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Automated Driving Data Chain Challenges

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Automated Driving Data Chain Challenges Maxime Flament, ERTICO – ITS Europe AUTOMATED DRIVING DATA CHAIN CHALLENGES Flament | Automated Vehicle Symposium | July 2017 1 Tomorrow’s Situation: Sensors, Maps and Online Data The Vehicle Looks beyond 300m and Around the Corner 3. Extension of limited in-vehicle resources 2. Extended preview 1. Highly accurate map information Close preview: model provided and 10 minutes updated via the Backend 4. Fleet based data collection Vehicle Sensor range 0-300m GSV-Forum Automatisiertes Fahren October 2016 Public FF@ Continental AG 2 Automated driving data chain and ecosystem Reference architecture proposed by OADF N NDS A - - - - -- - - INFRASTRUCTURE - - - - - - - - - - - - - - - - - - - - - - - - - - - - VEHICLE - - - - - - - - - S T Backend (one or multiple) operated by Map supplier / OEM / 3rd Party ADAS (Local) Sensors (V2x) provided) OEM-specific Backends Horizon Sensors Provider Live Map Updates N (Dynamic Data) T Live Map N Local Live Map Delivery Maps & Updates T (Dynamic Data) A Environmental Model N N HD Map (Dyn.) Data Production Delivery HD Map A Analytics/Sensor Fusion Localization Data Collection Strategy Infotainment Map Delivery Infotainment Map N A Systematic Data Community Data Collection Store S S Data Store (Mobile Mapping) Data Collection (raw or pre-processed) S Flament | Automated Vehicle Symposium | July 2017 3 INTRODUCTION TO ADASIS Flament | Automated Vehicle Symposium | July 2017 4 ADASIS horizon along the map data chain TPEG: Traffic Information Map database NDS: Incremental Map Update In-vehicle systems Layers HMI e. g. hazard spots e. g. traffic information Determination of location and most ADAS, Energy Management e. g. speed limits probable path (MPP) 30 Map data Enrichment of MPP with Relevant information Digital map (static) (NDS Format) road information (e.g. for road ahead topography, speed (ADASIS Format) limits) Conversion into ADASIS format Flament | Automated Vehicle Symposium | July 2017 5 ADASIS horizon – evolution to the cloud In-vehicle embedded software Cloud-based backend software i. function horizon provider map Link to NDS Local function horizon provider map map Link to NDS ii. Hybrid function horizon provider map map dynamic data Link to NDS & TPEG Link to Sensoris, NDS & iii. function horizon provider map dynamic data Cloud TPEG i. ADASIS Horizon uses data from local map database and provides information for functions in the vehicle ii. ADASIS Horizon uses recent data from updated map database via cloud backend or live data from additional databases and provides information for functions in the vehicle iii. ADASIS Horizon uses cloud-based data and provides information for in-vehicle functions directly from the cloud Flament | Automated Vehicle Symposium | July 2017 6 ADASIS V3 specification supports highly automated driving New ADASIS V3 specifications supports different aspects of autonomous driving 1. Support of HAD maps (NDS) • Copyright: Here.com Flament | Automated Vehicle Symposium | July 2017 7 ADASIS V3 specification supports highly automated driving Lane model & Geometry Example: Highway Exit “switch from a map-centric view to a vehicle-centric view of the world to create a simpler representation” © Wikimedia Commons, licensed by CC-by-SA 2.5 Flament | Automated Vehicle Symposium | July 2017 8 ADASIS V3 specification supports highly automated driving Lane model: Segmentation of road into stretches with Segmentation of road same lane characteristics 3 Lanes into stretches with 1stsame level =lane path characteristics description level detail: 1 Lane number1st level of = lanespath description for each segment level detail: number of lanes for each segment 3+1 Lanes 3 Lanes + shoulder © Wikimedia Commons, licensed by CC-by-SA 2.5 Flament | Automated Vehicle Symposium | July 2017 9 ADASIS V3 specification supports highly automated driving Lane Model & Connectivity Lane Model & Connectivity: Logical Description similar to v2 Lane #3: Lane #2: nd 2 level = logical view normal normal Lane #1: level detail: Lane #1: ramp normal lane details and their connectivity Lane #4: normal Lane #3: normal Lane #2: normal Lane #3: Lane #2: Lane #1: normal normal normal © Wikimedia Commons, licensed by CC-by-SA 2.5 Flament | Automated Vehicle Symposium | July 2017 10 ADASIS V3 specification supports highly automated driving Lane Model & Connectivity Geometry for Linear Objects: • Lane Boundaries Geometry for Linear Objects: • Guardrails • Lane Boundaries •3rdGuardrails level = geometry description level detail: 3geometryrd level = geometryof road, lane description and lines level detail: geometry of road, lane and lines lines and boundaries Lane #3: Lane #2: Lane #1: normal normal normal © Wikimedia Commons, licensed by CC-by-SA 2.5 Flament | Automated Vehicle Symposium | July 2017 11 ADASIS Forum Membership & Steering Board From 46 to 52 ADASIS Forum Members (updated 31 may 2017) Vehicle Manufacturers (16) ADAS Suppliers (15) Navigation System Suppliers (13) BMW Autonomos AISIN AW China FAW-RDC ** Continental Automotive * Alpine CRF (FCA) ** CTAG Autoliv Daimler * Denso Elektrobit Automotive Ford * dSPACE Garmin Ford-Otosan Fujitsu Ten (Europe) ** Harman Honda * Hitachi Mappers Co. ** Hyundai Motor Company Ibeo Mitsubishi Electric Europe Jaguar IPG MXNAVI Opel * LG Electronic NNG LLC Nissan Magna Electronic Europe Panasonic Renault Magneti Marelli Robert Bosch GmbH* Toyota Motor Corp. Novero Telenav Volkswagen TRW (ZF) Volvo Car Corp. Valeo Volvo Tech. Dev. Corp. Map & Data Providers (8) * Steering Board Members AND AutoNavi Holding GeoDigital Automotive** Here * ** New Members since June 2016 Navinfo Co TomTom* Wuhan Kotei Informatics** Zenrin Flament | Automated Vehicle Symposium | July 2017 14 Automated driving data chain and ecosystem Reference architecture proposed by OADF N NDS A - - - - -- - - INFRASTRUCTURE - - - - - - - - - - - - - - - - - - - - - - - - - - - - VEHICLE - - - - - - - - - S T Backend (one or multiple) operated by Map supplier / OEM / 3rd Party ADAS (Local) Sensors (V2x) provided) OEM-specific Backends Horizon Sensors Provider Live Map Updates N (Dynamic Data) T Live Map N Local Live Map Delivery Maps & Updates T (Dynamic Data) A Environmental Model N N HD Map (Dyn.) Data Production Delivery HD Map A Analytics/Sensor Fusion Localization Data Collection Strategy Infotainment Map Delivery Infotainment Map N A Systematic Data Community Data Collection Store S S Data Store (Mobile Mapping) Data Collection (raw or pre-processed) S Flament | Automated Vehicle Symposium | July 2017 15 INTRODUCTION TO SENSORIS Flament | Automated Vehicle Symposium | July 2017 16 SENSORIS: Sensor Ingestion Interface Specification Standardization of sensor data content Vehicle-to-Cloud / Cloud-to-Cloud o Sensor manufacturers o Car manufacturers o Location-based services provider o Mobile network operators Part of Open AutoDrive Forum o Focus on Sensor Data up- stream o Alignment with NDS, ADASIS, TISA Flament | Automated Vehicle Symposium | July 2017 17 SENSORIS architecture: Multi-role model Flament | Automated Vehicle Symposium | July 2017 18 Use Case: Real-time services Traffic flow Hazard warnings Environmental Traffic signage Traffic incidents conditions Flament | Automated Vehicle Symposium | July 2017 19 Use Case: Map maintenance • Road geometry and attributes • Lane geometry and attributes • POI entries and exits • Road condition Flament | Automated Vehicle Symposium | July 2017 20 Use Case: Statistical analysis • Historical and real-time data analysis • Personal preference learning • POI recommendations Flament | Automated Vehicle Symposium | July 2017 21 SENSORIS Members ADAS manufacturers Navigation System Suppliers Vehicle manufacturers Elektrobit Automotive GmbH Audi AISIN AW Harman Daimler AG Continental Automotive GmbH Hyundai Mnsoft Jaguar Land Rover Limited DENSO NNG Volvo Car Fujitsu Ten (Europe) GmbH PIONEER Co. Other LG Electronics Robert Bosch Car Multimedia ICCS GmbH Valeo Comfort and Driving Assistance In process to join Sensor & Component Location content & Service providers BMW AG Manufacturers CTAG AutoNavi Software Co. Ltd. Qualcomm Delphi HERE Global B.V. Telecom & Cloud Infrasrtucture Ericsson Nissan INRIX Inc. Providers Tass International IBM NavInfo Co.Ltd. TeleNav Toyota TomTom International B.V. Trafikverket Zenrin VTT Wuhan kotei informatics Flament | Automated Vehicle Symposium | July 2017 22 Conclusions • ADASIS and SENSORIS are both industry-wide specification initiatives facilitating the use of map data in automated vehicles • ADASIS V3 transforms the map information into relevant data for the Automated Driving functions • SENSORIS gathers vehicle sensor data to make it accessible in the cloud for various real-time, historical and statistical purposes • ADASIS and SENSORIS are part of the Open Auto Drive Forum Flament | Automated Vehicle Symposium | July 2017 23 Flament | Automated Vehicle Symposium | July 2017 24 HERE Digital Infrastructure Technologies Autonomous Vehicle Symposium July 11, 2017 A history of transforming maps into location technology 2015 3 new Investors 2011 1st pure 2009 location 1st map for Predictive Cruise Control cloud High-precision data collection and map-building technology Use of sensor data for map building 2007 Community 2004 mapping 1st map for ADAS Offline maps 1st map for phone for mobile 1985 1994 1st map for Adaptive Navigation 1st map for in-car nav Cruise Control Technologies 1st map for web founded HERE Technologies © 2017 HERE HERE Reality IndexTM Location & POIs Beyond roads Things People Spatial/aerial HERE
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