The Next Step in ADAS Testing

Autonomous driving is a popular topic at the moment, with various announcements from manufacturers who are confident that their cars will be doing the driving for us within a surprisingly short time frame. Some predictions state 2020 as the year by which the technology and infrastructure will be in place to make this a reality.

Whether or not this is feasible, there is no denying the leaps in technology that will, ultimately, deliver personal transport in which every vehicle occupant is a passenger. It could be argued that autonomous driving is already here: cars can now park and brake independently; Tesla have recently demonstrated their auto-pilot feature which controls speed based on traffic sign recognition; Volvo assure us that in five to ten years, their commercial vehicles will be constantly scanning every pedestrian, cyclist, and item of roadside furniture within the truck’s vicinity, then acting upon what it sees.

The combination of radar, lidar, GPS, and vision will ensure the current methods of advanced driver assistance will eventually morph into the actual drivers themselves.

Developing, then testing, and finally validating these systems has given rise to an automotive testing market that has seen dramatic upheaval in the last decade and it means that whilst we maintain a core competency in vehicle dynamics testing, recent years have seen significant development in providing test and validation solutions for ADAS. A recent update (firmware version 2.1) to the VBOX 3i SL-RTK introduces some interesting new features.

Testing Vision Enhancements

Traffic sign recognition systems are due to be greatly improved thanks to a new generation of high-definition cameras with better range than the current VGA resolution units. The new systems need to be tested for this greater range and a higher number of potential recognition markers, so the VBOX Multiple Static Points application allows for up to one hundred such targets to be surveyed, creating a GPS map of their locations.


The desired minimum and maximum detection angle and distance for these targets are then set, and the vehicle driven along the route. When the points fall within the detection zone, the range, angle, and time-to-collision parameters of up to five of them are simultaneously displayed and logged, with further targets being tracked as the closer ones are passed by. The GPS data is then compared to the performance of the system under test.


Read the rest of this article here.


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