Characteristics of driver cell phone use and their influence on driving performance: A naturalistic driving study

2020 ◽  
Vol 148 ◽  
pp. 105845
Author(s):  
Xuesong Wang ◽  
Rongjiao Xu ◽  
Abrha Asmelash ◽  
Yilun Xing ◽  
Chris Lee
Keyword(s):  
Cell Phone ◽  
Driving Performance ◽  
Cell Phone Use ◽  
Naturalistic Driving Study ◽  
Naturalistic Driving

Naturalistic Driving Study: Collecting Data on Cell Phone Use

2015 ◽  
Author(s):  
Julie K. Cook ◽  
Jonathan F. Antin ◽  
Whitney M. Atkins ◽  
Jonathan M. Hankey ◽  
◽  
...  
Keyword(s):  
Cell Phone ◽  
Cell Phone Use ◽  
Naturalistic Driving Study ◽  
Naturalistic Driving

scholarly journals Effect of Using Mobile Phones on Driver’s Control Behavior Based on Naturalistic Driving Data

2019 ◽  
Vol 16 (8) ◽  
pp. 1464 ◽  
Author(s):  
Lanfang Zhang ◽  
Boyu Cui ◽  
Minhao Yang ◽  
Feng Guo ◽  
Junhua Wang
Keyword(s):  
Mobile Phones ◽  
Cell Phone ◽  
Safety Management ◽  
Time Window ◽  
Crash Risk ◽  
Control Activity ◽  
Cell Phone Use ◽  
Control Behavior ◽  
Naturalistic Driving ◽  
The Impact

Distracted driving behaviors are closely related to crash risk, with the use of mobile phones during driving being one of the leading causes of accidents. This paper attempts to investigate the impact of cell phone use while driving on drivers’ control behaviors. Given the limitation of driving simulators in an unnatural setting, a sample of 134 cases related to cell phone use during driving were extracted from Shanghai naturalistic driving study data, which provided massive unobtrusive data to observe actual driving process. The process of using mobile phones was categorized into five operations, including dialing, answering, talking and listening, hanging up, and viewing information. Based on the concept of moving time window, the variation of the intensity of control activity, the sensitivity of control operation, and the stability of control state in each operation were analyzed. The empirical results show strong correlation between distracted operations and driving control behavior. The findings contribute to a better understanding of drivers’ natural behavior changes with using mobiles, and can provide useful information for transport safety management.

Modeling Driving Performance Using In-Vehicle Speech Data From a Naturalistic Driving Study

2016 ◽  
Vol 58 (6) ◽  
pp. 833-845 ◽  
Author(s):  
Jonny Kuo ◽  
Judith L. Charlton ◽  
Sjaan Koppel ◽  
Christina M. Rudin-Brown ◽  
Suzanne Cross
Keyword(s):  
Driving Performance ◽  
Speech Data ◽  
Naturalistic Driving Study ◽  
Naturalistic Driving

scholarly journals Examination of drivers' cell phone use behavior at intersections by using naturalistic driving data

2015 ◽  
Vol 54 ◽  
pp. 89.e29-93 ◽  
Author(s):  
Huimin Xiong ◽  
Shan Bao ◽  
James Sayer ◽  
Kazuma Kato
Keyword(s):  
Cell Phone ◽  
Cell Phone Use ◽  
Naturalistic Driving ◽  
Use Behavior

Driver Inattention: A Contributing Factor to Crashes and Near-Crashes

2005 ◽  
Vol 49 (22) ◽  
pp. 1922-1926 ◽  
Author(s):  
Sheila G. Klauer ◽  
Vicki L. Neale ◽  
Thomas A. Dingus ◽  
David Ramsey ◽  
Jeremy Sudweeks
Keyword(s):  
Performance Metrics ◽  
State Legislatures ◽  
Washington Dc ◽  
Cell Phone Use ◽  
Naturalistic Driving Study ◽  
Driver Inattention ◽  
Collection Period ◽  
Naturalistic Driving ◽  
Instrumented Vehicle ◽  
Post Hoc

Driver distraction, or inattention, has been receiving wide media attention recently as many state legislatures are considering various levels of restricting cell phone use. Research has been conducted using a variety of experimental methods to determine the level of risk associated with driving inattention. While most of this research suggests that inattention impairs driving, there have been no studies to directly link driving inattention to crashes. Data from the 100-Car Naturalistic Driving Study, an instrumented vehicle study for which data was collected on 100 drivers in the Washington, DC metropolitan area for 12 months, were used in the following analyses. Crashes and near-crashes were identified in the data using post-hoc triggers based upon driving performance metrics, (i.e. hard braking). Results suggest that inattention contributed to 78% of all crashes collected over the 12 month data collection period.

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