CSE498, Collaborative Design, Spring 2020
Computer Science and Engineering
Michigan State University

Bosch is a global engineering and technology company with products sold in 150 countries worldwide. Founded in Germany in 1886, Bosch is the world’s leading supplier of automotive components.

Bosch’s adaptive cruise control is an advanced driver assistance system that allows a vehicle to automatically change its speed based on traffic conditions. Using software that processes radar data and video footage from the vehicle, the behavior of surrounding vehicles is labeled.

For example, if the system determines that a car is cutting into the lane directly in front of the host vehicle, it will identify and label the new vehicle, and intelligently adjust its pace in real time.

Currently, Bosch employees determine the accuracy of the adaptive cruise control software by manually labeling video files and comparing them to the behavior of the vehicle. While necessary, this labeling process is costly and difficult because Bosch collects thousands of hours of video footage.

Classifying Target Vehicles for Adaptive Cruise Control is a tool that automates the label generation process. Using machine learning, video is analyzed to detect lane lines and surrounding vehicles. Then, a combination of statistical logic and machine learning labels the environment in a time-series fashion. Each label is assigned a confidence rating, allowing Bosch employees to easily identify and fix incorrect labels.

This tool significantly reduces the time and effort required to manually label testing videos.

Our software is deployed to both Windows and Linux. The user interface is built with PyQt. The YOLOv3 algorithm is used to recognize vehicles, and ERFNet for lane line detection. A combination of machine learning and logic is used to compute the labels.