Secondary tasks in steady state car following situations

Examensarbete för masterexamen

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Typ: Examensarbete för masterexamen
Master Thesis
Titel: Secondary tasks in steady state car following situations
Författare: Fernandez, Andre
Sammanfattning: Naturalistic driving studies and field operational tests are important tools for traffic and road safety research. Naturalistic driving data and accident data show that rear-end collisions are the most common type of accident in car following situations. Furthermore, distraction from secondary- tasks-has been shown to be one of the leading causes of rear-end collisions. The aim of this thesis was to analyze driver behaviour in car following situations in order to gain insight into the influence of factors such as secondary tasks to the likeliness of rear-end collisions. A steady state car following scenario was defined and used to extract data representing car following situations from commutes on main arterial road segments. This data was studied to determine the effects of secondary tasks on driver behaviour measured by, among other variables, headway time to the lead vehicle. Driving data from passenger vehicles in the euroFOT project –the largest ongoing field operational test in Europe— was used in this study. The results presented in this thesis indicate that traditional measures of longitudinal and lateral control such as lane position and headway time are less affected by secondary tasks than measures related to driver control inputs such as peak steering angle acceleration in steady state following situations.
Nyckelord: Transport;Övrig teknisk mekanik;Transport;Other engineering mechanics
Utgivningsdatum: 2011
Utgivare: Chalmers tekniska högskola / Institutionen för tillämpad mekanik
Chalmers University of Technology / Department of Applied Mechanics
Serie/rapport nr.: Diploma work - Department of Applied Mechanics, Chalmers University of Technology, Göteborg, Sweden : 2011:65
URI: https://hdl.handle.net/20.500.12380/155033
Samling:Examensarbeten för masterexamen // Master Theses



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