Jean-Marc DAVID — Renault — AI & Mobility Challenges & Opportunities for the Automotive Industry

AI & Mobility Challenges & Opportunities for the Automotive Industry Jean-Marc David Expert Leader Artificial Intelligence Groupe Renault

SophIA Conference - 8th November 2018

SOPHIA CONFERENCE

8TH NOVEMBER 2018

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AGENDA

01 02 03 04 SOPHIA CONFERENCE

AI at Renault: a global picture

Delivering robust & safe autonomous vehicles

Mobility services & robo-taxis

Conclusion; Q/A

8TH NOVEMBER 2018

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01 AI AT RENAULT: A GLOBAL PICTURE

The AI lanscape today (simplified)

Chatbots for customer relationship

Chatbots for user support

Optimized design

Interaction with other road users

Virtual Personal Assistant

HMI for occupants

Driver & occupant behavior Monitoring

Planning and sheduling

Mobility service operations Usage-based design

Decision making & navigation

Quality data analysis

AI is everywhere !

Predictive models

Perception

Personalized services (e.g. predictive maintenance)

Computer vision for intelligent manufacturing

Social media analysis

Off-board analysis of recorded data

Mobility needs analysis & demand prediction

Advanced Knowldedge & Content Management

R&D SOPHIA CONFERENCE

Manufacturing & Supply Chain

Sales & Marketing 8TH NOVEMBER 2018

Virtual simulation & (re)validation

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Connected Services & Mobility Services

Autonomous Vehicles 3

01 AI AT RENAULT: A GLOBAL PICTURE

With 2 main drivers: AV & big data

Chatbots for customer relationship

Chatbots for user support

Optimized design

Interaction with other road users

Virtual Personal Assistant

HMI for occupants

Driver & occupant behavior Monitoring

Planning and sheduling

Mobility service operations Usage-based design

Decision making & navigation

Quality data analysis Perception Predictive models

Personalized services (e.g. predictive maintenance)

Big Data Computer vision for intelligent manufacturing

Social media analysis

Off-board analysis of recorded data

Mobility needs analysis & demand prediction

Advanced Knowldedge & Content Management

R&D SOPHIA CONFERENCE

Manufacturing & Supply Chain

Sales & Marketing 8TH NOVEMBER 2018

Virtual simulation & (re)validation

‌

Autonomous Vehicles

Connected Services & Mobility Services 4

02 AUTONOMOUS VEHICLES

Why is it very difficult Non-critical applications

Critical applications

Autonomous systems

e.g. Go game

Autonomous Vehicles

Decision-support systems

e.g. customer analysis

e.g. medical diagnosis

• Technology challenge: robustness is more important than performance - and has to be assessed (resilient to condition disturbances, that cannot be fooled…)

• Business challenge: value / cost

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02 AUTONOMOUS VEHICLES

Why and where is AI required for Autonomous Vehicles ?

Interaction with other road users Interaction with occupants

Interaction

Driver & occupant monitoring

Decision making & navigation

Embedded intelligence Perception

Off-board analysis of recorded data

Off-board analysis and simulation

Virtual simulation & (re)validation SOPHIA CONFERENCE

8TH NOVEMBER 2018

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02 AUTONOMOUS VEHICLES

Perception

Interaction with other road users

• Object recognition (massive use of deep learning)

Interaction with occupants Driver & occupant monitoring

• Fusion between different types of sensors (e.g. fusion of a camera, in red, with a LIDAR, in blue)

Decision making & navigation

• Situation understanding

Perception

Off-board analysis of recorded data Virtual simulation & (re)validation

SOPHIA CONFERENCE

can we ‘understand’ all situations with deep learning only ?

8TH NOVEMBER 2018

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02 AUTONOMOUS VEHICLES

Decision Making

Interaction with other road users Interaction with occupants Driver & occupant monitoring

Decision making & navigation Perception

Off-board analysis of recorded data

• The most critical part to ensure robustness and safety of AD • Various AI techniques - in combination with other methods • Bayesian methods / POMDP • Rule-based systems • Constraint satisfaction techniques • End-to-end learning (?)

• …

• Solutions must be ethical, trustable and explainable

Virtual simulation & (re)validation

SOPHIA CONFERENCE

8TH NOVEMBER 2018

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02 AUTONOMOUS VEHICLES

Interaction with occupants; driver & occupant monitoring

Interaction with other road users Interaction with occupants Driver & occupant monitoring

Decision making & navigation Perception

• Cognitive attention assessment before take over • Behavior monitoring to ensure safety of people & goods in driverless-vehicles

Off-board analysis of recorded data Virtual simulation & (re)validation

SOPHIA CONFERENCE

• Explanation of vehicle perception & decision to ensure trust 8TH NOVEMBER 2018

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02 AUTONOMOUS VEHICLES

Interaction with other road users

Interaction with other road users Interaction with occupants Driver & occupant monitoring

Decision making & navigation Perception

Off-board analysis of recorded data

• Road users (vehicles, pedestrian…) are constantly interacting and negociating at a very local level • E.g. lane insertion / changing, intersection crossing…

• Interaction and negociation require modelling the alter perception of the situation, predicting intents and behaviors…

Virtual simulation & (re)validation

SOPHIA CONFERENCE

8TH NOVEMBER 2018

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02 AUTONOMOUS VEHICLES

Virtual simulation & (re)validation

Interaction with other road users Interaction with occupants Driver & occupant monitoring

Decision making & navigation Perception

Off-board analysis of recorded data

• Physical validation (& revalidation) with millions of km is not an option • Virtual simulation requires realistic models of sensors, driving & traffic simulation

Virtual simulation & (re)validation

SOPHIA CONFERENCE

8TH NOVEMBER 2018

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02 AUTONOMOUS VEHICLES

Off-board analysis of recorded data

Interaction with other road users Interaction with occupants Driver & occupant monitoring

Decision making & navigation Perception

Off-board analysis of recorded data

• Automatic analysis & labelling of data (cost & quality of labelling) • Situation clustering & scenario building from real data

Virtual simulation & (re)validation

SOPHIA CONFERENCE

8TH NOVEMBER 2018

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03 MOBILITY SERVICES & ROBO-TAXIS

Robo-taxis: why is it different from AD

• A shift from car ownership to MAAS (Mobility as-a-service)

• A new business for OEM: operating mobility services • Driverless cars • A different business model enabling more embedded technology • Localized services: cooperation with territories, public transport operators & the infrastructure

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03 MOBILITY SERVICES & ROBO-TAXIS

FOT

Several on-going Field Operation Tests to experiment Ride Hailing with AD level 4

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03 MOBILITY SERVICES & ROBO-TAXIS

Collaboration with the infrastructure

Intelligent infrastructure for robo-taxi FOT (Rouen & Saclay)

Roundabout in Rambouillet equipped with cameras to ease AV decision making (TORNADO FUI project)

SOPHIA CONFERENCE

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03 MOBILITY SERVICES & ROBO-TAXIS

And new products

EZ-ULTIMO EZ-PRO

EZ-GO

2018 Paris Motor Show the trilogy of shared mobility according to Groupe Renault

SOPHIA CONFERENCE

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03 MOBILITY SERVICES & ROBO-TAXIS

AI & New Mobility platforms – the next step

• Providing a global multimodal mobility service • Will become the unique contact point with mobility customers • A system of systems, integrating various services & data sources • With ‘AI inside’: • mobility need forecasts • planning & dynamic replanning • understanding user preferences • ...

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04 CONCLUSION

Final remarks The Automotive industry will be more disrupted in the next 5-10 years than it has been in the last 100 years…

And AI is raising hype (again)…

Some conditions for a successful deploiement of AI ▪ We need to explain opportunities and limitations – and build competencies ▪ We need to develop a ‘trustable’ AI (explainable, transparent, robust…) that probably requires to combine deep learning with other kinds of reasonning

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Editor-in-Chief: Prof. Frank Kirchner, DFKI / University of Bremen Associate Editors: Prof. Andreas Butz, LMU Dr. Jean-Marc David, Renault Group Prof. Malik Ghallab, LAAS-CNRS

Prof. Randy G. Goebel, University of Alberta Prof. Donia Scott, University of Sussex Prof. Oliviero Stock, FBK/ICT IRST Prof. Paolo Traverso, FBK/ICT IRST Aims and Scope

A new fully open access journal from Springer Nature aiperspectives.springeropen.com

• AI perspectives will cover the application of AI in industry, healthcare, transport, education, social sciences and humanities and business and economics.

• Strict high-level selection process to ensure an excellent publication quality.

• Publication of innovative applications of artificial intelligence with focus on: o An in-depth description how basic research enabled the application o How applied research triggers new questions for basic research o How integration of various AI Methods in application can be achieved • Interaction of data driven vs. model driven AI • System oriented and integrated research • Focus on responsibility/ethics of AI, explainability and transparency