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D2.1 Sensor Data Fusion V1 Grant Agreement Number: 687458 Project acronym: INLANE Project full title: Low Cost GNSS and Computer Vision Fusion for Accurate Lane Level Naviga- tion and Enhanced Automatic Map Generation D2.1 Sensor Data Fusion Due delivery date: 31/12/2016 Actual delivery date: 30/12/2016 Organization name of lead participant for this deliverable: TCA Project co-funded by the European Commission within Horizon 2020 and managed by the European GNSS Agency (GSA) Dissemination level PU Public x PP Restricted to other programme participants (including the GSA) RE Restricted to a group specified by the consortium (including the GSA) CO Confidential , only for members of the consortium (including the GSA) Document Control Sheet Deliverable number: D2.1 Deliverable responsible: TeleConsult Austria Workpackage: 2 Editor: Axel Koppert Author(s) – in alphabetical order Name Organisation E-mail Axel Koppert TCA [email protected] Document Revision History Version Date Modifications Introduced Modification Reason Modified by V0.1 18/11/2016 Table of Contents Axel Koppert V0.2 05/12/2016 Filling the document with content Axel Koppert V0.3 19/12/2016 Internal Review François Fischer V1.0 23/12/2016 First final version after internal review Claudia Fösleitner Abstract This Deliverable is the first release of the Report on the development of the sensor fusion and vision based software modules. The report presents the INLANE sensor-data fusion and GNSS processing approach. This first report release presents the status of the development (tasks 2.1 and 2.5) at M12. Legal Disclaimer The information in this document is provided “as is”, and no guarantee or warranty is given that the information is fit for any particular purpose. The above referenced consortium mem- bers shall have no liability for damages of any kind including without limitation direct, special, indirect, or consequential damages that may result from the use of these materials subject to any liability which is mandatory due to applicable law. © 2016 by INLANE Consortium. 2 Abbreviations and Acronyms Acronym Definition EDAS EGNOS Data Access Service EGNOS European Geostationary Navigation Overlay Service GNSS Global Navigation Satellite System IMU Inertial Measurement Unit INS Inertial Navigation System RMSE Root Mean Square Error WP Work Package 3 Table of Contents Executive Summary ............................................................................................................................... 6 1. Introduction ..................................................................................................................................... 7 1.1. Motivation ............................................................................................................................... 7 1.2. Purpose of Document ............................................................................................................ 7 1.3. Intended Audience ................................................................................................................. 7 2. Sensor Data .................................................................................................................................... 8 2.1. GNSS ..................................................................................................................................... 8 2.2. Low-Cost Inertial Sensors ...................................................................................................... 8 2.3. Visual Odometry ..................................................................................................................... 8 2.4. Sensor-to-Map Alignment ...................................................................................................... 8 2.5. Visual-Beacon-Based Positioning .......................................................................................... 9 3. GNSS processing and Augmentation ............................................................................................. 9 3.1. GNSS processing approach ................................................................................................... 9 3.2. EGNOS and EDAS ................................................................................................................ 9 3.3. Observation Modelling ......................................................................................................... 10 4. Sensor Data Fusion Module ......................................................................................................... 10 5. Current Results ............................................................................................................................. 12 6. Discussion and further development ............................................................................................ 14 4 List of Figures Figure 1: Current Sensor Data Fusion Scheme ................................................................................... 11 Figure 2: Lane change on a highway (GPS/INS) ................................................................................. 12 Figure 3: Trajectory of an urban scenario (GPS/INS fusion) ............................................................... 13 Figure 4: Trajectory of a forest scenario (white dots: GNSS 2 Hz, red dots: GPS/INS 500 Hz) .......... 13 List of Tables Table 1: Classification of sensor data for sensor data fusion in INLANE ............................................... 8 Table 2: Modelling of the GNSS observations ..................................................................................... 10 5 Executive Summary This deliverable presents the status of the development of the INLANE GNSS processing and sensor data fusion components at M12. An intermediate release of the report on the development will be issued at M24 and the final release will be issued at M30. The aim of INLANE’s positioning subsystem is to provide the position of the vehicle with lane-level accuracy, while using hardware that is suited for mass-market applications. An approach for combin- ing data from GNSS, an Inertial Measurement Unit and computer vision systems is presented. As a base for all developments, the available sensor information is classified systematically in terms of accuracy, availability and characteristic of the provided information. For achieving lane-level position- ing accuracy even in challenging urban scenarios, the available sensor information has to be com- bined in the best possible way. The current fusion architecture is based on a tightly coupled GPS/INS filter with additional measurement updates with data from the computer vision components. Current tests include only GPS and IMU data. First results of the developed software module are shown, fol- lowed by a discussed and a proposal for further developments. 6 1. Introduction 1.1. Motivation The INLANE project aims at developing a lane-level navigation system for the mass-market. The ac- curacy of the position determination sub-system should allow in-lane positioning, even in urban envi- ronment. It is the base for lane-level navigation and accurate map updates. The determination of the state of a car in urban environment is a challenging task. This applies even more if only sensors of low-cost are available. Current approaches are based on GNSS/INS fusion. However, when employ- ing mass-market hardware the performance of those systems in urban environments is limited due to the unfavorable GNSS observation conditions and the relative low performance of low-cost inertial measurement units. For overcoming these problems, a sensor-data fusion approach making use of computer vision techniques is under development. We expect, that the information from the computer vision components will improve the overall accura- cy of the positioning sub-system, as well as the percentage of time that allows lane-level positioning. 1.2. Purpose of Document Deliverable 2.1 is the report on the developed software modules that fuse EGNOS-GNSS absolute position estimates, IMU relative positions estimates, and vision-based (map matching) absolute posi- tion estimates. This current version is the first version of D2.1, based on the status of the INLANE project at the end of the first year. This deliverable gives an overview of the approach to sensor data fusion and GNSS processing of the INLANE project and the status of the tasks 2.1 and 2.5. Based on the presentation of the status and the first results, possibilities for further development are discussed and an outlook on the intended work for the next project phase is given. 1.3. Intended Audience This deliverable is intended to promote a better understanding of the approach that has been taken in this important part of the INLANE system and to document the progress. This is especially interesting for the project partners and for the European Commision. Moreover, D2.1 is public a public delivera- ble that is directed to everybody who is interested in the achievements of the INLANE project. 7 2. Sensor Data In this section a systematic overview about the available data for the fusion will be given. The INLANE positioning component uses data from three sensors: a GNSS receiver, a low-cost inertial measure- ment unit (IMU) and a video camera. As the final prototype should be an aftermarket device that should not need a connection to the car no data from the car’s CAN bus will be used. Table 1 pro- vides an overview of the sensor data and derived information that are available for the sensor-data
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