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.
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 (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.
Type of obstacle: – static obstacle
. linked to the infrastructure: works terminals, tolls, …
. related to users: tire on the roadway, package dropped from a truck, motorcyclist lying on the road following an accident, vehicle broken down stopped on the roadway, pedestrian stationary on the edge of the roadway (visible / hidden) – moving obstacle
. truck, car, vulnerable (pedestrian, bike, motorcycle) with the typical trajectories (longitudinal in the direction of travel, longitudinal in the opposite direction of travel, lateral) and the position (opposite, right, left) .
. Etc.
Real-life situations examples :
We see that if we combine these factors, we can find quite quickly a very large number of cases. Now, the development of ADAS systems is complex, and it is necessary to proceed by successive iterations, from simple situations to complicated situations.
Our database allows this, since all records are described such as cross-referring of modalities of the factors of variability. We thus know exactly in which cases the system was tested or not.
The formalism of ‘cross-referring of modalities of the factors of variability’ makes it possible to use experimental designs, and in particular orthogonal fractional plans, to greatly reduce the number of cases to be tested while guaranteeing maximum coverage of real-life situations. In this context, we can develop an ADAS on an orthogonal fractional plane and test it for other orthogonal fractional planes, for example.
2) Ground reality
It is a question of define the obstacles and elements of the infrastructure (markings, road edges, etc.) on the images so as to constitute a reference allow measuring the performance of the system.
1.1, summer, cloudy, unmarked road, moderate speed, tire on roadway, dry weather
1.2, summer, cloudy, unmarked road, moderate speed, package on roadway, dry weather
2.1, summer, cloudy, unmarked road, moderate speed, visible static pedestrians at the edges of the roadway, time
2.2, summer, cloudy, unmarked road, moderate speed, human lying on roadway, dry weather
etc.
It is not certain that one can meet these few cases, even by driving 1 million km on open road!
Target of this database :
NEXYAD starts its collection of images and data:
. video (towards the front of the vehicle) color
. accelerometers
. gyros
The files are synchronized by the RT-MAPS tool of the company INTEMPORA.
The files are saved in RT-MAPS format and directly replayable on this tool.
NEXYAD is currently looking for contributors on this internal project. Contributors co fund and have in return free access to the database, unlimited in time. This contribution will accelerate the work of collection and labeling.
NEXYAD wishes to make this database available soon, free of charge to give material to the ADAS community and the autonomous vehicle, in a reduced version of the database, and in a paid way (in the form of subscriptions) for the complete base.
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.
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.
A tough work was to be made in order to build such a knowledge-based system that could cope with « gradual truth » and could run a complex knowledge-based model in real time. Implementation uses fuzzy sets both for facts and knowledge representation, and competition between knowledge atoms uses deep Possibility Theory concepts. Of course, SafetyNex deals with dynamic problems (road accident, with distances, speed, …) and had to find a proper representation of TIME. NEXYAD was not very quick to develop all those solutions and to integrate them into a product called SafetyNex : SafetyNex is proposed for sale since Jan 2017 (first R&D on SafetyNex : 2001). But the result is efficient : you can run SafetyNex on your smartphone while driving your car and see how it helps you to drive much safer without alerting for nothing.
This unique technology places now NEXYAD in the center of the worldwide telematics/adas/data collecting race for car insurers.
So let’s see what are the main applications of SafetyNex for car insurers :
. PREVENTION : SafetyNex alerts (vocal alert) driver BEFORE a dangerous situation, letting time to slow down and avoid accident. It is the best prevention tool ever : studies showed that 20% of accident can be avoided (then also 20% of personal injuries and fatalities !!!). SafetyNex is the ONLY tool that runs in real time inside the smartphone or inside the telematics/adas devices and then is the ONLY module that can alert driver (all the other systems apply scoring methods on the cloud …). This is a major differenciation for SafetyNex : avoid accident ! Observation of drivers using SafetyNex showed that they change their way of driving in order to mimnimize the number of alerts, then they change their driving behaviour in the long term.
. COMMUNICATION : SafetyNex gives driver a score of Safe Driving after every trip. This is a positive way of presenting risk and driver appreciate being given a gold cup for his/her high safe driving score. You can imagine many ways to communicate for car insurers. Example : every year, sort all drivers (customers) of a country, find the best (highest SafetyNex safe driving score) and give a huge incentive (offer a brand new car, for instance). Such an incentive tranforms the car insurer’s customers set into a community that tries to drive better, and you can build of course a social network for experience share and local challenges … etc. This is a simple and very concrete use of digital technology both for getting better profits and for saving lives. Marketing executives call this ‘the Nudge Theory ». SafetyNex is a natural candidate for applying this Nudge Theory.
. KNOWLEDGE : car insurers only know about risk by accident observation. Although the theory of Frank E. BIRD (safety triangle) shows that the proper variable to observe would be what is called « near miss » or « quasi accident ». SafetyNex alerts every time that driver’s behaviour leads to a quasi accident situation. Then car insurers can use SafetyNex to build this new knowledge and sort and cross all their variables with this new notion. Actuaries will quickly find clever ways to use those new sets of data and you will be surprised to see how productive data scientists can be when they have a direct access to new qualified huge set of data.
. USAGE BASED INSURANCE : Of course, SafetyNex is THE perfect tool for UBI. At the end of every trip, SafetyNex sends data (statistics) : usage (urban, road, highway, time, duration, km, postal code, etc …) and risk (risk profiles). Then it is very easy to propose Usage Based princings (‘as you drive » or « how you drive » etc).
It is important to notice that real time abilities of SafetyNex also simplify business models :
. Anyway car insurer does effective prevention with SafetyNex : it is only needed to avoid few personal injuries and fatalities to « pay » the deployment of SafetyNex. That’s the key of SafetyNex deployment : SafetyNex alerts driver WHILE DRIVING and BEFORE danger, then many accident are avoided … then many personal injuries are avoided. If you know the price of a personal injury in you car insurance, then you see that SafetyNex price was made in order to let you get a fair ROI on this issue.
. Communication (incentive) is then already paid by the number of avoided personal injuries !
. and in addition, car insurer gets qualified data : for knowledge acquisition and UBI opportunities study.
As a conclusion, we can remember main facts :
. SafetyNex real time abilities make it VERY DIFFERENT from any other risk assessment solutions (using stats and data science in the cloud) because then SafetyNex ACTS on driving behaviour BEFORE accident and then lets avoid many accidents.
. Prevention effect of SafetyNex finances it deployment cost.
. Knowledge extraction and UBI opportunities business models can be done without stress as SafetyNex already gives a fair ROI to car indurer.
Some OEMs and insurers already started to integrate SafetyNex API into their smartphone App or into their telematics/adas device.
It is now time to move forward to the 21st century with digital insurance.
– 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
* * * * *
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.
* * * * *
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
* * * * *
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,…
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
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.
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
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.
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.
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.
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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.
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,…
ADAS, Driverless and Connected Car Symposiums with Nexyad
Headlines :
– Nexyad and Groupement ADAS at Automotive Symposium
– New Papers of Nexyad on advantages of SafetyNex
– Challenge Open Innovation Renault
– Nexyad at Imagine Mobility Forum 2017
– Nexyad presenting the driving risk solution SafetyNex to Eurapco
– Conference at “Cercle LAB” Paris
– HERE invited NEXYAD to Le Mans
– Meeting HappYnnov at Chamber of Commerce Versailles-Yvelines
– Nexyad booth to la fête du THD at Acome in Mortain (Normandy)
– NEXYAD in Media
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Example of Statitical Relationship in Risk Assessment : from Behaviour to Fatalities
