1. Digital Map Data from Vehicle Probes
Yuka Gomi
Ygomi LLC August 7, 2001

2. Vehicle Usage of Map Data
Established uses
Vehicle navigation using a CD, DVD or other media
Emergency roadside assistance
Off-board telematics services
Emerging uses (this decade)
Advanced Driver Assistance Systems (ADAS)
Traffic - aware dynamic route guidance
Situational awareness for driver workload
Eventual uses (next decade)
Active safety products
Collision avoidance
Road departure prevention

3. ADAS Applications That Will Use Map Data
Adaptive Cruise Control
Adaptive Light Control
Night Vision
Transmission Assistance
Intersection Collision Warning
Lane/Road Departure Detection and Warning
Front and Rear Collision Warning
Braking and Stability Control Assistance
Increase Fuel Efficiency

4. Digital Maps for ADAS Digital maps will play a major role in ADAS
Comprehensive view of possible paths
View of desired path according to
Programmed route from the navigation system
Inference from driver indications
Driver intent input to sensors
Knowledge of road conditions ahead

5. What Map Data will Bring
Prediction Capability
Preview of up-coming curves beyond the driver’s line of sight
Curve shape
Curve direction and radius
Potential maneuvers and decision making points (e.g., intersections)
Road characteristics and special attributes
Road type (highway, highway ramp, local roads, etc.)
Lane number, width, and type, speed limit, road grade, etc.

6. Situational Awareness (1)
Database provides a picture of the road ahead relative to vehicle location
Busy / dangerous intersections Predicts lane changes & merges

7. Situational Awareness (2)
Map data provides a picture of the road ahead to help understand the type of driving environment and level of attention required by the driver currently and in the next minute.
Analysis and continuous monitoring of the vehicle’s environment provides an understanding of what the driver is doing and should be doing. This information provides priorities for vehicle functions in situations where the driver might be surprised or over his/her task management ability.
What is the driver doing besides driving (e.g., talking on the phone, receiving directions, listening to the radio)?
What are the conditions that the driver is facing (e.g., wet pavement, rain, darkness, winding roads, hills, fog)?
What are the impending conditions that will be added to the driver’s workload (e.g., hidden intersection, stop and go traffic, complex exit)?

8. Situational Awareness (3)
Map data and information from monitoring the driving environment can be combined to dynamically determine
Is the driver in hectic stop and go traffic with many cars cutting in and out of the lane or in a low pressure country road driving the speed limit?
Is the driver entering or exiting an expressway or about to merge on a busy road?
What is the driver doing and how much more can she/he handle?
Should an incoming cellular call be held for a few seconds until the driver is through the upcoming interchange merge?

9. Situational Awareness (4)
All on-board functions must interrelate via the vehicle network
Communication between functions is essential for a comprehensive understanding of the road situation to allow
Simple human interfaces
Straightforward request entry
Easy to use answers
Safe human interfaces
Prevent use when the driver is exceeding a safe speed
Defer phone ringing as the driver is negotiating an icy turn
Careful integration of functions ensure that the driver has attention capacity left to spend on safe driving
Result is a situationally aware vehicle
Can control demands on the driver
Can regulate the driver’s use of information, entertainment, telematics, phone, etc.

10. What the Vehicle Sees Hidden intersection Left lane of 3 lane road
Traffic incident
middle lane
Merging traffic on
entrance ramp
Reduce speed to
50 kph ahead
124m: left curve
375 m ahead

11. Sample Of Predictive Map Capabilities
Tunnel
Bridge
Start&End Points 30 50
Stop
Change of
number of lanes
radius
Forest
seg01
seg03
seg02
seg11
seg09
seg10
seg12
seg08
seg04
seg13
seg15
seg07
seg06
seg05
seg14
Nodes
Shape points
Electronic horizon
Node A

12. Road Preview and Path Prediction (1)
Map data enables vehicle applications to preview the road ahead
Configuration of the road (e.g., curvature and curve radius)
Attributes along the road (e.g., speed limits)
Future predicted position of the vehicle
Map data and centimeter accurate positioning allow vehicle applications to
Use upcoming road conditions
Calculate data relevant to vehicle functions
Optimize performance in various road situations

13. Road Preview and Path Prediction (2)
Knowledge of the vehicle’s current and near future situation can allow the vehicle to prevent accidents:
Intersection collision avoidance
Forward collision avoidance
Lane departure prevention
Road departure prevention

14. Technology Trends
Map data collection technology enhancements by using probe data from vehicles
Improved location accuracy and reliability
Improved reliability of data at a reduced cost
Vehicle technology enhancements
Improved sensing capabilities
Improved vision capabilities for extraction of accurate data from road scenes

15. Data Feedback Loop for Updating
Probe data operations will handle map data exceptions generated by vehicles
Updates are applied to the data as part of core data collection when validated
Direct access to the most up to date data available
Raw data
feedback
Probe Data
Operations
Map updates
Content
Suppliers
Location
Based
Services
Provider
Qualified, updated
map data and
location based content
Vehicle as a
data probe
Automotive
Service
Provider

16. Data Feedback Loop Vehicles as probes leads to
Current, highly accurate data
Increased reliability
Data that can be gold plated
Vehicles as probes results in
Continual improvement in data reliability
Increase in content
Evolution of dynamic data for active safety functions

17. Consortium Activities
Next Map (European Project) - Started January 2000
Project purpose is to evaluate the technical and commercial feasibility of enhanced map data for safety applications.
Vehicle manufacturer partners: BMW, DaimlerChrysler, Fiat, Jaguar, Renault
Enhanced Digital Map (EDMap) (USDOT sponsored IVI Project) - Started April 2001
Project purpose is to determine safety application performance improvements and extensions using enhanced map data.
Vehicle manufacturer partners: DaimlerChrysler, GM, Ford, Toyota

18. Conclusions Usage of map data is moving beyond navigation.
ADAS applications are part of this trend.
Safety applications will require a central map server for timely creation and delivery of map and location based data updates.
The need for up-to-date road network data requires the use of vehicles as probes.
Situational awareness can provide data relevant to driver workload.
Vehicle manufacturers will have complete, accurate map data.

19. The Vehicle Manufacturers Will Know
Road usage
Current traffic
Predictions
Road geometry for every road
Precision to a few centimeters
Lane configuration
Road edge
Shoulder
Road conditions for every road
Pavement status
Detailed by lane, shoulder, edge
Change
Failures and damage
Surface (icy, slippery)
Micro weather
Temperature
Precipitation
Road furniture for every road
Every sign
Sign removal

20. The Future of ITS
Christine M. Johnson

21. Everyone needs data! Precision Weather Response
Military -- Cutting deployment time from 60 days to 72 hrs.
Growth in Costal evacuation needs
Precision Weather Response
National Park Management
Everyone needs data!
Precision Medical Response

22. Data

23. A Public Private Partnership
Themes for reauthorization: Data
From Spots of data
To a nationwide network of data
A Public Private Partnership

24. Data Available Nationally From Vehicle Manufacturers in Ten Years
No infrastructure
Can be made available through a public private partnership with DOT
Can be used for
Traffic management
Maintenance
Response
Planning