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

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

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

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

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.

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

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)?

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?

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 email 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.

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

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

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

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

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

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

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

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

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.

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

The Future of ITS Christine M. Johnson

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

Data

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

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