New-generation, low-cost, lane-level navigation

Lane-level positioning and map matching are some of the biggest challenges for navigation systems. We need more accurate and more reliable positioning systems to cater to the growing demand from applications such as enhanced driver awareness, intelligent speed alert and simple lane allocation.

There is also a question around the adaptability of navigation systems to these applications. This depends firstly on the availability of an accurate common reference for positioning (an enhanced map) and secondly, on the level of the provided pose estimation (integrity).

We propose new generation, low-cost, lane-level, precise turn-by-turn navigation applications through the fusion of EGNSS and Computer Vision technology. With the help of crowdsourced real-time updates, inLane foresees the  generation of local dynamic maps (LDM) that help ADAS applications with enhanced dynamic scene information. Delivering lane-level information to an in-vehicle navigation system and combining this with the opportunity for vehicles to exchange information between themselves, will give drivers the opportunity to select the optimal road lane, even in the case of dense urban and extra-urban traffic.

Every driver will be able to choose the appropriate lane and will to be able to reduce the risks associate with last-moment lane-change manoeuvres.