The document discusses the large amount of data generated by vehicle sensors and the challenges associated with managing that data. It notes that the average mid-range car will have 10 cameras by 2020 that provide 360-degree views inside and outside the vehicle. These cameras generate data used for applications like lane departure warning, collision avoidance, and driver monitoring. The document outlines the vehicle data lifecycle from initial collection and annotation to powering onboard autonomous systems to closing the data loop by sending analyzed sensor data back to cloud computing platforms. It aims to address how automakers can deal with the massive volumes of data required to enable semi-autonomous and autonomous vehicles.

1. HOW TO DEAL WITH
ALL THE DATA THAT IS
GENERATED BY THE
VEHICLE SENSORS?
Seán Gaines, Vicomtech-IK4. Bordeaux
20151007

2. How are We?
Applied Research Centre, founded in 2001, specialising in
ComputerGraphics, Visual Computing and Multimedia technologies
Location:
Paseo Mikeletegi 57
Parque Científico y Tecnológico de
Gipuzkoa
20009 San Sebastian
Spain
+34 943 30 92 30

3. Vroom Vroom…

4. Where is my Jet Pack?
 Semi/Autonomous driving by 2020?
 What do I get on the way?
 How can data and data analytics enable this?

5. What do consumers say the
want?
 Active Safety was requested by 78% of
respondents
 Assisted Driving by 77% of respondents
 Location-based Services by 67% of
respondents
 Alternatives to petrol engines by 65% of
respondents
 Digital-device integration by 64% of
respondents
 Connectivity by 60% of respondents*

6. What are the challenges?
 Loosing data
 On-board analysis of data
 “Data Factories and Tooling”
 Exploiting connectivity (closing the loop)
 Nailing the HMI nail on the head
 Product recall/liability
 Software security, safety and formal methods
 Car manufacturers and Tier 1s as Software
Houses
 Changes in how we learn to drive, privacy,

7. Where is the data coming
from?
 Outside: Lidar, Radar, Ultrasound, Cameras,
etc.
 Inside: Cameras, Mics, etc.
 Inherent: Engine and Vehicle Management,
Telemtry, etc.
 Elsewhere: V2V, V2i, Internet, 4G, etc.

8. What trends are creating
data?
 Lots….. But let’s look at just one. Cameras:
o The average mid-range car will have 10 cameras by
2020
o CMOS Image sensor market was valued at 8.4BN
USD in 2014
o 29.4 Million cameras sold to Automotive industry in
2014
o In 2020 the volume is estimated to grow to 102M units
p.a.

9. External Cameras - 360°
 Lane Departure Warning
 Collision Avoidance
 Blind Spot Detection
 Parking Assist Systems
 Pedestrian and cyclist Detection
 Road and Traffic Signal Detection
 Precise Lane Level Navigation
 Free Space Detection
 Local Dynamic Maps
 Road Osculation Detection

10. Internal Cameras - 360 °
 Fatigue Detection
 Drowsiness Detection
 Gaze Estimation
 Head Pose and Orientation
 Acoustic Environment
 Traits Analysis
 Gesture Analysis
 Driver Authentication

11. Data Fusion – beyond 720 °
 Event Detection and Prediction
 Scene Understanding
 Holistic Driving Models
 Risk Prediction
 Continuous Monitoring
 HMI Response
 Single Channel HMI fusing multiple ADAS
systems
 Personalised Driver Models

12. Vehicle Data Lifecycle
 Starting with Big Data and creating Big Data Technologies:
o Petabytes of Test Video, Mapping and Sensor data
o Annotation of video and data (on the Cloud please)
o Create new ADAS Algorithms and software
o The annotated video will be used to create ADAS algorithms and New Digital
Maps as validation of the value of the annotated datasets.
 Moving fromBig Data to “Little Big Data”:
o ADAS software is updated to your Car, GPS or Smartphone
o Vehicles do lightweight real-time analysis of sensor data using spare cycles on
on-board computer….. Lots of vehicles
 Closing the loop:
o Device and Car connectivity, in its analysed form will be sent back to the Cloud
o This data is passed through the data factory again closing the loop

13. A picture, please…

14. Questions?