Papers

Nouvel Article de Nexyad sur SafetyNex

DEPLOIEMENT DE SafetyNex DANS LE CADRE DE L’OBLIGATION DE DEPENSE
EN ACTIONS DE PREVENTION ROUTIERE CHEZ LES ASSUREURS AUTOMOBILE

Par NEXYAD



I – CONTEXTE

Depuis 1996, les assureurs français se sont engagés auprès de l’Etat à mener des actions de prévention routière. Ils doivent consacrer ainsi chaque année à ce type d’action de prévention 0,5% du montant des cotisations de responsabilité civile automobile perçues.
Traditionnellement, les actions menées sont des opérations de sensibilisation dans les écoles, conseils pratiques en vidéo, pistes de conduite avec moniteur, simulateurs de conduite, voiture tonneau, etc… Ces actions doivent avoir un effet à long terme sur la réduction du nombre d’accidents de la route. Récemment, les applications smartphone sont aussi utilisées, toujours en opération de sensibilisation.
C’est dans le cadre de cette entrée du numérique, dans l’action obligatoire de prévention, que SafetyNex représente une avancée très intéressante pour les assureurs automobile. En effet, SafetyNex évite les dangers liés à une vitesse inadaptée aux difficultés de l’infrastructure, ce qui correspond à 75% des accidents de la route. SafetyNex est actuellement le seul système permettant de prévenir en temps réel et de façon prédictive le conducteur afin qu’il ralentisse pour éviter l’accident. SafetyNex répond ainsi aux critères des actions de prévention à mettre en œuvre, si bien qu’il est possible pour un assureur de déployer massivement SafetyNex sans aucune dépense supplémentaire. C’est une opportunité unique de réaliser une action de prévention efficace, tout en préparant la transition digitale du métier d’assurance.

Lire l’article en entier

Interpretation of Risk Profiles with SafetyNex
A new paper by Nexyad

ESTIMATION OF DRIVER’S EXPERTISE, OF RISK TAKEN CONSCIOUSLY BY THE DRIVER,
AND OF THE LACK OF ANTICIPATION AND MISUNDERSTANDING OF THE ROAD



By NEXYAD

Lire la version Française


I – INTRODUCTION
NEXYAD has been developing the smartphonte application SafetyNex which estimates the risk of driving in real time [1]. SafetyNex is both a driver assistance system (ADAS), which alerts the driver (vocal alert) before danger (When the risk increases too much), and a telematics system that records risk profiles and usage profiles.
Warning before the danger gives the driver time to slow down and avoid the accident. Road Safety studies show that SafetyNex can reduce the number of accidents by 20% [2]. This simple functionality is of interest of car insurers, fleet managers, and to car manufacturers.
SafetyNex also rewards the driver with cups (gold, silver, bronze) that can be transformed into money incentive (vouchers, etc.) so that the safe drivers stil have a daily interest to go on using SafetyNex. Indeed, tools that are not used over a period of time rarely have a real effect on the accidentology. SafetyNex is therefore distinguished from other products, on the one hand by its real time and driving assistance, but also for its « reward » side. SafetyNex informs the driver In real time when the risk exceeds a threshold of danger, than one can say that SafetyNex gives the risk in the hands of the driver first. The driver is in control of his/her risk.
Then SafetyNex distinguishes from all telematics products that ultimately provide information to the insurer or fleet manager, but not to the driver who feels rightly spied on.
Risk and usage profiles [3] are forwarded to managers who have an interest in minimizing risk and the number of accidents. This paper presents a simple way to interpret the risk profiles constructed by SafetyNex.

II – SafetyNex RISK PROFILES
SafetyNex estimates risk of driving at every instant.
Since SafetyNex also measures usages, it measures among other things the durations and the number of traveled kilometers.
One can then construct the curve Risk (t) which is the risk at each moment, and also the curve Risk (km) which is the risk at each point of the route.

Risk Distance

Risk Distance rated

Let’s consider one or the other of those curves, it is easy then to cut the risk into slots:

Risk 03

It is therefore possible to calculate the total duration spent [resp the total number of km carried out] with a risk
between 10% and 20%, for example (or between 50% and 60%). The graph of these durations [resp number of km] for each range of risk (0% -10%, 10% -20%, etc.), looks like :

Graph 4

It can be seen that this graph can be seperated into three parts:

Graph 05

. A very high bar of near zero risk
. A shape of « bell curve » comparable to a gaussian
. Rising at the very end towards high risks
NEXYAD has run over 3,500 testers since June 2016, and has been able to interpret the shapes of these curves.

III – INTERPRETATION OF SafetyNex RISK PROFILES : CONSENTED RISK, EXPERTISE OF DRIVING, LACK OF ANTICIPATION OF DRIVER
The large quasi-zero risk bar simply expresses the fact that overall the car is a safe mode of transportation.
The part that draws a bell curve has a more or less strong spread : we have noticed that experienced drivers have a narrow curve (repeatability of their driving style is high) while beginners have a huge spread (they can’t drive always the same way).
The centering of the bell curve (maximum likelihood) corresponds to the way in which the driver takes a controlled Risk : cautious beginners have a low maximum likelihood (they try to take as less risk as they can) while experienced drivers have a higher maximum likelihood : they know what risk level thay can cope with.
Finally, the values that go up to the right (tail of distribution of the curve in bell) correspond to the vocal alerts, that is to saycases where the driver has not fully understood that the risk is high. In other words, it is the lack of anticipation and misunderstanding of road.

IV – CONCLUSION
SafetyNex’s risk profiles make it possible to understand the kind of driver you have :
. Cautious / not cautious (maximum likelihood of the bell curve position)
. Experienced / beginner (spreading of the bell curve)
. Lack of anticipation / very good anticipation (queues of distribution of the curve in bell)
Fleet insurers and managers therefore have all the information that they need to help the driver.
For example, within the framework of prevention plans, offering training adapted to each type of risky driving.
We validated this information by driving 3,500 testers, including beginners, experienced drivers, and also pilots (who in take risks appearance, but in reality have a very safe driving). This allowed us to give these interpretations of SafetyNex’s risk profiles.
With the deployment of SafetyNex to reduce the number of accidents, professionals structurally gain margin, and can use this margin to analyze profiles, segment them, and find the segments where it may be interesting to develop UBI (Usage Based Insurance) and real time pricing fleet.
This multi-functionality of SafetyNex makes it a unique and effective tool for managing driving risks.

V – REFERENCES
[1] : THE ULTIMATE SOLUTION FOR INSURANCE COMPANIES THAT NEED ONBOARD RISK ASSESSMENT : SafetyNex

[2] : SMARTPHONE APP SafetyNex COULD REDUCE ACCIDENT RATE BY 20%

[3] : EXAMPLE OF SafetyNex RISK PROFILES

SafetyNex App Risk Profiles Analysis

Risk profiles estimated by SafetyNex: Analysis of profiles, and possible use to detect fatigue and hypovigilance of driver.

SafetyNex is a nomadic real-time risk estimation system. The system has been described in detail in previous publications [1] and uses the key concept of « near-accident » or « quasi-accident », and is a result of 15 years of collaborative research with road safety experts and researchers.
The main competitive advantage of SafetyNex is that it allows, since the risk is estimated in real time,
to warn the driver (vocal alert), and thus to allow driver to avoid accident. Studies show that SafetyNex can reduce accident rate by 20% [2], which represents for insurers and fleet managers a consequent increase in margin [3].
But of course, SafetyNex also records usage and risk profiles. These profiles provide the behavior of the driver, or more precisely, his/her ability to regulate driving task consistently with danger. No need to record large volumes of data (accelerations, etc…) which in reality are not data (these are signals) for a possible back-office analysis, SafetyNex provides exactly the interesting data [4].
Below are examples of usage profiles and driver risk profiles.

. Read the entire paper
. Analyse des profils de risque en conduite estimés par SafetyNex (version française)

Evaluation of return on investment (ROI) with SafetyNex
for a Car Insurance Company

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

Nouveau Livre Blanc Nexyad n°5

Déploiement de l’App d’estimation temps réel du risque de conduite SafetyNex (télématique embarquée sur smartphone) par une Compagnie d’Assurance :
évaluation du retour sur investissement (ROI)


par NEXYAD
Octobre 2016

INTRODUCTION

Les Compagnies d’Assurance automobile Européennes et Américaines sont toutes actuellement en train de tester des systèmes de télématique, soit sur boîtiers, soit sur smartphones, afin d’étudier les possibilités apportées par le digital dans l’évolution de leur métier et de leurs modèles d’affaires. La digitalisation de l’économie n’épargne en effet pas le secteur de l’assurance qui voit arriver de nouveaux interlocuteurs comme les GAFAMs susceptibles de capter la valeur.

L’idée principale qui se dégage des essais est qu’il serait possible d’ajuster au mieux, sur-mesure en quelques sortes, les tarifs d’assurances en fonction du conducteur, et ce, en utilisant des systèmes de mesure et de scoring dans le cloud susceptibles de mesurer les usages et d’estimer des indicateurs corrélés au risque.

Lire le livre blanc n°5

SafetyNex Revolution in Road Safety

SafetyNex the Smartphone App that revolutionizes automotive world : Autonomous car, Car insurance, Fleet management, use of Telematics for retail.

Version française

SafetyNex is a smartphone application developed and marketed by NEXYAD and which reduces by 20% the number of road accidents [1]. This application is of direct interest to many application targets.

– Driver
– Insurance Companies
– Car Manufacturers
– Fleet Managers
– Mass Marketers

Read the Paper Here

La Révolution SafetyNex

SafetyNex, une App SmartPhone qui révolutionne le monde de l’automobile : véhicules intelligents, assurance auto, gestion de flottes, utilisation du digital pour le retail

English translation

SafetyNex est une application Smartphone développée et commercialisée par NEXYAD, et qui permet de réduire de 20% le nombre d’accidents de la route [1]. Cette application présente un intérêt applicatif direct pour de nombreuses cibles.

– Le conducteur
– L’assureur automobile
– Le constructeur automobile
– Le gestionnaire de flotte auto
– Le grand distributeur

Lire le papier

SafetyNex App could reduce accident rate by 20%



SMARTPHONE APP SafetyNex COULD REDUCE ACCIDENT RATE BY 20%

Version française

by Nexyad

I – ONBOARD TELEMATICS AND AUTO INSURANCE : REMINDER

Onboard telematics now can measure behavior of a driver, and therefore, car insurers have early started this adventure of connected car, more or less successfully.

The simplest applications that have been deployed are:
. locate stolen vehicles
. measure the usage of the driver, and in particular the number of kilometers traveled in order to propose adaptive pricing (vehicle that always stays in a garage will never have an accident!)

But the main business of the insurer deals with the concept of risk, and then, we have seen a lot of telematics firms proposing automatic detection of risky behaviors. The most common is the so-called detection of « severe braking », which is based on the assumption that severe braking reveals a lack of anticipation, and thereby a dangerous driving. We now know that this assumption is totally false [1], but it is still in the mind of some insurers that « want to believe » there is a simple way to classify human beings behaviours. However, the lack of results of these deployments has led some German and US insurers to abandon Telematics [2].

Read the entire paper

L’APP SMARTPHONE SafetyNex POURRAIT REDUIRE DE 20%
LE NOMBRE D’ACCIDENTS DE LA ROUTE
Nouveau papier de Nexyad

L’APP SMARTPHONE SafetyNex POURRAIT REDUIRE DE 20%
LE NOMBRE D’ACCIDENTS DE LA ROUTE

English translation

par NEXYAD

I – TELEMATIQUE EMBARQUEE ET ASSURANCE AUTOMOBILE : RAPPELS

La télématique embarquée permet de mesurer en situation le comportement d’un conducteur, et de ce fait, les assureurs auto se sont assez tôt lancés dans l’aventure, avec, il faut le dire, plus ou moins de succès.

Les applications les plus simples qui ont été déployées sont :
. localiser les véhicules volés
. mesurer les usages du conducteur, et en particulier le nombre de km parcourus pour proposer des tarifs au km (un véhicule qui ne roule jamais n’aura jamais d’accident !)

Mais le métier principal de l’assureur tourne autour de la notion de risque, et assez vite, on a vu des tentatives de détection automatique des comportements à risque. Le plus répandu est la détection des « freinages sévères », qui s’appuie sur l’hypothèse selon laquelle un freinage sévère révèle un manque d’anticipation, et par là-même une conduite dangereuse. Nous savons maintenant que cette hypothèse est totalement fausse [1], mais elle est encore présente à l’esprit de pas mal d’assureurs.

Le manque de résultats de ces déploiements a d’ailleurs conduit des assureurs allemands et américains à abandonner la télématique [2].

Lire la suite

Deep Changes in the Business of Car Insurance
Nexyad White Paper #3

« Deep changes in the business of car insurance.
Contribution of smartphone App SafetyNex in this global context. »

Version française

by NEXYAD
September 2016

1 – Role of the insurer
The insurance idea would have appeared on the occasion of the first great journey by boat, and the appearance of « modern » insurance is generally dated from the 19th century.
The principle of insurance is easy to understand : if accidents are rare (compared to the number of occurrences – travel, car trips, etc.), a simple and prudent idea then is to « put aside » a certain amount of money for each occurrence (which on average does not lead to an accident) and to use the money to repay the cost of the claim in case (rare) of accident.
One could imagine that individuals manage themselves each a « pot » of this type. Of course, even if an accident is rare, you never know when it happens and it may happen at any beginning of the process so that the pot is almost empty.
We could then easily make a common pot between several people, to smooth it : if three people make a common pot, it is unlikely that the three have an accident while starting hoarding. But… it is anyway possible. Although if the pot is conceived with hundreds of thousands of people there, you secure the problem of « instant » of the accident. This is the « law of large numbers », which allows a deterministic modeling of chance : the odds. It remains to define the amount of money to set aside each month for example (or each travel).
To handle this (a pot shared by hundreds of thousands of contributors, the estimated sum to put aside, etc…), it is obvious that it is necessary to have qualified personnel, sufficient… and finally, it happens naturally to the idea of the Insurance Company.

Read the entire paper

Modification profonde du métier de l’assurance auto
Nexyad Livre Blanc n°3

Modification profonde du métier de l’assurance auto.
Apport de l’App smartphone SafetyNex dans ce contexte global.

Par NEXYAD
Sept 2016

English translation

1 – Rôle de l’assureur

L’idée d’assurance serait apparue à l’occasion des premiers grands voyages maritimes, et l’apparition
« moderne » de l’assurance est généralement datée du 19ème siècle.
Le principe de l’assurance est le suivant : si les accidents sont rares (comparativement au nombre
d’occurrences : de voyages, de trajets automobile, etc.), une idée simple et prudente consiste alors à « mettre de côté » une certaine somme pour chaque occurrence (qui en moyenne ne conduit pas à un accident) de manière à utiliser cette somme pour rembourser le coût du sinistre en cas (rare) d’accident.
On pourrait imaginer que les particuliers gèrent eux-mêmes chacun une « cagnotte » de ce type. Bien sûr, même si un accident est rare, on ne sait jamais quand il arrive et il se peut qu’il arrive au tout début du processus si bien que la cagnotte est presque vide.
On peut alors facilement faire une cagnotte commune entre plusieurs personnes, pour lisser ce problème : si trois personnes font une cagnotte commune, il est peu probable que les trois
aient un accident au tout départ de la thésaurisation. Mais … c’est quand-même possible. On conçoit bien que si l’on construit la cagnotte avec plusieurs centaines de milliers de personnes, là
on a sécurisé le problème du « moment » de l’accident. C’est la loi des grands nombres qui permet d’utiliser une modélisation déterministe du hasard : les probabilités. Reste à définir le montant de la somme à mettre de côté, chaque mois par exemple (ou à chaque trajet).

Lire le livre blanc ici

L’accident mortel en Tesla aurait peut-être pu être évité

L’accident mortel en TESLA aurait peut-être pu être évité grâce à des modules logiciels de NEXYAD

English translation

par NEXYAD, août 2016

Les passions se déchaînent autour de la question des véhicules autonomes, ou semi-autonomes. Récemment, une personne a perdu la vie dans son véhicule TESLA alors qu’il était en mode auto-pilote.
NEXYAD a étudié la sécurité routière pendant une vingtaine d’année, et nous donnons quelques éléments de réflexion sur ce type d’accident.

Les chaînes de traitement de l’information des systèmes auto-pilote, driverless, etc… allant de la perception de l’environnement jusqu’à la prise de décision et à la gestion automatique des actionneurs, sont généralement très bien conçues, et mettent en œuvre des modules performants. Mais cela ne suffit pas à rendre nul le risque d’accident. En effet, pour traiter ce risque, il manque une chaîne parallèle (et indépendante) de « monitoring ».
C’est pour bien comprendre cette nécessité, il faut tout d’abord appréhender le niveau de complexité d’une scène routière vue par une caméra.

Le livre blanc à lire ici

Accident fatalities in a TESLA car

Accident fatalities in a TESLA car might have been avoided by using software modules of NEXYAD :
the time for monitoring circuit has come.

Version française

By NEXYAD

Processing circuit, informing auto-pilot systems, control, etc … from perception, data fusion, decision-making, and automatic control of actuators, are usually very well designed, and based on high-performance modules. But unfortunately, this is not enough to void the risk of accidents. Indeed, for the treatment of this risk, it lacks a parallel circuit (parallel and independent) called « monitoring » circuit.
To understand this need for a monitoring circuit, one must first understand the level of complexity of a road scene viewed from a camera.

The variability of road scenes is actually much more than what a normal person comes to imagine. Indeed, a color image, which has eight bits for each colors (then, 24-bit, as there are 3 colors) may encode 224 different color levels per pixel (more than 65,000 different possible values). HD video has more than 2 million pixels.
This means that the matrix of HD 8-bit color image may encode more than 65 0002 000 000 images !
This huge number is simply unimaginable.

Read the entire paper

Accidented Tesla
http://www.nextinpact.com/news/100804-accident-mortel-tesla-model-s-roulait-trop-vite-enquete-se-poursuit.htm

Vehicle Telematics, measurement of risk in driving,
respect of individual privacy

« Vehicle Telematics, measurement of risk in driving, respect of individual privacy » is the new white paper from Nexyad, which explains important points to check on a vehicle telematics application to assess the risk taken by the driver about his driving task.

Version française

The calculation of risk requires having contextualized data that are inherently confidential, personal, and therefore which must in no case be recorded on computer servers in a cloud as they contain, directly or indirectly, information about offenses (in France it is forbidden: by respect of the criminal code and rules CNIL).

Onboard-measurement-of-risk-of-accident-with-SafetyNet-real-time-risk-assessment.pdf

Télématique auto, mesure du risque de conduite,
respect des libertés individuelles

« Télématique auto, mesure du risque de conduite, respect des libertés individuelles » est le nouveau white paper de Nexyad, qui explique quelles sont les points importants à vérifier sur une application de télématique embarquée destinée à évaluer le risque que prend le conducteur pendant sa tâche de conduite.

English translation

Le calcul du risque nécessite de disposer de données contextualisées qui sont intrinsèquement confidentielles, personnelles, et donc qui ne doivent en aucun cas être enregistrées sur des serveurs informatiques dans un cloud car elles contiennent, directement ou indirectement, des informations sur des infractions (en France c’est interdit : respect du code pénal et des règles CNIL).

Lien vers le white paper

Nexyad wrote a paper in the book
Energy Consumption and Autonomous Driving

METHODOLOGY for ADAS VALIDATION :
Potential Contribution of Other Scientific Fields Which Have Already Answered the Same Questions
By Gérard YAHIAOUI & Pierre DA SILVA DIAS

Livre Jochen

This volume by Jochen Langheim collects selected papers of the 3rd CESA Automotive Electronics Congress, Paris 2014. CESA is the most important automotive electronics conference in France. The topical focus lies on state-of-the-art automotive electronics with respect to energy consumption and autonomous driving. The target audience primarily comprises industry leaders and research experts in the automotive industry.

To buy the book : http://www.springer.com/jp/book/9783319198170

Economic Intelligence presentation on Nexyad-ADAS blog

NEXYAD always looking at surveys about ADAS and driverless cars market … Here is a relevant study about Automotive Advanced Driver Assistance Systems Market (2015-2025), by ReportBuyer.com

The Next Step Towards Autonomous, Self-Driving & Driverless Cars

LONDON, May 12, 2015 /PRNewswire/ — Report Details

In many ways, advanced driver assistance systems (ADAS) are the first step on the road to semi-autonomous or fully-autonomous self-driving and driverless vehicles. In 2015, Park Assistance, Surround-View Cameras, and Adaptive Cruise Control applications dominate the ADAS market; however, the penetration into passenger cars is relatively low despite the increasing rate of installations into the premium car segment manufacturers.
Often these are fitted in isolation, and even where multiple systems are fitted in a vehicle, great care is taken to ensure that these systems are perceived only as assisting the driver (who must remain fully alert) rather than taking over his role. As the number and abilities of these systems increases, the situation will move further along a continuum from driver assistance to in effect driver substitution, meaning that the driver would no longer be required to be alert and instead the onus would fall on the vehicle to warn the driver when his input was required, bringing him back to a state of full alertness.

To read more : http://www.nexyad-adas.com/archives/2015/12/31/33118647.html

USING NEXYAD ADAS MODULES
FOR AUTONOMOUS VEHICLE AND SAFETY/RISK ESTIMATION



USING NEXYAD ADAS MODULES FOR AUTONOMOUS VEHICLE AND SAFETY/RISK ESTIMATION

by NEXYAD


INTRODUCTION

The company NEXYAD developped software modules for Advanced Driver Assistance Systems :
. RoadNex (Road detection) : lane detection, detection of the borderlines of drivable area in the lane, detection of the surface of drivable area in the lane.
Sensor : camera (color)

. ObstaNex (Obstacles detection) : obstacles detection (if they have a vertical dimension or – inclusive – if they have their own movement)
Sensor : camera (N&B or color), accel, gyro

. VisiNex onboard (weather visibility measurement) : visibility measurement (quality and distance)
Sensor : camera

. SafetyNex : onboard road safety / risk estimation
Sensor : navigation map, gps, accel or car speed

Those modules were made to develop very efficient ADAS.
There are many ways of comining those modules, depending on the function that should be developped.

LANE KEEPING AND AUTOMATIC BRAKING : FOR CAR MANUFACTURERS AND TIER ONE COMPANIES

For this function, modules may be integrated in a rather complex way :
Nexyad Suite 1
Such an application needs to know where it works and where it doesn’t work (reliability). For that, VisiNex helps because it measures weather visibility and the nit is possible to know in which context artificial vision algorithms are efficient or not. It is also possible to switch setting parameters of artificial vision based algorithms using visibility characteristics, in order to expand the range of good performance of the global system (this is robustness).

NEXYAD applies a validation methodology called AGENDA (see papers in CESA Automotive 2014 in Paris and in SATETYWEEK 2015 in Aschaffenburg). This methodology is the onlt approach that allows to know what the system is supposed to do in a functional point of view, with measurable characterisctics of road scenes.
NEXYAD of course uses the NEXYAD ADAS validation data base : a part of this validation data base for artificial vision-based ADAS will be soon online for free (usable by every researcher or engineer in the world).

Note : the AGENDA methodology also provides a method to measure the similarity of a road scene in the validation data base anda current road scene : this is applied to estimate a confidence score.

SAFETY / RISK ESTIMATION FOR INSURANCE COMPANIES

SafetyNex measures the adequation of driving to road infrastructure characteristics.
It generates then a risk if the driver goes too fast when approaching a crossing road or a dangerous curve.
Of course, a poor visibility should lead the driver to drive slower.
In addition, there could be auxiliary inputs that would tell SafetyNex if there are obstacles on the pathway :
Nexyad Suite 2
This scheme is the same than the previous one but the outputs of RoadNex and ObstaNex are used INSIDE the scheme (they don’t provide an output of the global scheme).

DEMOS OF NEXYAD MODULES



REFERENCES

Validation of Advanced Driving Assistance Systems by Gérard Yahiaoui & Nicolas Du Lac
CESA Paper by Gérard Yahiaoui & Pierre Da Silva Dias
Road detection for ADAS and autonomous vehicle
Using the NEXYAD road detection (RoadNex) to make obstacles detection more robust
Real Time Onboard Risk Estimation Correlated with Road Accident
Visibility Measurement for ADAS and Autonomous Vehicle