Analyzing the Effect of Distractions and Impairments on Young Driver Safety Using Naturalistic Driving Study Data

被引:1
|
作者
Bharadwaj, Nipjyoti [1 ]
Edara, Praveen [2 ]
Sun, Carlos [2 ]
机构
[1] Indian Inst Technol Guwahati, Dept Civil Engn, IIT Annex Civil Engn Bldg 204, North Guwahati 781039, Assam, India
[2] Univ Missouri Columbia, Dept Civil & Environm Engn, E2509 Lafferre Hall, Columbia, MO 65211 USA
关键词
Young drivers; Teen drivers; Naturalistic driving study (NDS); Logistic regression; TEENAGE DRIVERS; RISK; CRASHES; NOVICE; SEVERITY; BEHAVIOR; RATES;
D O I
10.1061/JTEPBS.TEENG-7265
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In the United States, motor vehicle crashes are the leading reason of fatalities for young drivers in the age group of 16-19 years. This paper used naturalistic driving study (NDS) data to examine the safety of young drivers. The NDS data consist of comprehensive information related to driving behavior. The statistical modeling method (logistic regression) was used to investigate the relationship between factors of driver attention such as secondary tasks, impairments, hands on wheel, and crash risk to aid in the formulation of teen driving policy. The results indicated that nondriving tasks engagement such as cell phone use, external distraction, food and drink intake, personal hygiene, and reaching and handling objects in the vehicle increase the possibility of involvement in a safety critical event [odds ratio (OR)=1.67-1.93]. Risk estimation for the observable impairments indicated that emotional state of the driver (OR=6.01) and impairments (drugs/alcohol, OR=5.02) exerted greater influence on crash likelihood compared to involvement in secondary tasks. The study revealed that not all secondary tasks pose the same risk. Transportation agencies can design behavioral countermeasures targeted at young drivers to help increase driver attention. Countermeasures such as increased enforcement, treatment and monitoring of the offender, and education and outreach programs for teenagers may help alleviate impaired driving. (C) 2022 American Society of Civil Engineers.
引用
收藏
页数:8
相关论文
共 50 条
  • [21] Revision of the driver behavior questionnaire for Chinese drivers? aberrant driving behaviors using naturalistic driving data
    Jiao, Yujun
    Wang, Xuesong
    Hurwitz, David
    Hu, Gengdan
    Xu, Xiaoyan
    Zhao, Xudong
    ACCIDENT ANALYSIS AND PREVENTION, 2023, 187
  • [22] Cooperative Safety Based on Naturalistic Driving Data
    Li, Yingfeng Eric
    Gibbons, Ronald B.
    Kim, Bumsik
    JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS, 2022, 148 (10)
  • [23] Effects of driving anger on driver behavior - Results from naturalistic driving data
    Precht, Lisa
    Keinath, Andreas
    Krems, Josef F.
    TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2017, 45 : 75 - 92
  • [24] Analyzing the Impact of Distractions on Driver Attention: Insights from Eye Movement Behaviors in a Driving Simulator
    Narayana, Pradeep
    Attar, Nada
    2023 SEVENTH IEEE INTERNATIONAL CONFERENCE ON ROBOTIC COMPUTING, IRC 2023, 2023, : 356 - 359
  • [25] Screening Naturalistic Driving Study Data for Safety-Critical Events
    Wu, Kun-Feng
    Jovanis, Paul P.
    TRANSPORTATION RESEARCH RECORD, 2013, (2386) : 137 - 146
  • [26] Driver Head Pose Detection From Naturalistic Driving Data
    Chai, Weiheng
    Chen, Jiajing
    Wang, Jiyang
    Velipasalar, Senem
    Venkatachalapathy, Archana
    Adu-Gyamfi, Yaw
    Merickel, Jennifer
    Sharma, Anuj
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 24 (09) : 9368 - 9377
  • [27] Using SHRP2 naturalistic driving data to examine driver speeding behavior
    Richard, Christian M.
    Lee, Joonbum
    Atkins, Randolph
    Brown, James L.
    JOURNAL OF SAFETY RESEARCH, 2020, 73 : 271 - 281
  • [28] Driver Identification Based on Stop-and-Go Events Using Naturalistic Driving Data
    Gao, Zhen
    Li, Longqi
    Feng, Jinsong
    Yu, Rongjie
    Wang, Xuesong
    Yin, Changqing
    2018 11TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL 1, 2018, : 306 - 310
  • [29] Using naturalistic and driving simulator data to model driver responses to unintentional lane departures
    Svard, Malin
    Markkula, Gustav
    Aust, Mikael Ljung
    Bargman, Jonas
    TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2024, 100 : 361 - 387
  • [30] Analysis of Headway and Speed Based on Driver Characteristics and Work Zone Configurations Using Naturalistic Driving Study Data
    Xu, Dan
    Xue, Chennan
    Zhou, Huaguo
    TRANSPORTATION RESEARCH RECORD, 2021, 2675 (10) : 1196 - 1210