This document summarizes research on identifying critical lane change scenarios using data from field tests of vehicles. Real driving data was used to parameterize a hyperbolic tangent function to model vehicle trajectories. Different parameter values for speed, acceleration, steering angle and position were tested in a simulated environment to identify boundaries where collisions occurred. Critical test cases were identified, such as when two vehicles shared the same trajectory point. The research aims to estimate collision risk in naturalistic driving to improve safety of advanced driver assistance systems.

1. Identification of Critical
Cases in Lane Changing
Sameed Tariq-82142
References:
Zhou, Jinwei, and Luigi del Re. "Identification of critical cases of ADAS safety
by FOT based parameterization of a catalogue." Control Conference (ASCC),
2017 11th Asian. IEEE, 2017.

2. Motivation
 The aim of the paper is to estimate the risk of
collision in naturalistic driving scenarios to obtain
a realistic parameterization.
 The primary focus of the paper is lane change
scenario on highways, one of the most relevant
safety critical maneuvers

3. Field Operational Test
 BMW 320d equipped with 2 Radar sensors (front,
back) and 2 Stereo cameras (front, back) is used
to gather data

4. Real Measurement to Hyperbolic Tangent
function.

5. Parameter in Hyperbolic Tangent
Function (Track Generation)
 Ego Car Speed
 Acceleration
 Steering Angle
 Position of the Ego Car (x,y) Coordinates

6. How
 lane change by applying hyperbolic tangent function
 Cut in and cut out Scenarios
 “Quickly” identify the critical boundaries (i.e., under which
conditions the car crashes) by doing parameter exploration
 Car Collision
 Yes
 NO

7. Story Line
 The car is roaming on the road with other traffic
participants and it overtakes the car by lane
changing. The car can collide or may not collide
depending upon the parameters of the model.

8. Lane Changing Test Scenario
Modified Test CaseOriginal Test Case

9. Scenario Demonstration
 Calculating the initial and starting position of the
coordinates of the car on the map (highway/road).
 The coordinates are used to generate the path on the
track.
 Goal: How the parameters of the hyperbolic tangent
function and acceleration effect the path followed by
the car.

10. Reference Scenario

11. Crash Scenario 1

12. Crash Scenario 2

13. Visual Tracks

14. Test Case 1
 Path : Car follows the
tangent path
 Result
No Collision
 Reason
It bypass the car lane
and go to third lane with
no cars and reach the
target point

16. Test Case 2
 Path : Car follows the
tangent path
 Result
Collision
 Reason
The Ego Car and leading car
share the same trajectory
path/point at given time.
 Parameter Change :
Increase Acceleration

18. Test Case 3
 Path : Car follows the tangent path
 Result
Collision
 Reason
The Ego Car and leading car share
the same trajectory path/ point at
given time.
 Parameter Change : Increase
Acceleration twice

20. Car Safety
Scenarios
 Blue – Crash Region
 Red, Green and Yellow (Safe
Region)

21. Challenges (Simulation BeamNG)
 Determine the exact point when to start/trigger ego car
for the lane changing.

22. Technologies and Tools
 BeamNG.research
 Python
 Draw.IO

23. Thank You
5846HS : Search-based Software Engineering for Testing Autonomous Cars
(Advanced seminar)