Variables extraction and trajectory reconstruction for modelling driver behaviour
Typ
Projektarbete, avancerad nivå
Program
Publicerad
2020
Författare
Hamdy Shams El Din, Ahmed
Takkoush, Mohamed
Pettersson, Nicklas
Hulkunte Gopinath, Sriranga
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
Active safety and autonomous driving are two booming words in the automotive industry of
today. Most, if not all, companies are in a race to provide a safe environment for driving and are
thriving to reach their goals in producing autonomous vehicles.
The general goal of this project is to develop a human driver model for critical lane-changing
manoeuvres. Annotation of such data was done manually on videos acquired from dash-cam footage
from a naturalistic driving study (NDS) by identifying di erent events in time, such as time of lane
crossing and relative distance between vehicles. A semi-automatic tool to aid the annotation of the
NDS footage was developed and several methods for range calculation are discussed such as the pixel
width method and the triangulation method, which are also used for calculating the heading angle
and the lateral o set of the lead vehicle. The results were found to be relatively accurate considering
the simplicity of the tool. As for the tracking of the lead vehicles and the lanes, the most accurate
method was found to be through interpolating between user inputs.