inLane
Description
inLane’s vision is to develop a low-cost, lane-level, precise turn-by-turn navigation application through the fusion of EGNSS and Computer Vision technology. It envisions a new generation of enhanced mapping information, made possible by real-time updates based on crowdsourcing techniques, which will result in lane-level vehicle positioning to take navigation to a new level of detail and effectiveness.
​
Objectives
-
To develop a low-cost EGNOS/EDAS + GNSS (GPS/GLONASS/Galileo) + IMU + Computer Vision based positioning module prototype for fast HW/SW in-the-loop development, which will enable enhanced positioning capabilities.
-
To develop new, computer vision based, road modelling (lane modelling), traffic signal identification and road/traffic element tracking and identification.
-
To create a new generation of enhanced maps that will update continuously
-
To define and develop complex fusion and hybridisation algorithms for GNSS, IMU, Map and Computer Vision technologies for reaching sub-metre accuracy (precise in-lane position)
Participants
inLane
Project Status
Ongoing (1 January 2016 – 30 June 2018)
Related Projects
DITCM
CONTACT
Vicomtech
-
HRI (Honda Research Institute EU)
-
RACC
-
intel
-
Ertico
-
TomTom
-
Vicomtech
-
IFSTTAR
-
TU/e
-
TeleConsult Austria
​
Inputs
​
Architecture
In Vehicle Infrastructure
-
Camera sensor
-
3D Maps
-
GPS
Road Side Infrastructure
-
Low-cost EGNOS/EDAS + GNSS (GPS/GLONASS/Galileo) + IMU + Computer Vision based positioning module.
Data Processing Hub
-
Precise turn-by-turn navigation application through the fusion of EGNSS and Computer Vision technology.
Communication Protocol
-
IEEE802.11p alpha prototype - Used for developing, integrating and evaluating different components.
-
IEEE802.11p Pre-beta prototype - Demo for assessing positioning accuracy, Demo for showing camera to map alignment and Local Dynamic Map functionalities, Demo for showing lane-level navigation functionality, Demo for showing map update functionality
​
​
Benefits
-
Low-cost, lane-level, precise turn-by-turn navigation application through the fusion of EGNSS and Computer Vision technology.
-
Use of European GNSS through demonstrating the ability to use EGNOS/EDAS and early Galileo services to obtain the accuracy needed to ensure a smooth, safe and precise vehicle positioning and cartography generation.
-
Accuracy and integrity of the calculated position thanks to the use of EGNSS signals
-
Road elements automatic detection using advanced computer vision techniques
-
The development of standards for coding new road data content classes
-
Cartography data automatic generation and location with high precision and integrity
Services
-
Lane-Level Navigation Application
-
Traffic Sign Recognition
​
Limitations
Adaptability of navigation is a problem for big drivers.
The cartography data is facing a great challenge since the current data is not going to be enough for next-generation uses, such as lane level position in Advanced Driver Assistance Systems (ADAS), hyper-specific location-based services and self-driving cars.
Cartographic Data is an International E&P Database module that includes multiple geographic data layers for geographic mapping, GIS analysis, and spatial validation.