FREE SPACE IN THE DIRECTION OF THE WHEEL ON SHORT DISTANCE (URBAN DRIVING APPLICATION) : ON A REGULAR COMPUTER ARCHITECTURE IN REAL TIME
RoadNex Short (free space detection in front of the car) runs on regular computer architectures (even on a smartphone). This module is made for fast sensor fusion with lidar and radar.
It works even on dusty roads, stones (image below), cobblestones, etc …
RoadNex brings interpretation (drivable surface), telemeter (radar; lidar, …) brings measurement precision (in mm).
No need for a big computer (it means deployment cost reduction).
This disrupts some electronics architectures big firms that try to convince car manufacturers to put their computers Inside cars, but they do not bring only computing efficiency (they do), they also bring additional cost, weight, heat, integration room need, etc …
RoadNex runs on a regular ARM chip (for instance) and may be the next generation solution.
The next generation autonomous POD (Shuttle) MILLA made by ISFM uses RoadNex and will be shown at CES Las Vegas in Jan 2019.
Come to see it.
Groupement ADAS on their booth at MONDIAL.TECH.
Many good contacts for NEXYAD : potential OEMs, and other kinds of integrators for our 4 Artificial Intelligence software modules :
. SafetyNex : real time Driving risk assessment
. VisiNex : detection of lacks of visibility (fog, rain, sand, snow, …)
. RoadNex : detection of road borders and detection of free space
. ObstaNex : detection of obstacles (cars, …)
NEXYAD is starting a new image capture campaign in the summer heat of Paris suburb. Those new captured videos will sample the issue of strong casted shadows and will show robustness of our two Artificial Intelligence perception algorithms RoadNex (road border detection even without markings and free space detection) and ObstaNex (obstacles detection).
Database of NEXYAD applies the methodology A.G.E.N.D.A. (Approche Générale des Etudes Neuronales pour le Développement d’Applications) that allows to train deep learning with a compact learning database (knowledge-based selection of learning and of validation examples) with much better performance than with randomly selected massive databases.
Yes it is possible ! …
NEXYAD can then re-train ANNs for a special cam for instance, very quickly, with real maths KPIs instead of poor « percentages » estimators of effectiveness and robustness.
Try our AI perception algorithms, it will change a few things :
. VERY robust detection
. low computer load consumption (runs on regular architectures)
. retrainable quickly is sensor technology evolves
NEXYAD will be present at Autonomous Vehicle World Expo 2018 in Stuttgart, June 5 – 6 – 7
Come to visit Nexyad on Groupement ADASbooth 2015/hall C
Discover our 4 Artificial Intelligence Algorythms for ADAS, Autonomous Driving and Telematics
SafetyNex : Real Time Driving Risk Assessment
Fusion of Digital Map with Sensors, combinable with RoadNex, ObstaNex and VisiNex
Artificial Intelligence giving Safety to your Driver Assistant or your Autonomous Driving Systems
VisiNex : Measurement and Score of Visibility
Detection of Lack of Visibility, Fog, Heavy Rains, etc… on front of Vehicle
Artificial Mono Vision Algorythm for Autonomous Driving & ADAS
NEXYAD Automotive & Transportation Newsletter #22, April 17th, 2018
4 disruptive AI algorithms for automotive mobility by NEXYAD
Headlines :
– SafetyNex episode 4 : Driving Risk Assessment for Automotive (Driving Assistant, ADAS, Autonomous Driving)
– CNEJITA Seminar on Artificial Intelligence: who will be responsible ?
– SafetyNex : driving robot maybe will mitigate human errors, but first they have to imitate good drivers
– « Theory of Water Flush » and Impact on the Prevention of Accidents for Autonomous Vehicles
– 4 disruptive AI algorithms for automotive mobility
The new video on SafetyNex, on board driving risk assessment in real time.
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CNEJITA Seminar on Artificial Intelligence: who will be responsible ?
April 10th, CNEJITA (National Company of Legal Experts on Computer Science and Associated Techniques) organized a Seminar, whose objective is to determine the responsibility in terms of artificial intelligence through the understanding of technology and the dialogue with the actors of the sector.
It is therefore around this theme of topicality and future which is the artificial intelligence that the best experts in terms of computing met at the Commercial Court of Paris.
AI: concepts, technological breakthroughs and new risks
– Understanding the Concepts and Landscape of AI – Jean-Claude HEUDIN (Artificial-Creature.com – Teacher Researcher in AI)
– IA: state of play and perspectives – Jean-Philippe DESBIOLLES (IBM head of France IA WATSON)
Roundtable – Which Expertise fo AI ? was animated by Serge MIGAYRON (Honorary President of CNEJITA)
– The acceptability and limits of IA – JA CAUSSE (CNEJITA Expert)
– The Autonomous Vehicle and Traceability of IA – Jean-Louis LEQUEUX (Former President of VeDeCoM Tech)
– Auditability and risk control in the design of an IA – Gérard YAHIAOUI (NEXYAD)
– Evolution of the world of insurance, towards an objective responsibility – Nicolas HELENON (Co-manager Firm NEO TECH Assurances)
Roundtable – The Legal Challenges of AI. Animation – A MEILLASSOUX (ATM Lawyers – President of AFDIT)
– Introduction to Classical and New AI Concepts by Law: Applicable Regime and Evidence – L SZUSKIN (BAKER McKENZIE Lawyer)
– Tort liability in the face of AI: adaptation of traditional categories or creation of a responsibility specific to AI? – P GLASER (Lawyer TAYLOR WESSING)
– Contractual liability in the face of the IA: risk management during the contractualization of an IA system – FP LANI (DERRIENNIC Associate Lawyer)
– Synthesis on the current legal landscape – G de MONTEYNARD (Attorney General at the Court of Cassation)
Gérard YAHIAOUI, CEO of NEXYAD
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SafetyNex : driving robot maybe will mitigate human errors, but first they have to imitate good drivers
BEWARE with the statistics : « 94% of severe personal damage accidents are due to human errors » doesn’t mean that you’ll save 94% of severe accident with autonomous driving : drivers do not only make mistakes they also drive well (1 accident every 70 000 km, 3 dead every billion km – OCDE) … It is important to study also good driving and near misses (when driver has the right behaviour to avoid accident or to mitigate severity)… That’s what NEXYAD did during 15 years of research programs on road safety ^^ (that led to SafetyNex). See image (if you do not provide the « green » features, you will lose lives more than you gain with your driverless car. Our AI algorithm SafetyNex was made for this.
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« Theory of Water Flush » and Impact on the Prevention of Accidents for Autonomous Vehicles
« THEORY OF WATER FLUSH » AND IMPACT ON THE PREVENTION OF ACCIDENTS FOR AUTONOMOUS VEHICLES
by NEXYAD
INTRODUCTION
Let’s suppose that the flush does not exist in our toilets, and then let’s suppose that engineers able to create complex systems or even « systems of systems » are consulted to invent it, and that they apply exactly the same method than they do in the field of ADAS and Autonomous Vehicles.
METHOD OF SCENARIOS
We propose to apply the method of scenarios, which consists in crossing all the factors that can modify the situation, then in each case of the complete combination, propose a solution. For this, it is necessary to note the number of possible shapes for the tank, the possible volumes, all the possible locations for the water supply entry, the possible diameters of the inlet pipe, the flow rates and possible pressures of water, the possible residual water levels before filling. We can generate the combinatorial of these factors, which allows us to generate all the possible scenarios of the « flush » problem. In each case, it is possible to give a solution, namely, the duration of filling of the tank (opening and closing of the water tap).
This approach is fully compatible with deep learning, which will also interpolate between two reference cases (quality of interpolation/generalization to be controlled, of course) if characteristics had to drift over time. Of course, the tank must integrate a system of sensors to evaluate the configuration (diameter of pipe, pressure of water, position pipe, capacity of the tank, etc …). We can use a camera, lasers, ultrasounds, etc. So that this recognition of situation is as accurate as possible. For such an approach, automation/control engineers talk about open-loop (feed forward) control because the data flow is as follows:
COST AND ROBUSTNESS OF THE SCENARIOS METHOD
It is easy to understand that the flush thus designed will be perfectly functional (there is no reason for it does not work), but for a high cost due to the sensors to integrate. Similarly, the robustness of the system to a measurement error or to a bad situation recognition is not guaranteed : we can very good to fill too much or not enough. The accuracy of the configuration case recognition is very important.
SOLUTION OF WATER FLUSH IN THE REAL WORLD
If you have the curiosity to disassemble your flush, you will notice that it is much simpler than the system described above: A float indicates when the water supply valve should be closed. The figure is as follows:
Automation engineers call this a closed loop control (servo control). The feed forward « open » control is reduced to « open the tap thoroughly without worrying about the flow of water, the volume of the tank, and turn off the tap as soon as the float asks for it « . Note that this method works regardless of the configuration of the flush : we do not even need to know the volume of the tank that can be modified (for example: by filling half of the tank with glass beads) without affecting the operation of the flush. It is a robust and cheap system.
TRANSCRIPT OF THESE REMARKS IN THE FIELD OF ADAS AND AUTONOMOUS VEHICLES: SERVO CONTROL IN DECISION
The information processing chain of the autonomous vehicle follows the general feed forward form :
NEXYAD has developed the SafetyNex system which dynamically estimates in real time the risk that the driver (human or artificial) takes. However, the autonomous vehicle may be functionally specified as follows:
« transport someone from point A to point B as quickly as possible, and safely. »
The « quickly » aspect is the historical business of the automobile. The « safely » notion integrates intrinsic safety of the system (its dependability: it should not explode, sensors or power supply may not be disabled, etc.), and since it is a vehicle, its ability to move with a good road safety, that is to say by « not taking too much risk in driving ». Since SafetyNex estimates this driving risk dynamically and in real time, it can be said that SafetyNex is a dynamic indicator of « SOTIF » (Safety Of The Intended Function). SafetyNex acts as a « driving risk float » : when the risk arrives at the maximum accepted level (like the float of the flush) we stop the action that raised the risk (example: we stop accelerating or we slow down). Thus, the response of an autonomous driving system is made adaptive (at the decision level) : even if the feed forward open loop is not perfect, it can correct itself to take into account, among other things, the instruction and the measure of driving risk. This system is completely independent of the automatic driving system in terms of information processing, so it represents redundancy of processing.
SafetyNex uses to estimate risk :
. risk due to inadequacy of driving behaviour to the difficulties of the infrastructure : navigation map, GPS, accelerometers
. risk due to inadequacy of driving behaviour to the presence of other road users (cars, pedestrians, …) : data extracted from the sensors (camera, lidar, radar, etc) such as « time to collision », « inter distance (in seconds) », number of vulnerables around, etc.
. risk due to inadequacy of driving behaviour to weather conditions: in particular to atmospheric visibility (fog, rain, snow, sand, penumbra). Knowing that when visibility is low, vehicle must pay more attention (and slow down) even if this autonomous vehicle is not impacted by the decrease in visibility (if it only uses a lidar for example) because the avoidance of an accident is done at the same time by the two protagonists : if one of them (pedestrian, human driver), does not see the autonomous vehicle, then it finds itself only to be able to avoid the accident, which doubles the probabilities of a potential accident.
. other
The use of SafetyNex allows to make adaptive an artificial intelligence of autonomous driving, on the following diagram :
If you have a lean computer, then you only apply one loop between t and (t+1) as it is shown on the figure. If you have a powerful computer, you can then even simulate a big number of decisions and take the less risky one (like automaticians do with predictive control systems). Of course, SafetyNex is only ONE way to close the loop (on a crucial notion : driving risk). This figure may be extanded to other variables of contol that make sense for an autonomous vehicle. More complex adaptation rules may switch from a decision to another if risk simulation shows that finally it is less risky (ex : slow down or turn wheel ?).
CONCLUSION
SafetyNex uses the map in addition to sensors (same sensors as the driving system or parallel tracks) and does not need to accurately identify the situation but instead to estimate a risk (this is a different task). SafetyNex is a knowledge-based AI system (knowledge extracted from human experts in road safety, from 19 countries – Europe Japan USA – who validated the system over 50 million km. Total research program duration : 15 years). This technology is still being improved, of course, but it can already be integrated into autonomous vehicles and avoid a large number of accidents by its ability to make the system adaptive to unknown situations. In particular, in the case of autonomous urban vehicles (autonomous shuttles, robot taxis), the adaptation of driving behaviour to complexity of infrastructure is made possible by SafetyNex, which decodes this complexity by reading the navigation map in front of the vehicle. SafetyNex makes the autonomous vehicle anticipate more by following « rules of safety » : with SafetyNex emergency situations (that still will need emergency braking and other emergency actions) become much more rare. Autonomous vehicle acts like an experienced cautious driver. Note : if you modulate Maximum Accepted Risk, then you modulate aggressiveness of the autonomous vehicle. This might make sense not to let the autonomous vehicle trapped in complex human driving situations (where the autonomous vehicle would stopped indefinitly).
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4 disruptive AI algorithms for automotive mobility
. ObstaNex detects obstacles with a simple cam (a la Mobileye).
What is disruptive ?
ObstaNex runs in real time on a regular smartphone… it means it doesn’t need a big computing power to run. It can be trained/re trained on a « small database » using the methodology A.G.E.N.D.A. (Approche Générale des Etudes Neuronales pour le Développement d’Applications or General Approach of Neuronal Studies for Application Development) – important is you improve your cam !
. RoadNex detects drivable part of the lane borders and free space.
What is disruptive ?
RoadNex works even in the Streets of old cities as Paris, London or Roma, and it runs in real time on a regular smartphone. it means it doesn’t need a big computing power to run.
. VisiNex detects lacks of visibility (fog, heavy rain, snow, sand storm …).
What is disruptive ?
VisiNex is an artificial vision tool which is correlated with human perception. If there is something to see, VisiNex is able to give a score of visibility. Except Daimler, we haven’t seen such a military background-based detection elsewhere.
. SafetyNex is the only fusion Artificial Intelligence algorithm (sensor + map fusion) that estimates driving risk dynamically and in real time.
What is disruptive?
SafetyNex allows to have an explicit value of driving risk. It is a total revolution for car insurers, fleet managers, and autonomous driving engineers. These algorithms are already under integration into products for telematics /connected car, ADAS, Autonomous Vehicle.
– Come to meet Nexyad at CES 2018 in Las Vegas – January 8-12
– NEXYAD giving the award of the best Insurtech startup «prix coup de cœur des assureurs 2017»,
organized by Cercle LAB (Laboratoire Banque Assurance) at Allianz Tower in Paris La Défense
– Nexyad invited speaker at UNESCO Conference on Artificial Intelligence : use case of autonomous vehicle
– SafetyNex driving risk assessment (20 times per second while driving): anticipation of danger
– INTEMPORA and NEXYAD, members of MOVEO Groupement ADAS interviewed on BFM Business (Major French TV)
– Bitumen Free Space Detection by Nexyad RoadNex module in real time on a Smartphone
– Nexyad on Groupement ADAS booth at Equip’Auto 2017
– Validation of ADAS Nexyad Database with ground reality
– Individual driving risk assessment and car insurance : what applications ? what business models ?
– SafetyNex can bring Artificial Intelligence into Autopilots in respect of ASIL ISO 26262
– Welcome to YOGOKO, new member of “MOV’EO” Groupement ADAS cluster
Come to meet Nexyad at CES 2018 in Las Vegas (Jan 8-12)
Nexyad invite you to visit us at the Leddar Ecosystem Pavillion at East LVCC – Central Plaza (booth CP-23)
If you want to reserve a meeting slot, please contact us at nexyadCES2018@nexyad.net
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NEXYAD giving the award of the best Insurtech startup « prix coup de cœur des assureurs 2017», organized by Cercle LAB (Laboratoire Banque Assurance) at Allianz Tower in Paris La Défense
Gerard Yahiaoui at Cercle Lab
Last year Nexyad won the special prize « Coup de Cœur » by french insurers of Cercle Lab with SafetyNex the driving risk assessment App in real time. For this, Gerard Yahiaoui CEO of Nexyad handed the 2017 new prize to the winner KAP-Code represented by Adel Mebarki. Kap-Code is dedicated to improve the care of chronic diseases and the detection of drug safety signals on social networks thruth 3 solutions : helping patients and health advisors with connected objects, Digital Health that allows profesionals to provide care for their patients and harnessing Big Data for science.
Adel Mebarki, head of innovation of Kap-Code
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Nexyad invited speaker at UNESCO Conference on Artificial Intelligence : use case of autonomous vehicle
Nexyad CEO Gérard Yahiaoui A.I. expert was invited to speak (invited paper) in a conference in Paris on Artificial Intelligence (JNI/IESF, Under the patronage of UNESCO, 2017 Oc 19). He talked about Artificial Intelligence for Autonomous Vehicle : « Intelligence Artificielle pour le Véhicule Autonome, et exemple de réalisation : SafetyNex ». Very interesting papers during this day showing a broad range of AI applications (automotive, fashion, HR management, Legal, …). More than 400 people in the audience.
Gerard Yahiaoui explaning difference between A.I. and complex automation for autonomous driving
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SafetyNex driving risk assessment (20 times per second while driving): anticipation of danger
SafetyNex estimates driving risk 20 times per second, during driving (real time).
On the following figure, you can see risk rising when approaching a stop sign with an inappropriate car speed :
Speed of the car is quite high before the STOP sign and Risk goes to the maximum with a vocal alarm to the driver which have time to slow down or brake to stop.
This estimation is computed INSIDE the local device (inside the car). Current implementation is on smartphones (IOS and Android), then computing of risk is completely done INSIDE the smartphone : that makes SafetyNex compliant with all driver’s privacy regulations and laws in Europe.
INTEMPORA and NEXYAD, members of MOVEO Groupement ADAS on BFM Business (Major French TV)
1st Nov 2017, the Tech & Co tv show on the subject : will self-driving car come sooner than expected ?
Nicolas du Lac & Gerard Yahiaoui
Nicolas du LAC, INTEMPORA, and Gerard YAHIAOUI, NEXYAD, presented their innovations and explained how the MOVEO Groupement ADAS helps to be stronger for their innovative startups.
Nicolas talked about RT-MAPS that is a software tool for R&D, making easy the task of developing applications with multiple sensors (cameras, lidar, radar, …) that of course are not synchronized and that must collaborate through algorithms of sensor fusion in order to get good objects detection and recognition.
Gerard talked about SafetyNex that is an onboard real time module that is the only module in the world that can estimate driving risk 20 times per second. Self-driving car can then know the risk it takes with and it simplifies the development of autopilot (example : « if risk too high then slow down »).
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Bitumen Free Space Detection by Nexyad RoadNex on Smartphone
RoadNex detects free space on road with negative detection of obstacles as vehicle on the video below.
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Nexyad present with Groupement ADAS at Equip’Auto 2017
Philippe Orvain, CEO of Nomadic Solutions
Nexyad was present with Groupement ADAS at Equip’Auto Congress in Paris. Groupement ADAS is a SME’s cluster : 10 companies with expertise in the field of Advanced Driver Assistance Systems, Connected car and Autonomous vehicle. Philippe Orvain CEO of Nomadic Solutions and competitiveness cluster MOV’EO Vice President has responsed to journalist Laurent Meillaud on Congress TV channel.
Watch Philippe Orvain interview on the congress channel with SafetyNex video demo :
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Validation of ADAS Nexyad Database with ground reality
Free space ground reality (for RoadNex) and obstacles ground reality (for ObstaNex)
The NEXYAD company is currently developing the construction of a database for the validation of systems of driver assistance and driving delegation, (ADAS and Autonomous car) using the AGENDA methodology published in the 1990s by Gérard Yahiaoui in the field of machine learning and artificial neural networks applications. Here is an example of ground reality : ground reality is needed in order to automate performance / KPIs measurement when you modify the perception system.(methodology initially intended to handle, among other things, the construction of learning databases and tests for the implementation of neural networks).
This database has two essential characteristics:
1) Real-life situations
Indeed, the AGENDA methodology recommends describing the possible variations of signals and input images as factors of variability and their crosses.
Example, for obstacle detection:
. weather (dry weather, sunny weather, rain, fog) . overall brightness (low, medium, high)
. vehicle speed (low, moderate, high)
. type of road (motorway, road with marking, road without marking, …)
. coating (bitumen 1, bitumen 2, …, pavers)
. day / night (car headlights and infrastructure lighting)
. season (spring, summer, autumn, winter)
. etc.
NEXYAD’s ambition is to propagate its methodological expertise and to enable everyone to evaluate the performance of vision systems for ADAS, be they systems developed by NEXYAD or others.
Individual driving risk assessment and car insurance : what applications ? what business models ?
As many people know now, NEXYAD has been developing the first real time driving risk assessment system called SafetyNex.
SafetyNex is currently available in B2B :
. as a smartphone App (Android and IOS)
. as a real time driving risk assessment API that OEMs and Insurers may integrate into their own smartphone App or into their own telematics or ADAS device (Android, iOS, Linux, Windows).
This real time driving risk assessment module has been validated on 50 million km, and applies proven methods for risk assessment, using, for instance, the Frank E. BIRD « safety triangle » concept, and running in real time a knowledge-based system AI that has been built by NEXYAD since 2001. It took 15 years to extract thousands of road safety knowledge atoms from experts of 19 countries. Some of this knowledge is directly operational, some is deep knowledge on detection theory (a mix of Information Theory and Knowledge on Human Brain abilities). And of course, SafetyNex also applies fundamental knowledge on mechanics (braking abilities, …) including complex issues such as grip for example.
Complex Automation MUST be ASIL ISO 26262.
Artificial Intelligence CANNOT BE ASIL ISO 26262 (by definition) and acts only on parameters of Complex Automation doing ++/– – variations, never skipping « reflexes actions » (emergency braking, etc), but allowing anticipation speed adaptation to reduce frequency of emergency situations (and then give more margin to reflexes actions and also improve comfort). Maximum acceptable Driving Risk can be changed depending on driving situation in order to set « aggressivity level» of HAV.
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Welcome to YOGOKO, new member of « MOV’EO » Groupement ADAS cluster
In november, cluster Groupement ADAS, from Mobility and Automotive R&D competitiveness national cluster Mov’eo, welcomed YOGOKO as new member. It makes eleven players like a football team, and we hope to score goals in the Automotive market competition.
YoGoKo is a startup company founded in 2014 by employees from three research institutes : Mines ParisTech, Telecom Bretagne and Inria. YoGoKo makes use of software developed in teams specialized in Internet technologies (RSM at Telecom Bretagne) and robotics (CAOR at Mines ParisTech and RITS at Inria). These research teams have been working together since 2006 on innovative communication solutions applied to Intelligent Transportation Systems. They contributed to several collaborative R&D projects related to ITS (CVIS, ITSSv6, GeoNet, DriveC2X, SCORE@F, …).
In 2012, these laboratories engaged together into the development of a common demonstration platform which comprises connected vehicles (fleet of conventional vehicles from Mines ParisTech and fleet of autonomous vehicles from Inria), roadside equipments and cloud-based services.
YoGoKo demonstration platform was finally revealed on Feb. 11 th 2014 during the Mobilité 2.0 event organized by the French Ministry of Transport. This successful demonstation and the extremely warmfull feedack gained at this occasion triggered the launch of YoGoKo as a company.
Nexyad invite you to visit us at the Leddar Ecosystem Pavillion at East LVCC – Central Plaza (booth CP-23)
If you want to reserve a meeting slot, please contact us at nexyadCES2018@nexyad.net
Nexyad was present with Groupement ADAS at Equip’Auto Congress in Paris. Groupement ADAS is a SME’s cluster : 10 companies with expertise in the field of Advanced Driver Assistance Systems, Connected car and Autonomous vehicle. Philippe Orvain CEO of Nomadic Solutions and competitiveness cluster MOV’EO Vice President has responsed to journalist Laurent Meillaud on Congress TV channel.
Watch Philippe Orvain interview on the congress channel with SafetyNex video demo :
– Road accident and driving risk are two different notions
– Nexyad at AutoSens Brussels 2017
– Enova Symposium Paris 2017
– Connected & Self-driving Car Meetup #9
– Academic chair at MOV’EO with INSA Rouen
– Sensor fusion and data fusion with SafetyNex
– SafetyNex : Understanding the Concept of Risk
– NEXYAD : the story
– Navigation Based ADAS : use SafetyNex to build ACC and anticipation (predictive) brake systems
Road accident and driving risk are two different notions
A lot of professionals that must cope with road safety observe accident through statistics : it seems to be normal to think that safety is low where there are a lot of accidents and that safety is high where there are few accidents.
This reality tends to make people confuse the two notions : risk and accident.
And since you stay at the statistic level, then it works : if 99% of people that played russian roulette more than 50 times have died (accident), then you can say that russian roulette is risky (risk).
Insurance companies, fleet managers, have taken into account those statistics, in order to estimate their future costs, and compute their pricing.
But now, digital connected devices are available at the very individual and local level : telematics (professional devices installed into cars), smartphones, connected car, can estimate the driving behaviour in real time and they know exactly where you drive.
Then, what this new technology brings to risk assessment ? and can you still apply at the individual level the ideas that was set at a population (statistics) level ?
That question was studied in 1969 by an American University Professor that was also a researcher for the company « Insurance of North America », Frank E. BIRD, and a key notion was then used : the « incident » or « near miss accident » or « quasi accident ». It was shown that the risk you take does not lead to accident but to « quasi-accident ». Indeed, even in very risky situations, accident can be avoided most of the time at the very last second ! Frank E. BIRD worked on what was called « The Triangle of Risk » or « Safety Triangle »
Sometimes, you do not have luck … and then you have an accident instead of having a quasi-accident.
Example of Statitical Relationship in Risk Assessment : from Behaviour to Fatalities
Then accident is the confluence of « risk you take » and « bad luck ». It is interesting to notice that, if you do not study the individual and local (in space and time) level, so if you consider a large population of drivers during a long duration, then « bad luck » automatically disappears… and so risk can be measured by observation of accident. But at the individual and local levels, risk cannot be measure by observing accident.
It is interesting to read about Safety Triangle and then have a clear idea of links between RISK, ACCIDENT, SEVERE PERSONAL INJURIES.
In road Safety concerns, researchers and experts have been working during 50 years on this concept of quasi-accident and they accumulated data and knowledge about this key notion. Let us resume the russian roulette comparison : pulling the trigger is the quasi-accident … and sometimes you die (accident). But even before playing such a « game » you KNOW that it is risky.
The knowledge of risk is represented by a collection of cause-effect relationships.
There is a knowledge-based artificial intelligence system that gathered the knowledge from road safety experts and researchers (that work mainly on road infrastructure) and that is now available in order to assess driving risk in real time : SafetyNex developed by the company NEXYAD. SafetyNex is the « thermometer » of driving risk and it alerts the driver BEFORE the dangerous situation, letting time to slow down and then potentially to avoid accident, to reduce severity (less personal severe injuries), …
Obviously, markets are :
. car insurance (prevention, severity, UBI)
. fleet management (prevention, reduction of costs, fit in regulations and laws)
But even the automotive can take benefit of suche a real time driving risk assessment module :
. intelligent navigation with risk vocal alerts
. automatic triggering of braking for ADAS (if risk too high then slow down)
. driverless cars : giving to the artificial intelligence that drives the car the perception of the risk it takes…
SafetyNex opens the door to a new generation of onboard applications for every field of automotive sector that is concerned with risk and safety. Read more
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Nexyad at AutoSens Brussels 2017
AutoSens took place at the AutoWorld Museum in Brussels September 19-21.
To answer the issues of Connected Cars and Autonomous Cars, engineers need first to give eyes, ears and A.I. to future vehicles. Sensors will play this crucial and difficult role of replacing the human senses.
Engineers and sensors providers met for three days of conferences and workshops.
Groupement ADAS was present with Leddartech the lidars canadian company that rose 100 M$ funding, New Imaging Technologies with their unique high dynamic range camera sensors, Intempora that provide famous RT-Maps, and of course Nexyad presented his three camera-based software modules for Road Detection – RoadNex, for Obstacles Detection – ObstaNex, for Visibility Measurement – VisiNex and SafetyNex – the Road Safety system with sensors fusion and data fusion (digital map, accelerometers, GPS, cameras, lidars, radars, ultrasounds, weather data, traffic data, etc.).
New players appeared as Crowdflower or Mighty Ai, they are plateforms that help you process your data or images very quickly by dividing the workload with very many people registered online.
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Enova Symposium Paris 2017
Round Table at ENOVA symposium in Paris, on the subject of self-driving car
(see from left to right)
. Vincent ABADIE, Vice-President Expert Leader Autonomous Vehicle and ADAS, PSA Group
. Jochen LANGHEIM, Vice-President advanced systems R&D programs, ST MICROELECTRONICS
. Jean-François SENCERIN, Autonomous Driving NFI/PFA Program Director
. Gérard YAHIAOUI CEO, NEXYAD
. Guillaume DEVAUCHELLE, Vice-President Innovation, VALEO
. Alain PIPERNO, Expert Safety & Autonomous Vehicle, UTAC
The audience could listen to this experts panel and ask questions about connected and driverless cars.
Journalist : Laurent MEILLAUD
ENOVA, Paris, Porte de Versailles
3 days of exchanges and conviviality at the service of Innovation + Business Meetings driven by THE NEW NEEDS OF CONNECTIVITY. Read more about the Event
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Connected & Self-driving Car Meetup #9
Nexyad was invited to the Connected & Self-driving Car Meetup #9 at Le Square (Renault’s innovation lab in Paris), on september 13.
Thanks to the perfect organisation of Laurent Dunys and Bruno Moncorge.
A large audience listened presentation about vehicles and data security with Nabil Bouzerna of IRT SystemX. Finally, Jean-François Menier, lawyer at Elyos Avocats gave a very interesting wrap-up about the potential responsibility of a driver in the case of a connected / self-driving car accident and of course about driver and passengers safety with SafetyNex App : real time driving risk assessment.
* * * * *
Academic chair : effective collaboration between MOV’EO groupement ADAS and INSA Rouen
MOV’EO Groupement ADAS built an academic chair with INSA ROUEN (option Intelligent Transportation) on ADAS and driverless cars.
The first course was given by Gérard YAHIAOUI, CEO of NEXYAD, the 13th of September 2017 in Rouen : presentation of key notions (near missed accident, driving risk), and presentation of SafetyNex (real time driving risk assessment) and applications to car insurance, fleet management, ADAS, and driverless cars.
* * * * *
Sensor fusion and data fusion with SafetyNex
SafetyNex is a real time driving risk assessment system. Of course, Driving Risk makes everyone think of car insurance and fleet management. And it is a natural application (deployment has already started). But it is important to note that Driving Risk is also a key notion for ADAS and Driverless car.
Indeed, Driving Risk happens when there is no adequation between Driving Behaviour and Driving Context. ADAS and Driverless act on Driving Behaviour :
. ADAS modifies Driving Behaviour : braking when the human driver did not, etc …
. Driverless car creates Driving Behaviour : there is still a driver called « artificial intelligence ».
Driving context is measured :
. Map Electronic Horizon
. GPS
. Accelerometers
. Times to collision (front and rear)
. Number of vulnerables around (even on sidewalks)
. Atmospheric visibility / weather condition (fog, pouring rain, etc.)
. X2Car Data Streams (accident, weather alert, construction area, etc.
So you can now imagine that if you have the opportunity to ESTIMATE adequation between Driving Behaviour and Driving Context, then you can build much more relevant ADAS and Driverless Artificial Intelligence (adequation or inadequation).
You may notice that Driving Context is measured through heterogenous sensors and data streams. It brings no difficulty to SafetyNex that uses Fuzzy Sets and Possibility Theory to estimate adequation, givin a Driving output called Driving Risk (that you should want to minimize under constraints of mobility efficiency).
Then SafetyNex is actually a sensor and data fusion system (high level fusion), much more efficient than every fusion systems that you ever developed, because it generates a variable (Driving Risk) that is a KEY NOTION for driving and is EASY TO UNDERSTAND AND USE.
NEXYAD implemented a low cost version with only the first 3 inputs (more than 5,000 road safety rules to cope with the infrastructure dangers …) and is now implementing simple rules to take into account mobile context. Example: « the shorter the time to collision, the higher the risk ». And that’s it ! The knowledge based artificial intelligence of SafetyNex automatically does the fusion with the 5,000 rules. There is no need to « weight » the rules, as possibility theroy allows a fusion with every rule competing with the others … Elegant applied maths to a problem that most engineers describe in a so complicated way that it becomes impossible to solve.
We really encourage ADAS and Driverless engineers to come to us and simply integrates SafetyNex (low CPU consumption, easy real time, etc.) and then get NOW a proven sensor fusion and data fusion system that works. This gives ONE dimension of Driving Systemic Analysis items: Driving Risk, in real time.
Of course, if you do the systemic analysis you will find other dimensions of interest (we let you do that, we’ve done it for ourselves, trace of the military research past of NEXYAD founders).
SafetyNex is now under implementation by big ADAS OEM companies. Series deployment will start in 2018. We will be glad to help you being a part of it.
* * * * *
SafetyNex : Understanding the Concept of Risk
SafetyNex App is a real time driving risk assessment. We present below 3 videos to explain as simply as possible the concept of driving risk.
Luck doesn’t change the risk that the driver takes. It means that risk taken by the « lucky risky driver » is exactly the same than risk taken by the « unlucky risky driver ». It is possible then to detect risky drivers before they have accident (anticipation of costs). Once detected, it is possible to train them (prevention program).
Because SafetyNex driving risk assessment is done in real time, it is possible to alert the driver (when risk is higher than an acceptable value), and if driver slows down, then risk never rises at the red level. It is an onboard prevention system (ADAS).
Observation of accidents on a short period of time (3 months for instance) may not show any difference between « cautious driver » and « lucky risky driver » (both of them may not have accident). It is a big problem for UBI, and SafetyNex brings the solution as it anticipates accident (sooner or later the « lucky risky driver » will have a severe accident).
All you have to know about the french High Tech company.
NEXYAD is a « fake startup » (much older than it seems ^^) set up in 1995 by maths research engineers (Pierre DA SILVA DIAS & Gérard YAHIAOUI + other shareholder : researchers, finance executives, engineers). Founders came from military research (anti-tank missiles), with a strong culture of computer vision, machine Learning, artificial intelligence, signal theoy and processing, stats and data analysis.
During years we were the extended maths team of famous big firms in many fields : defence, automotive, banking, insurance, energy, cosmetics, agri-food, glass, railways, … Customers were research departments first, and then product and marketing departments, sales departments, industrial labs, manufactures, actuaries, etc.
In the automotive sector, we’ve been involved in a lot of different high level maths works such as :
. production/manufacture (work for PSA Group, Charleville),
. industrial Lab (work for PSA Group – Belchamp,TOYOTA Europe – Brussels, Robert BOSCH GmbH, Bühlertal, VALEO, La verrière – SAINT GOBAIN, … etc.)
. research & development for PSA Group, RENAULT, NISSAN, IEE, DAIMLER, FAURECIA, LE LAB (PSA RENAULT), on perception by camera, radar, capacitive sensors, ultrasound, infrared, etc … , vehicle dynamics (active control), sensorial analysis (touch smell perception of texture by vision), human factor analysis, detection of passengers on seats, odor gas sensors, artificial intelligence, epidemiologic analysis (pollution, particles, …), etc.
Navigation Based ADAS : use SafetyNex to build ACC and anticipation (predictive) brake systems
Imagine a robotized car that would slow down automatically when approaching a tiny curve, or an intersection or a priority, of a stop sign, etc … if needed (i.e. if and only if the current speed and acceleration of the car is not appropriate to the driving context). Sounds interesting ?
It would be then « smooth anticipation braking » (from 0.1 to 0.3 g) instead of « emergency braking » (so easier to do and not that disturbing for driver and passengers comfort in the car). Doing this, the car dramatically decreases the probability to be kept in a dangerous situation and it let much more margin to emergency brake if still needed.
Finally, it would mean that the car follows road traffic code plus safety rules (anticipation).
This is easy to achieve using NEXYAD real time driving risk assessment module SafetyNex : SafetyNex reads « Electronic Horizon » (reading POIs and decoding shape and dimensions of the infrastructure ahead), « GPS« , « accelerometers« , and can accept additional inputs such as « time to collision« , « size of free space« , « position in the lane« , « atmospheric visibility« , alert data streams (weather, accident, traffic, …). All those heterogenous data are used (data fusion) to estimate driving risk in real time : Driving Risk (t)
Then everytime that Driving Risk(t) comes higher than an acceptable threshold value, the robotized car slightly slows down … and that’s it ! SafetyNex is the result of 15 years of collaborative research and it works.
Markets : Car insurance and fleet managers (for real time alert and risk profiles recording), ADAS (for automatic predictive/anticipation brake), and Driverless car (Automated car that follows Road Traffic Code).
SafetyNex is Under deployment, please feel free to try it and put it into your own products (available as an API).
Keywords : Adaptive Cruise Control, ACC, Intelligent ACC, Intelligent Cruise Control, navigation-based, navigation-based ADAS, NB ADAS, ADAS, Advances Driver Assistance Systems, Anticipation brake, Predictive Brake, SafetyNex, Risk, Driving Risk, Real time driving risk assessment, road traffic code, SafetyNex, electronic horizon, GPS, accelerometers, time to collision, free space, size of free space, position in the lane, lane departure, visibility, atmospheric visibility, data stream, weather, accident, traffic, data fusion,…
AutoSens took place at the AutoWorld Museum in Brussels September 19-21.
To answer the issues of Connected Cars and Autonomous Cars, engineers need first to give eyes, ears and A.I. to future vehicles. Sensors will play this crucial and difficult role of replacing the human senses.
Engineers and sensors providers met for three days of conferences and workshops.
Groupement ADAS was present with Leddartech the lidars canadian company that rose 100 M$ funding, New Imaging Technologies with their unique high dynamic range camera sensors, Intempora that provide famous RT-Maps, and of course Nexyad presented his three camera-based software modules for Road Detection – RoadNex, for Obstacles Detection – ObstaNex, for Visibility Measurement – VisiNex and SafetyNex – the Road Safety system with sensors fusion and data fusion (digital map, accelerometers, GPS, cameras, lidars, radars, ultrasounds, weather data, traffic data, etc.).
New players appeared as Crowdflower or Mighty Ai, they are plateforms that help you process your data or images very quickly by dividing the workload with very many people registered online.
All you have to know about the french High Tech company.
NEXYAD is a « fake startup » (much older than it seems ^^) set up in 1995 by maths research engineers (Pierre DA SILVA DIAS & Gérard YAHIAOUI + other shareholder : researchers, finance executives, engineers). Founders came from military research (anti-tank missiles), with a strong culture of computer vision, machine Learning, artificial intelligence, signal theoy and processing, stats and data analysis.
During years we were the extended maths team of famous big firms in many fields : defence, automotive, banking, insurance, energy, cosmetics, agri-food, glass, railways, … Customers were research departments first, and then product and marketing departments, sales departments, industrial labs, manufactures, actuaries, etc.
In the automotive sector, we’ve been involved in a lot of different high level maths works such as :
. production/manufacture (work for PSA Group, Charleville),
. industrial Lab (work for PSA Group – Belchamp,TOYOTA Europe – Brussels, Robert BOSCH GmbH, Bühlertal, VALEO, La verrière – SAINT GOBAIN, … etc.)
. research & development for PSA Group, RENAULT, NISSAN, IEE, DAIMLER, FAURECIA, LE LAB (PSA RENAULT), on perception by camera, radar, capacitive sensors, ultrasound, infrared, etc … , vehicle dynamics (active control), sensorial analysis (touch smell perception of texture by vision), human factor analysis, detection of passengers on seats, odor gas sensors, artificial intelligence, epidemiologic analysis (pollution, particles, …), etc.
NEXYAD Automotive & Transportation Newsletter #16, April 11th, 2017
Achieving of real time risk assessment in car telematics with Safetynex
Headlines :
– New Rating of Nexyad by Early Metrics
– BIKER ANGEL Project selected for Government funding (FUI23)
– Conference on Machine Learning organized by SNCF
– Nexyad Paper at 1er European Conference on Connected and Automated Driving
– Meeting Mov’eo, Systematic and Cap Digital
– Nexyad has visited 6th « les Rencontres Flotauto »
– Nexyad in Media
– SafetyNex available on stores for testers (Apple and Google)
– Groupement ADAS welcomed New Member NIT New Imaging Technologies
– Articifial Vision Products of Nexyad
NEXYAD has just been rated again by the rating agency Early Metrics and got the score of 81/100 which puts us in the top 2% of companies rated by Early Metrics. This rating is primarily for investors.
Early Metrics is an European rating agency of startups and SMEs.
* * * * *
BIKER ANGEL Project selected for Government funding (FUI23)
The FUI23 French collaborative research program published the list of projects that are approved : The project BIKER ANGEL (adaptation of the real time driving risk assessment module SafetyNex to motorbikes) is selected !
Biker Angel Project led by NEXYAD was already labelised by Competitiviness Cluster FINANCE INNOVATION.
Le programme de recherche collaborative FUI23 (Fond Unifié Interministérielle) a publié la liste des projets approuvés : BIKER ANGEL est sélectionné (adaptation du logiciel de mesure du risque en conduite temps réel SafetyNex pour la moto).
Le projet BIKER ANGEL porté par NEXYAD avait déjà été labelisé par le Pôle de Compétitivité FINANCE INNOVATION.
Very interesting conference on Machine Learning and Deep Learning. SNCF RESEAUX welcomed a large audience last tuesday 28th march in Saint Denis.
French experts of A.I. field were introduced by Claude Solard SNCF réseau Chief Operating Officer and Jean-Jacques Thomas Director of Innovation.
Christophe Garcia, Full professor at INSA Lyon, deputy director of the LIRIS laboratory, gave an introduction to Neural Networks and Artificial Intelligence and answered to the audience’s questions.
Then, Gérard Yahiaoui, CEO of Nexyad, Vice President of the MOV’EO Cluster, explained the Criteria for use and Methodology for implementation: the methodology AGENDA.
Gérard Yahiaoui CEO of Nexyad
From CEA List, Jean-Marc Philippe presented « from the Neural Network Tools to the Optimized System ». The conference continued with a roundtable about the SNCF Cafeine Project or how to go from the industrial need to the applied solutions in SNCF Réseau; animated by Alain Rivero, SNCF Réseau Director of Cafeine Project; Xavier Roy, Head of Innovation of ITNovem; Michel Paindavoine, co-founder of Global Sensing Technologies and professor at University of Bourgogne; and Jean-Jacques Thomas Director of innovation of SNCF Réseau.
The CAFEINE Project proposes to use the Artificial Neural Networks to detect the defects of pantographs on moving trains, and also to read the number of each wagons, oars and containers.
Another roundtable was organized about Startups and A.I. with Kunthirvy Collin-Dy, Head of relationships with Startups of SNCF Réseau Robot Lab; and Yannick Gérard, Head of Project of DAVI.
Patrick Bastard, Director of Driving Assistance Systems engineering of Renault, ended the conference with a presentation on an opening to other fields of application : vehicles electrification, ADAS and autonomous driving.
From the left : Jean-Marc Philippe, Patrick Bastard et Christophe Garcia
* * * * *
Nexyad Paper at 1er European Conference on Connected and Automated Driving
Machine Learning and Artificial Intelligence for Intelligent Connected Car : The Validation Issue.
A paper by Brahim Yahiaoui, Pierre Da Silva Dias and Gérard Yahiaoui
First European Conference on Connected and Automated Driving
3-4 april 2017 – European Commission, Charlemagne Building, Brussels
– How to concile high complexity of A.I. with ASIL standard that needs a system to be fully predictable ?
– How to make sure that machine learning based behaviour will be adapted to new cases ?
– A Conception AND Validation methodology : « AGENDA »
* * * * *
Meeting Mov’eo, Systematic and Cap Digital
A networking event took place at Cap Digital in Paris, the 16th of march. In the presence of Christophe SIRUGUE, Secretary of State for the Digital and Innovation Industry, the goal of this meeting was to bring together SMEs or startups offering innovative technologies or services for the connected vehicle.
Jean-Luc Moullet, Director of the competitiveness program, industrial and transport , Investment advisory services for the government, introduced the support mechanisms available under the Investments Program of the Future. Jean-Luc BROSSARD, R&D Director of PFA spoke about the Dynamics of innovation and needs of the automotive sector and mobilities. Anne Laliron, Director of Business Lab for PSA, gave a car manufacturer vision for the future. Gérard Yahiaoui, CEO of Nexyad and vice-president of Mov’eo, Michaël Fernandez, CEO of Drust, and Thierry Ernst, CEO of YoGoKo, advocated view for SME’s and Startups. Then Marc Charlet, Managing Director of MOV’EO, Patrick Cocquet, General Delegate of Cap Digital Hub, and François Cuny, General Delegate of Systematic Hub, discussed about Hub contributions. Christophe Sigure concluded this information-sharing.
Thierry Ernst on the left with the mic, Michaël Fernandez and Gérard Yahiaoui on the right
* * * * *
Nexyad has visited 6th « les Rencontres Flotauto »
On Thursday, March 9, the « Rencontres Flotauto » or Professional fleet meeting were held in Paris.
This important event brings together all players of the fleet sector.
Suppliers of telematic equipment such as Nomadic Solutions, a French eco-driving specialist. Pure fleet management as Fleetmatics a French SME recently acquired by the American giant Verizon . New mobility startups such as OpenFleet which offers car sharing solutions for professionals. Almost all the European and Japonese car manufacturers were also represented by their Fleet subsidiary such as Volkswagen Group Fleet Solution.
Fleetmatics booth
Nomadic Solutions on the right and Carte Carburant Leclerc on the left
* * * * *
Nexyad in Media
Saint Germain en Laye : This App promises to Secure your Driving, by Jeremy Denoyer.
« C’est une application dont certains conducteurs ne pourraient plus se passer. SafetyNex, actuellement en phase de test auprès de 3500 utilisateurs, permet de déclencher des alertes en fonction de la dangerosité des aménagements fixes (croisements, ronds-points, virages) et des excès de vitesse. Développée par la société Nexyad, basée à St Germain en Laye, cette application devrait être disponible sur les plates-formes de téléchargement mobile d’ici deux mois. »
SafetyNex available on Stores for Testers (Apple and Google)
To test SafetyNex in your car, send your iTunes email if you use iOS smartphone or your Google account email if your smartphone is an Android one, to this adress obenel@nexyad.net
Today SafetyNex works on four continents :
– Europe : Austria, Belgium, France, Germany, Ireland, Italy, Nederland, Spain, Switzerland, United Kingdom
– North America : Mexico, United States
– South America : Chile
– South Asia : India, Singapore
We’ll integer new countries as soon as possible and on demand.
NOTICE : SafetyNex is now also available for integration in any Smartphone App and Electronic Devices through an API.
Groupement ADAS welcomed New Member NIT New Imaging Technologies
Groupement ADAS is a Team of innovative companies (cluster) with over 20 years experience in the field of technologies used in assistance driver systems (design, implementation and integration of ADAS in vehicles for safety features, driver assistance, partial delegation to the autonomous vehicle).
Last month, a new member joined the cluster to make ten companies !
New Imaging technologies (NIT) offers CMOS and InGaAs imaging sensors and cameras operating over an extraordinary dynamic range of more than 140dB. Our sensors are particularly useful for machine vision, automobile and autonomous driving, biometrics, security and surveillance. NIT delivers from large volume production down to small numbers and custom products. Our facility is fully ISO9001 accredited.
– RoadNex is a functional bloc (software) for ADAS (Advanced Driver Assistance Systems) : detection of the road shape/contours and lane in front of the vehicle.
– ObstaNex is a functional bloc (software) for ADAS (Advanced Driver Assistance Systems).
ObstaNex detects obstacles (a car, a pedestrian). Definition of an obstacle: object that is not plane (or that is « enough » vertical), and/or that has a movement that is not due to the movement of the camera.
– Visinex Onboard is a functional bloc (software) for ADAS (Advanced Driver Assistance Systems).
VisiNex Onboard measures the visibility on a region of interest (visual quality score and distance of detection).
NEXYAD Automotive & Transportation Newsletter #14, December 23th, 2016
Check NEXYAD Technologies for New Mobility Applications
Headlines :
– Demo video of SafetyNex : Smartphone App Onboard Real Time for Driving Risk Assessment
– Cercle LAB Symposium : new digital technologies for Insurance and Bank
– FinTech Community Symposium
– New Release of SafetyNex : Real Time Driving Risk Assessment for Car Industry and Insurance Companies
– Nexyad Technologies for Car Industry and New Mobility : SafetyNex – RoadNex – ObstaNex – VisiNex
– R&D project BIKER ANGEL (Driving Risk Assessment for Motorbikes) has been certified by the pôle FINANCE INNOVATION
– Business Trip to CES at Las Vegas
New Release of SafetyNex : Real Time Driving Risk Assessment for Car Industry and Insurance Companies
Reminder :
. SafetyNex App gives risk of accident
. No Big Data on Cloud, but risk is fully calculated inside driver’s smartphone
. The App warns the driver in case of high risk able to generate dangerous situation
. With 4 secondes anticipation that let time to reduce speed or to brake
. Risk construction implements concept of near accident invented by searchers in accidentology
. Near accident is explainable by cause/effect relations
. Regularity of this concept ensures the perfect correlation of calculated risk by SafetyNex with accidentology
. Nexyad work since 2001 and work basis used came from scientific publications
General ergonomics of SafetyNex has changed and after each run you have immediate results of your driving score with Gold Cup if you are safe.
Update of RoadNex & ObstaNex : Road Detection and Obstacles Detection for ADAS and Driverless
Nexyad realised a major update of RoadNex v3.0 & ObstaNex v3.1
Obstacle Detection with ObstaNex by Nexyad: this run was made with a single camera
Obstacle Detection with ObstaNex by Nexyad : city traffic
* * * * *
CESA Automotive 2016 : Symposium on Automotive Innovation
Nexyad on the booth Groupement ADAS at CESA Automotive 2016
RENAULT ZOE of Adaccess on Groupement ADAS booth at CESA Automotive 2016.
Gérard Yahiaoui CEO of Nexyad and Jochen Langheim Vice President of ST microelectronics and Chairman of CESA Automotive 2016 on Groupement ADAS booth at CESA in Versailles.
Nexyad Presented SafetyNex at CESA 4.0 2016
Gérard Yahiaoui CEO of Nexyad presented SafetyNex Real Time Onboard Driving Risk Assessment for Car Telematics at the Conference « Highly Automated Driving New Sensors » of CESA 2016 in Versailles.
Groupement ADAS booth shows top technologies and competences of 9 companies dedicated to ADAS and sponsored by MOVEO.
. ADACCESSis a French engineering company specialized in embedded measurement and vehicle prototyping.
. CAR&D : Creative Automotive Research and Development (Car Dynamics)
First issue of ADAS Morning on ADAS for Road Safety
Cluster « Groupement ADAS » Launched the october 18th first ADAS Morning co-organized with MOVEO in Paris. Thema was ADAS and Road Safety : to discuss challenges, solutions and opportunities with many specialists personalities in the field in front of a large audience.
Les enjeux
Les enjeux humains
ADAS et véhicules autonomes quels enjeux pour les personnes ayant des besoins spécifiques – Claude Dumas – CEREMH
Les chiffres de l’insécurité routière : Christophe Ramond – Prévention Routière
ADAS et facteurs humains : Apports des sciences cognitives- Franck Techer – IFFSTAR
Les enjeux économiques
Risque routier lié au travail: quel coût pour les entreprises ? Patrick Oberto – Promotion et Suivi de la Sécurité Routière en Entreprise
ADAS et TIC, outils de disruption de la chaîne assurancielle : Philippe Caton – COVEA
Diminution de la sinistralité responsable : Jean Zermati – ORANGE
Les solutions actuelles
Les systèmes de sécurité active et les ADAS
Evolution technique de l’accidentologie et de la problématique d’estimation du gain des ADAS : Philippe Chrétien – CEESAR
Nouvelles mobilités et sécurité routière : quelles évolutions pour l’infrastructure ? : Eric Violette – CEREMA
Assistant nomade à la conduite sûre et responsable : Gérard Yahiaoui – NEXYAD
Les Perspectives
Le défi de la sécurité routière : l’intégration des facteurs humains dans les cas d’usages d’expérimentation des ADAS : Stéphane Barbier – TRANSPOLIS
Véhicule autonome, une révolution de la mobilité – Rémi BASTIEN–RENAULT
New white paper : ROI Evaluation for Insurance Companies with SafetyNex
New Nexyad paper :
Real time App for onboard driving risk assessment SafetyNex used by Insurance Companies
(onboard telematics with smartphone for car insurance)
Evaluation of return on investment (ROI)
INTRODUCTION
European and American car Insurance Companies are all currently testing onboard telematics systems (on professional electronics devices or on Smartphones), in order to study new opportunities provided by digital technologies in the evolution of their business and business models [1].
We also can see now some experiments in Asia. Indeed, digitization of the economy has an impact on insurance industry too, as new competitors such as GAFAMs (Google, Amazon, Facebook, Apple, Microsoft) come to their car insurance market with new approaches, always ready to capture value.
The main idea behind testing telematics is that it would be nice to adjust at best pricing of insurance depending on the driver. Onboard telematics is expected to « measure » usage (kind of road, day/night, number of km, et …) and to estimate risk taken by the driver. Read the entire paper
* * * * *
Vision Systems presenting Smart-Vision
at Automotive Techdays 2016
Friday, november 4th, at Automotive Techdays in Lyon (Rhône-Alpes), Vision System announced its new technology Smart-Vision. This ADAS innovation is fully developed by the firm from Brignais in partnership with Nexyad. Smart-Vision is a unique and complete rearview and surround view system replacing traditional mirrors with HD digital cameras and interior screens.This system informs the driver :
. When a vehicle is coming from the back 80 meters away
. When a vehicle, bicycle or pedestrian enters the blind spot area, each with a specific signal, regardless of the speed of the vehicle or the external environment.
. When they can safely change lane (for example, after overtaking).
Smart-Vision reduces power/fuel consumption significantly, enhances ergonomics and improves safety.
Both hardware and software are tailor-made by Vision Systems.
* * * * *
Nexyad in Media
Article de la PFA (Filières Automobile et Mobilités) citant Nexyad :
Retour sur le congrès du CESA 4.0 – « Automotive Electronic Systems »
Pitch de Nexyad au Congrès CESA Automotive 2016 à Versailles
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Example of Statitical Relationship in Risk Assessment : from Behaviour to Fatalities
