The Local Dynamic Mapa data store for cooperative applications

Nic SmithNAVTEQ

Royal Institute of Navigation: Nav 09 LandNPL, 19 November 2009

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• Co‐operative Systems •The LDM Concept• LDM Requirements• LDM Structure • LDM Architecture• The LDM API • Challenges for a map maker• Building the LDM

Contents

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Co-operative Systems

Co-operative systems are ADAS applications that communicate with each other

Essential Elements:Communication

•Exchanging data via ad hoc networksPositioning and object recognition

•Using auxiliary data input to enhance positioningData Processing, Fusion and Storage

•Managing the Perception Horizon around Vehicles and Road Side Units

PurposeEnabling Safety and Efficiency applicationsUnderstanding the local neighbourhood and predicting potential conflicts and hazards

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Co-operative Systems

Image Source : CAR 2 CAR Communication Consortium

Each Vehicle and Road Side Unit maintains an LDM containing the current state of its surroundings

The LDM Concept

MapDynamicLocal

static

non-standard static

slowly dynamicdynamic

Dynamic data• Data needs to be added, removed and accessed quickly without 

compilation of binary data. • Relational database approach 

Geometry• Features are defined with geometries (e.g. sidewalk, pedestrian crossing, 

traffic island)• LDM has to support spatial queries to find objects within range of a sensor 

and to find non‐navigable entities (e.g. area/point landmarks)Structure

• 4 layer structure with increasing dynamics• Structure and content defined by object model and database schema• Additional relationships and communication tables

2 Implementations• NAVTEQ – based on SQLite (NT‐LDM)• Bosch / Tele Atlas – based on Postgres (PG‐LDM)

LDM requirements

LDM structure

pointlandmarksreferencetracksroadelementtrafficlighttrafficsign

arealandmarks crossingcrossingsignalgroup sensordetectionarea junctionlinelandmarks rsu

non‐standard static map data

slowly dynamic data

dynamic data

accidenthotspotdynamicblackspotdynamicsensorattributesdynamicreferencetrackattributesdynamicroadelementattributes

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3

4

dynamictrafficsignenvironmentaleventfcdeventmeteodetectiontrafficevent

egomotorvehiclemotorvehicleuo (unidentified object)trailer

Conceptual objects

Moving objects

Non‐standard static features

standard static data1Standard static features

roadelement junctions

NT‐LDM

Map Access Layer SQLite Library

LDM Level 2 API

Communication Layer

PG‐LDM

PostgreSQL

LDM architecture

NAVTEQ Implementation Bosch/TeleAtlas Implementation

LDM Level 1 API

LDM Server

LDM Client

Applications

The LDM API

A Simple Client Server Programming Interface

Low Level (Level 1) API• SQL like queries allowing direct access to the LDM content with the 

database schema

query.query(“alongroadelement”,”long_offset”,”movobj_id=1”);

Higher Level API• Predefined queries for specific use cases• Applying map maker knowledge of database to acquire result

Std::list<LDM::NetworkRoadElement> nrel = l2query.getNextRoadElements(3, LDM::DIR_TRAVEL_POSITIVE, LDM::VT_ALL_VEHICLES, false);

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Challenges for map providers

Higher precision• Current resolution of map databases is 10 microdegrees, which roughly 

corresponds to 1.1 m longitude and 0.7 m in latitude at 50o latitude• Sub‐meter accuracy required for lane‐level positioning

• Lane centre lines and reference tracks

Navigable Map• Richer data model and specification• Enhanced intersection navigation with static reference tracks

New features• Enhanced map features including 

• Lane centre lines• Enhanced lane markings and stop lines• Curbs and roadsides• Bicycle and pedestrian paths and crossings

• Common access API

Building the LDM

Roadelement ‐ junction ‐ Referencetrack ‐ Arealandmark – Linelandmark ‐ Pointlandmark

Example Applications (1)

Novel applications utilising the LDM 

• Visual lane level positioning• Using cameras to recognise the lane markings in the database and

perform lane level positioning within limited GPS coverage• Following is a demonstration of this approach from Chemnitz 

University of Technology

Visual Lane Level Positioning

Example Applications (2)

Novel applications utilising the LDM

• Real time Lidar scanning• Matching detected object to static objects in the map allows for

improved positioning and detection of unknown possibly hazardousobjects in the environment

• Lane Change Warning applications• Using knowledge of the location of approaching vehicles from 

behind to determine if it is safe to move into an adjacent lane.

Conclusion

• With the LDM, Safespot has proposed a common definition of static and dynamic data required for automotive safety applications

• It was demonstrated that multiple map providers can deploy their data in a common format with a harmonised access method• A change of map provider is transparent to the application 

developer

Finally….

Questions ?