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Low Cost GNSS and Computer Vision Fusion for Accurate Lane Level Navigation and Enhanced Automatic Map Generation

Periodic Reporting for period 1 - INLANE (Low Cost GNSS and Computer Vision Fusion for Accurate Lane Level Navigation and Enhanced Automatic Map Generation)

Reporting period: 2016-01-01 to 2017-06-30

Nowadays lane navigation consists in preparing the exits and turns on difficult roads by showing the driver the lane and exit that he or she needs to follow. The information is visual (usually showing still images). This is informative, rather than being based on the vehicle’s real position on the road. Additionally, the system gives independent voice alerts as to whether you are correctly placed or not, and this in some cases can lead to confusion and loss of attention for the driver.

The current state of mapping is sufficient for the basic navigation applications, but 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.

The main objective of inLane is to develop a new generation, low-cost, lane-level, precise turn-by-turn navigation application through the fusion of EGNSS and Computer Vision technology. This will enable a new generation of enhanced mapping information with real-time updating based on crowdsourcing techniques. The resulting lane-level vehicle positioning will bring navigation to a new level of detail and effectiveness.
From M1 to M12 the project activity was focused on developing the alpha prototype. Firstly, a definition stage was accomplished generating the first set of specifications requirement and architecture. After the architecture specification, an alpha version of each software module was developed.

A common methodology and set of rules to efficiently develop, integrate and evaluate the different components involved and the resulting system was also defined. In addition, the alpha version of each software module was individually tested with unit tests to obtain a ready-to-integrate system that forms the alpha prototype.

In parallel, the strategy to involve end users in the project was defined, the alpha prototype was tested with technical expert users, and a user survey to gather end users’ opinion and feed functional requirements and use cases were designed.

From M13 to M18, the activities of the technical work packages focused on developing a pre-Beta prototype that would demonstrate the work carried out in the first reporting period. In order to facilitate the evaluation of the developed functionalities, we decided to integrate 4 demonstrators during this period. Each of these demonstrators is focused on one of the inLane’s core functionalities:
- 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

During this reporting period, the consortium also focused on dissemination, exploitation, standardisation and management activities.

Finally, the inLAne project has successfully achieved the following milestones:
- Kick-off meeting and successful launch of the project
- inLane requirements, specifications, and architecture delivered
- inLane subsystems delivered for the first prototype
- First business and exploitation plan created
1. Expected results and progress beyond state of the art
inLane, using a low-cost and therefore accessible model, will provide drivers with the following advantages, progressing beyond the state of the art and fostering a new generation of driver assistance navigation:
• Accuracy and integrity of the calculated position thanks to the use of EGNSS signals
• Road elements automatic detection using advance 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
• Local Dynamic map information layer generation for assisting the driver
• Vehicle positioning in the lane (contrary to the most common approach in map matching of simply projecting the vehicle position on the centre of the segment)
• The relative lateral position of the vehicle on the carriageway, informing the user of how many lanes the carriageway has at its current cross section and on which one of these lanes the vehicle is
• A level of confidence on the position level that is based not only on GNSS measurements (as traditional integrity parameters do) but on the combination of all positioning information sources and the enhanced maps
• A level of reliability in terms of lane

2. Potential impacts
inLane will stimulate the 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. This will be used for next generation driver assistance application such as lane level navigation that will be validated in this project and also to generate new, enhanced cartography. By working on the surface transportation area, the consortium intends to demonstrate how most modern EGNSS technologies can be applied in traditional sectors and become part of the tools accessible to everyone in their everyday life.

In particular, this project seeks to show to the mass market end-user that:
• Galileo or EGNOS based services bring enhanced accuracy, safety and integrity (that the GPS cannot typically bring) of the position and thus it usage into the driver assistance domain
• This enhanced safety and integrity can be a direct and significant benefit in terms of general public mobility, since the inclusion of this technology will be straight forward in vehicles, aftermarket devices and smartphones.

In doing so, inLane will also be fully in line with the Work Programme Objective and European Space Policy, which reflects the key strategic importance of space systems and space applications for Europe.

ITS is one of the leitmotiv themes in the European Transport Roadmap to 2050. Galileo will afford considerable advantages in many sectors of the economy. In road and rail transport, for example, it will make it possible to predict and manage journey times, or, thanks to automated vehicle guidance systems, help reduce traffic jams and cut the number of road accidents.
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