Driverless car system looks to master road construction sites
Wed 1 Mar 2017
A new system is currently under development which seeks to improve the real-time interpretation of traffic information on construction sites by autonomous vehicles.
Driverless cars have to be able to accurately detect traffic signs, but current technologies are facing difficulties when presented with temporary traffic management as appears in construction zones.
These sites are challenging for self-driving vehicles which have to read different information on speed or the course of lanes for example. Additionally, lanes typically narrow, traffic jams build up, drivers can react under stress and accidents are more likely to occur.
Road works can also present added complexities such as overlapping road markings, and beacons and traffic cones which are difficult for sensors to detect.
‘Our technology enables a system to read signs of this kind with a high degree of accuracy,’ said lead researcher Stefan Eickeler of the Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS), based in Sankt Augustin, Germany.
The Fraunhofer team believes that through the interplay between navigation equipment and on-board computers, it will be possible for road traffic complexities on construction sites to be correctly identified, for optimal distances to be maintained between vehicles, and for speed to be adjusted in a timely manner.
In the current model, an automotive camera is used to deliver 20 to 25 frames per second. During the journey, these images are analysed for information relating to road signs, lane information and LED traffic announcements. The future vision sees this camera as a primary interface, making many of the vehicle sensors redundant.
The project, which is expected to continue for the next three years, falls under the AutoConstruct scheme launched in December last year by the German Federal Ministry of Economics and Energy (BMWi).
The national initiative, funded by just under €2 million (approx. £1.7mn), sets out to develop systems for the real-time environment recognition of construction sites by automated vehicles.