ROBUSTNESS OF NEXYAD SOFTWARE MODULE
FOR ROAD DETECTION : RoadNex

ROBUSTNESS OF NEXYAD SOFTWARE MODULE FOR ROAD DETECTION : RoadNex

By NEXYAD

Detection of the road, detection of the lane, in front of the vehicle is now a « must-have »
for Advanced Driver Assistance Systems (ADAS) and of course for Autonomous Cars too.
Every R&D team is able to show cases of good detection. The difference between different
modules is robustness : ability to work in many cases (almost every cases).

For instance, robustness consideration led many big Automotive firms to interger the MOBILEYE
detection system : jus because MOBILEYE is more robust than detection systems developed by
those big firms. And robustness is not a matter of deployment : you won’t get a more robust
module is you put 10 000 developers on the project. You need time, big amount of data, and
« smart ideas ».

Note : This robustness definition leads to question on ADAS validation (« almost » every case is
not that well defined … how could we put some maths on those words). NEXYAD has been
developing an applied maths-based methodology for ADAS validation and is currently
recording a validation data base that will be soon available for free worldwide on the internet.

But let’s go back to road detection modules comparison.

There is another difference between road detection systems : do they need white markings
or are they able to work even without markings ?

NEXYAD founders has been working on road detection since the beginning of the 90’s and never
stopped (*). The NEXYAD team is one of the moste experienced team in the world about road detection.
That actually makes the difference, and RoadNex is a module that would take long to develop by
other teams. RoadNex is currently available on PC (windows, Linux) in the real time framework
RT-MAPS. RoadNex will be soon available :
. on electronic device of an Automotive Tier One Company
. on smartphones (so it works in real time on a smartphone usual processor ! try to compare to other modules)
(*) publication at a scientific congress in France in 1993 :
« Texture-based Image Segmentation for Road Recognition with Neural Networks », G. Yahiaoui, M. de Saint Blancard,
Sixth international conference on neural networks and their industrial & cognitive applications NeuroNîmes93, EC2,
Nîmes, 1993,

In order to have an idea of what robustness means, here are some case used to test RoadNex :
RoadNex01
RoadNex02
https://nexyad.net/Automotive-Transportation/wp-content/uploads/2015/11/RoadNex03.jpg
RoadNex04
RoadNex05
RoadNex06
RoadNex08
RoadNex07
RoadNex09
RoadNex10

How many kilometers should you drive to sample those few road scenes variations ?

For more information : https://nexyad.net/Automotive-Transportation/?page_id=412

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

NEXYAD at the “Carrefours Mov’eo Ile de France” in Paris, with the ADAS cluster (Groupement ADAS, Mov’eo Groupement) (November 20, 2013)

NEXYAD shows a demo car for innovative ADAS.
This demo car has been developed by 3 SMEs of Mov’eo that will be a part of the next Mov’eo high tech SMEs cluster (Groupement ADAS) : INTEMPORA, FH ELECTRONIQUE, and NEXYAD.

In this demo car, FH ELECTRONIQUE deals with physical integration into the car, INTEMPORA deals with real time management and time stamping (using their software RT-MAPS) and NEXYAD brings their ADAS bloc for road detection RoadNex. This ADAS demo car was developed for Université de Valenciennes.


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