Tag Archive: AGENDA Methodology

Jun
20

Nexyad Algorithms in Autonomous Vehicles

NEXYAD Automotive & Transportation Newsletter #23, June 20th, 2018

 


Nexyad Algorithms in Autonomous Vehicles

 
Headlines :

– ISFM selected Nexyad algorithms

– SafetyNex episode 6 : Five use cases when your eyes or sensors are not enough

– Broad Range Applications of Real Time Driving Risk Assessment

– Deep Learning for Onboard Applications: Hidden Trap

– SafetyNex and the “S” Curve Theory

– Congresses & Events

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ISFM selected Nexyad algorithms

 
NEXYAD is proud to announce that our Artificial Intelligence Algorithmes are used for Autonomous Driving Vehicles French High Tech Startup ISFM (Intelligent Systems for Mobility) selected Nexyad artificial intelligence algorithms for their Milla Smart Shuttle.
 
ISFM
ISFM is one of the companies selected by the Ubimobility 2018 program

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SafetyNex episode 6 :
Five use cases when your eyes or sensors are not enough

 
            SafetyNex can save your life part 1: Rainy Curve               SafetyNex can save your life part 2: Tight Curve

       SafetyNex can save your life part 3: Priority                   SafetyNex can save your life part 4: Stop Sign

SafetyNex can save your life part 5: Pedestrians Crossing

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Broad Range Applications of
Real Time Driving Risk Assessment

 
Driving risk is not predictable from the so called “black spots” location, or from only driving behaviour. Driving risk appears when driving behaviour is not adapted to driving context, and particular, to road infrastructure complexity. There is no inherently bad driving behaviour (it depends on WHERE you drive: a disused airport ? in front of a school ? approaching an intersection ? risk is different for all those case). There is no inherently dangerous infrastructure and all automotive projects that record “black spots” are doomed to failure : they are places where few drivers in the past had a driving behaviour that was not appropriate to infrastructure complexity, and they died in accident. Thousands, millions, of other drivers did not have any accident at this location. What will this information bring to YOU ? Nothing ! It is necessary to evaluate adequation of YOUR driving behaviour to infrastructure complexity.
An AI module does that 20 times per second: SafetyNex.
Driving risk computed by SafetyNex is a core notion with lots of different applications : car insurance, fleet management, commerce, ADAS, Autonomous Driving, Vocal Driving Assistants, …

SafetyNex Presentation Page

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Deep Learning for Onboard Applications: Hidden Trap

 
Now Deep Learning is used in onboard detection and pattern recognition applications. NEXYAD for instance uses Deep Learning in RoadNex (road detection without need of markings + detection of free space), and ObstaNex (obstacles detection).
But if you do not analyse your INDUSTRIAL project in detail, you may have bad surprises : everyone thinks he/she knows that the more numerous the training examples, the most accurate the KPIs. Let’s say you used 1 billion km to train and validate your Neural Network (NN) for computer vision. Now a new cam is launched on the market (32 bits per color, 10k) : If you want to use your NN, you will degrade quality of images and put them into your system. If you want to take advantage of your better camera, then you must capture 1 NEW billion km with the new cam and train a new NN.
NOT VERY INDUSTRIAL!
NEXYAD has developed a methodology to get same KPIs with a very picky compact database (easy to reshape the database with new sensors) : A.G.E.N.D.A. (Approche Générale des Etudes Neuronales pour le Développement d’Applications), published in scientific papers in the 90’s – yes – the 90’s by NEXYAD team.

Deep Learning Database Validation

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SafetyNex and the “S” Curve Theory

 
RELATIONSHIP BETWEEN DRIVING RISK AND ACCIDENT : THE “S” CURVE THEORY
Let’s say in a manufacture there is a very dangerous machine that may grind up your hand. If you are 10 km away from the machine, risk is “very” low. If you are 1 km away from the machine, risk is the same. If you are 10 m away from the machine … risk is still very low … but if you come closer (let’s say 10 cm), suddenly risk becomes high ! This is not linear. In road safety, the Artificial Intelligence algorithm SafetyNex estimates 20 times per second the driving risk you take, and many people ask about relationship between “risk you take” and “accident”. This relationship is not deterministic (probabilities must be used) : risk is not linked directly to accident but rather to accident frequency (or probability)… and the relationship is a non linear curve called a “S” curve as shown on the figure below. It is possible then to use it to alert human driver (Vocal Driving Assistants) or to control autonomous driving (Autonomous Vehicle) in order to keep risk under the threshold of the “S” curve or not too far after the threshold. SafetyNex was calibrated in order to have 95% of accident frequency just after the threshold (validated on 50 million km).



Click image to enlarge

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Congresses & Events

 
A.I. key of profitability Conference at TNP

TNP logo

This thursday 14th june, TNP, a consulting firm specializing in business transformation, inaugurated its new generation start-up accelerator! The audience follow interesting conference about Artificial Intelligence in Mobility field.

– Benoit Ranini, TNP : Introduction
– Philippe Giry-Deloison : Conseiller municipal de Neuilly sur Seine
– Stéphane Mallard : Artificial Intelligence, Get ready for disruption
– Juliette Girard, Renault & Adrian Pellegrini, Blue DME : Feedback on futuristic car dealership
– Gérard Yahiaoui, Nexyad : Intelligence on board with SafetyNex
– Demo and business dating with TNP Accelerator’s start-ups

Gerard Yahiaoui
Gérard Yahiaoui, CEO of Nexyad



The European Mobility Exhibition 2018

TP 2018

Transports Publics, the European Mobility Exhibition, is the not-to-bemissed biennial exhibition for all the key players in public transport and sustainable mobility from across Europe. Over 11,000 highly qualified participants come together over three days in Paris to discuss the latest innovations for urban, interurban and regional transport, as well as green mode transport.
Transports Publics is recognised as the leading European showcase for innovations in equipment, services and policies relating to the entire mobility sector, bringing together leading European decision-makers from transport and politics.

Smart-Vision

This year, we could see for the first time, the new technology for rear-vision on buses,coaches and trucks : the camera-based system instead of mirrors. We visited Vision Systems booth that is the first firm to propose such system with its Smart-Vision product.
Smart-Vision allows to save about 5% gas consumption, that reduces CO2 emissions; the cockpit screens for driver are much more efficient than mirrors, they eliminate sun glare or reflexion problems and of vehicles lights, and they increase visibility at night and tunnel conditions.
This solution has been integrated in Heuliez and Irizar buses as shown on the exhibition, and public transportation operators companies in Europe have already adopted Smart-Vision.
Vision Systems also shown a lidar perception system around vehicle called Savety-Front for collision avoidance.

Navya

The trend of 2018 was on electrification for buses in particular, and public transporation in general.
Autonomous pod or shuttle was not yet present except outside with Navya.

Lohr Pod
Cristal by Lohr



Autonomous Vehicle World Expo 2018 Report

Logo

For the third consecutive time the Groupement ADAS (cluster) was present to the Autonomous Vehicle Technology World Expo at Messe Stuttgart 5-7 june 2018. Intempora and Nexyad represented the french-canadian cluster sponsorised by Mov’eo Imagine Mobility.
Edition 2018 was quite good, we propose a focus on some companies we saw to the convention.

Nexyad_Veoneer

The Elektrobit industry experts came to share their experience on how to effectively manage a functional and open HAD software architecture on an adaptive AUTOSAR infrastructure. They were keen to demonstrate how the functional software architecture with open interfaces and software modules is integrated on a high-performance microcontroller using an AUTOSAR adaptive middleware. In addition to the functional challenges, the transmission of integrity levels of automotive safety could be explained to you. EB booth visitors could appreciate why the advantage of combining an open software framework for automated driving with a reliable operating environment reduces time-to-market due to fast integration and first system-level testing.

ESI Group is a leading innovator in the field of virtual prototyping software and services. A specialist in materials physics, ESI has developed a unique skill to help industrial manufacturers replace physical prototypes with virtual prototypes, enabling them to manufacture, assemble, certify and pre-certify their future products. Coupled with the latest technologies, ESI now wants to anchor virtual prototyping in the broader product performance lifecycle concept, which addresses the operational performance of a product throughout its life cycle, from launch to disposal. The creation of a hybrid twin, based on simulation, physics and data analysis, allows manufacturers to deliver more readable and connected products.

Sigra Technologies was exhibiting its autonomous driving system, its components and services called Deep Einstein. Its products range from drive-by-wire embedded systems to decision-making based on a deep neural network. The company believes that an approach based on deep learning is the best way to handle hard-to-solve cases using traditional algorithms. During the exhibition, Sigra presented its new system for the demonstration of autonomous driving.

StreetDrone is an ambitious UK self-driving startup with a rich automotive, motorsport and entrepreneurial DNA. The streetDrone team is passionate about putting the AV revolution into the hands of the many , not just the few, providing the platform , data management system and functional safety, thereby allowing businesses and institutions to focus on their own development goals without having to worry about the cost and complication of vehicle hardware and systems engineering. StreetDrone is enabling the next generation of engineering to be involved in what is the most exciting area of technology today.

Veoneer is a leading system supplier for ADAS autonomous driving AD and advanced brake control solutions, and a market leader in automotive safety electronics products. With one of the oadest product portfolios in the larket, Veoneer is the forefront of innovation in the current revolution of the automotive industry. Veoneer takes on the challenge of automation and human-machine tion as vehicles become increasly intelligent.

Elektrobit

Vector informatik is a leading manufacturer of software tools and embedded components for the development of electronic systems and their networking with many different systems from CAN to automotive Ethernet. Vector has been a partner of automotive manufacturers and suppliers and related industries since 1988; Its tools and services provide engineers with the decisive advantage to make a challenging and highly complex subject area as simple and manageable as possible. Worldwide customers in the automotive, commercial vehicles, aerospace, transportation and control technology industries rely on the solutions and products of the independent Vector Group for the development of future mobility.

The four algorithms products of Nexyad are now well known by automotive profesionals. Numerus companies worldwide integrated SafetyNex the on board Driving risk assessment in real time, combinable with the three camera-based modules: RoadNex for road detection (edges of road and bitumen free space); ObstaNex for obstacles detection (vehicles and pedestrians); and VisiNex for visibility measurement (fog and heavy rains detection, reliability, distance of visibility, etc.)

Groupement ADAS


MOV’EO Imaging Mobility Forum 2018

Imaging Mobility Forum by MOV’EO, June 7th 2018 at ESTACA, Campus Paris-Saclay.
“Innovation Hubs : a new deal for efficient mobility”

 
Luc Chatel - Rémi Bastien
Luc Chatel, PFA President                                             Rémi Bastien, Mov’eo President

 
– Mov’eo General Assembly – 2017 Management & Financial report
– Keynote : opening by Luc CHATEL, Chairman, French Automotive Industry & Mobilities, Former French Secretary of State for Industry
– Tech Sessions : Blockchain: the ultimate bypassing. New Eldorado for mobility or just a buzz?
Smart Grid: the key for electric mobility solutions ?
ESTACA’LAB research activities on intelligent, clean and safe transport
 
Conference : Innovation Hubs : a new deal for efficient mobility
– Introduction by Rémi Bastien, Mov’eo Chairman & Ludovic Busson, ESTACA Chairman
– Keynote : Richard Dujardin, CEO France, Transdev & Patrick Pelata, Chairman, Meta Consulting LLC
– Roundtable – European clusters :
Rémi BASTIEN, VP Automotive Prospective, Groupe Renault, Chairman of Mov’eo & VEDECOM Institute
Leo KUSTERS, Managing Director, AutomotiveNL
Maren LOUCHET, International Cooperation, e-mobil BW
Laura MORGAGNI, CEO, Torino Wireless

 
Groupement ADAS
Adaccess demo car                                             Groupement ADAS Booth


May
22

Deep Learning for Onboard Applications: Hidden Trap

DEEP LEARNING FOR ONBOARD APPLICATIONS: HIDDEN TRAP
Now Deep Learning is used in onboard detection and pattern recognition applications. NEXYAD for instance uses Deep Learning in RoadNex (road detection without need of markings + detection of free space), and ObstaNex (obstacles detection).
But if you do not analyse your INDUSTRIAL project in detail, you may have bad surprises : everyone thinks he/she knows that the more numerous the training examples, the most accurate the KPIs. Let’s say you used 1 billion km to train and validate your Neural Network (NN) for computer vision. Now a new cam is launched on the market (32 bits per color, 10k) : If you want to use your NN, you will degrade quality of images and put them into your system. If you want to take advantage of your better camera, then you must capture 1 NEW billion km with the new cam and train a new NN.
NOT VERY INDUSTRIAL!
NEXYAD has developed a methodology to get same KPIs with a very picky compact database (easy to reshape the database with new sensors) : A.G.E.N.D.A. (Approche Générale des Etudes Neuronales pour le Développement d’Applications), published in scientific papers in the 90’s – yes – the 90’s by NEXYAD team.

Deep Learning Database Validation