influences of transportation signs and intersection designs. The investigation innovatively demonstrates the feasibilities of different methods to protect the pedestrian safety while they enter intersections. The findings from this research can provide decision support for future transportation design and implementation rules of CAVs.
自从汽车上路以来,机动车事故就引起了许多安全问题。随着合作车辆和自动驾驶车辆(cav)融入当前的人行横道、信号和具体规则,车辆与行人的互动产生了值得注意的安全问题。通过观察发现,与只有人行横道和没有行人信号的十字路口相比,有较高标志和行人信号的十字路口行人发生口角的可能性更小。本研究提出了优化框架和分析解,并结合现场观察来研究更多行人信号的实施是否会对车辆/行人事故产生重大影响。本研究采用案例研究、建模和仿真相结合的方法,利用数学和统计软件对相关性和概率进行研究。这项研究对自然发生的观察结果的干扰最小。研究环境是非人为的,并保持自然环境。收集的数据为连续时间序列,使用卡方测量进行分析。本研究基于伊利诺伊州立大学(Illinois State University, ISU)周边的调查数据,识别出自动驾驶汽车与行人之间可能存在的相互作用后,发现行人的安全更多地依赖于交叉口标志和信号的设计,而不是自动驾驶汽车的智能(显著性水平= 95%)。本文还讨论了执法和自动驾驶作为降低十字路口行人事故的手段。建立的数学分析模型和仿真有助于验证交通标志和交叉口设计的影响。本研究创新性地论证了不同方法保护行人进入十字路口安全的可行性。研究结果可为未来自动驾驶汽车的交通设计和实施规则提供决策支持。