Toyota - Traffic Scene Understanding for Automated Vehicles with Focus on Freeway Merging Maneuvers
Funding or Partner Organisation: Toyota Motor Engineering and Manufacturing North America, Inc (Toyota Motor Engineering and Manufacturing North America Inc)
Start year: 2014
Summary: One of the most demanding situations in driving is when a vehicle is to merge from a slow moving traffic of lower priority into a fast moving one of higher priority. The condition is even more challenging when merging from a ramp into a freeway, which requires estimating the distance and speed of the front and rear vehicles accurately and making the decision to merge in a time-pressing situation. The aim of this research is to develop a system of visual analytics to extract and analyse informative clues from video streams obtained by on-board cameras. The system is especially focused on achieving comprehensive understanding of the particular traffic conditions in the context of freeway merging. Thus the research will deliver the essential perceptive capability for autonomous driving systems to cope with the fast changing and decision demanding situation of freeway merging. The research will also contribute to a driver assistance system which is highly helpful for human users.
FOR Codes: Application Tools and System Utilities, Information Processing Services (incl. Data Entry and Capture), Computer Vision, Pattern Recognition and Data Mining