Improved Testing of Self-Driving Vehicles in Challenging Traffic Situations

In the foreseeable future, spanning decades from now, connected autonomous vehicles and human driven vehicles need to coexist on our roads. Therefore, there must be further exploration into the specific traffic situations which are the most challenging to the autonomous vehicles. Among these are highway on-ramps, where vehicle drivers normally adapt to the traffic flow and the actions of other drivers. Another example providing difficult scenarios for the mixed traffic is roundabouts, for the same reasons.

In order to develop AD and ADAS systems, industry needs a good understanding of complex traffic situations. This can be achieved by recording actual traffic flows in a real field environment. 

The proposed project is focused on the lane merging situation and assumes that it is possible to use modern camera technology and roadside units to record actual traffic flows.

The objective is to define requirements on how an arrangement of equipment should be installed, and what data to capture in order to provide traffic flow information which can be used for repeatable test cases that meet the current and anticipated needs of vehicle manufacturers, regulators such as NCAP, and other stakeholders.

Key steps of the project are

• Establishing current and anticipated stakeholder needs related to virtual testing
• Define requirements on a test system for lane merging that can capture data for the virtual testing system
• Prepare for a Proof of Concept demonstration, to be carried out in a possible full-scale continuation project