Getting Started with Sensor Data for Autonomous Cars:

Sensor Fusion Part 2Session Four: Sensor Fusion for Vehicle Cognition

Webinar Overview

1) Sensor fusion brief intro and recap2) Atlas Devkit video3) Questions4) Integrating HD Semantic Map with the Autonomous Car

Cognition for Cars

Hardware Abstraction Layer (HAL)

GPS

IMU

LiDAR

Localization in 6 dimensions

3D SemanticMapping

Augmented Reality Maps and Context

Civil Maps Products

Point Cloud

Civil Maps Block Diagram (1 of 2)

Radar

Camera

LiDAR

Civil Maps Prior Map around vehicle (Context)

Civil Maps Block Diagram Part 2 of 2

Real-time map validation and state detection

Decision Engine and Actuation

Detailed queries of map:“How far until the intersection?”

HD Semantic Map: A SensorUsing the Map in Sensor Fusion

● Output validation● Optimize resource usage with foveation● State detection (signal light red, yellow, green)

HD Semantic Map: A MapRoute Planning

● Lane by lane instructions between waypoints● Alternative routes in case of unpredicted event● ‘Near clipping distance’ semantic map refreshed at desired frequency

Driveable Area and Speed Control

HD Semantic Map: A Map

● Recommended drivable area from aggregated observable path

● Real time feedback on vehicle position within the drivable area (Safe->Warning->Emergency)

● Drivable path and routing direction for Steering control

● Essential Map data for Speed Control○ Speed limit ○ Cross slope○ Lane width○ Distance to event trigger○ Aggregated trip statistics

Questions & Comments

● Webinar videos & documentation○ YouTube Playlist○ Slides○ GitHub code

Coming Soon:

After Webinar - Happy Hour San Francisco, CA

111 Minna Gallery, San Francisco, CAToday, 6/29 at 6:00 PM PST

The Future of Transportation World Conference, Cologne, Germany

Ensuring Safety & Building Trust in an Autonomous World Sravan Puttagunta (Co-founder) - July 5 - 6

Autonomy - The Urban Mobility Summit, Paris, France

October 19 - 21

Upcoming Events:

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