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From Advanced Driver Assistance Systems toward Automated vehicle
Serge Boverie
www.conti-engineering.com
Continental Engineering Services
Excellence always succeeds
Continental – 150 Years of Progress and Achievement
Merger with major companies of the German rubber industry to form Continental Gummi-WerkeAG.
Acquisition of a US company’s Automotive Brake & Chassis unit, the core of which is Alfred TevesGmbH in Frankfurt.
Continental-Caoutchouc- andGutta-Percha Compagnie is founded in Hanover, Germany.
Continental strengthens its position in the ASEAN region and Australia by establishing its Continental Sime Tyrejoint venture.
Takeover of the European tire operations of Uniroyal, Inc., USAthe tire operations of the Austrian company Semperitthe North American tire manufacturer General Tire
Continental reinforces its activities by acquiring Temic, the international electronics specialist.
Creation of ADAS Bu
Continental expands its activities in telematics, among other fields, with the acquisition of the automotive electronics business from Motorola.
Through the acquisition of Phoenix ContiTech becomes the world’s largest specialist for rubber and plastics technology outside the tire industry.
1871
1929
1979
1985
1987 1998
2001
2003 2004
20062007
Continental acquires a majority interest in the Slovak company Continental Matador Rubber s.r.o. and expands its position for the Tires and ContiTech divisions in central and eastern Europe.
2012
Continental acquires Siemens VDO Automotive AG and advances to among the top five suppliers in the automotive industry worldwide, at the same time boosting its market position in Europe, North America and Asia.
› Automation in passenger cars is constantly increasing.
› Many automated functions have already been developed for enhancing safety and efficiency of driving.
› Simulation studies and field operational tests indicate that current advanced driver assistance systems (ADAS), such as adaptive cruise control (ACC), have already positive effects, both on traffic flow efficiency and traffic safety .
› OEMs and suppliers predict automated vehicles on highways by 2020.
› Fully and highly automated driving comprising also rural roads and inner-city situations will follow within the next decades.
13.10.20173
Impact of ADAS and automated vehiclesnot only focused on “Safe Mobility”
� SAFE Mobility“70% of all serious accidents could potentially be avoided by driver assistance systems”
Source: BAST Germany
e.g. Management of unnecessary acceleration and hard braking in response to sudden changes of traffic signals (traffic Light detection, Car ro X communication…)
e.g. predicting road profile (magic carpet)Substituting driver in some tasks (head lamp control)
e.g. Elderly drivers (project SAFE MOVE)
� Clean Power
� Comfort
� Mobility
“everything somewhere”,
› provides full autonomous support to the driver (“everything”),
› can be achieved only after a complete perception, comprehension and understanding of the environment
› possible only in specific conditions and situations (somewhere)
“something everywhere”,
› Provides a certain level of automation for every situation,
› this level is different, depending on the specific scenario.
Vehicle automation concepts
13.10.20175
Automation levels definition
13.10.20176
Level 0No
automation
Level 1Assisted
Level 2Partial
Automation
Level 3ConditionalAutomation
Level 4High
Automation
Level 5Full
Automation
Driver must monitor the
system at all the time
Driver Doesn’t have to
monitor the system at all the
time but must be in situation
to resume control
Driver is not required during
defined cases
Automated Vehicle road map
10/13/20178
Time Line 2015 2020 2025 2030 2030 +2010
Blind Spot monitoring
Intersection pilot
Intelligent Speed
Adaptation
Lane Keeping Assist (LKA)
Lane departure warning
Autonomous Emrgency Braking
Emergency Driver Assistant
3D Cloud Based navigation
Vehicle to Vehicle, Vehicle to Device and vehicle t o Infrastructure Communication
Cruise ControlAdaptive Cruise Control
Traffic Jam Assist
Highway Autopilot
Park assist (steering only) Valet Park Assist
Autonomy
Connectivity
Safety
Level 4 Highlyautomated car
Certain drivingsituations e.g.remote parkingand urbanautomateddriving
Level 5 Fully Automated car
Full end to end journey
Level 1 assisted cars
Level 2Partially
automated car
Level 3 Conditionally automated car
ADAS is the safety backbone for HAD
13 October 201710Author, © Continental AG
HAD
ADAS
Enable Fall-Back
ADAS Application
Time
Optimized normal driving DangerDuringaccident
Beforeaccident
Afteraccident
Accidentprevention
PrecrashAction
In Crash post crash actions
Emergency alerts
Somehundred of
ms
someSecondes
minuteSomeminutes
information
100%
Ene
rgy
effic
ienc
y
On-board ADAS functions
V2V
V2I
V2I
Impact domain
Strategic Tactic Operational
Emergency management
Accid
en
t pro
ba
biliy
Active safety Passive Safety
Sensor technologies
Technologies for ADAS and AD can be based upon systems local to the car, i.e. “vehicle resident systems”
Active or passive technologies (Camera, Radar, Lidar etc)
or
on smart, interconnected networks as in the case of vehicle-to-vehicle
(V2V), or vehicle-to-infrastructure (V2I) systems, jointly known as V2X
systems.
13
ADAS Functions
16
Lane Departure Warning – Lane Keeping Assist
� First lane departure warning, lane markers
� Lane-keeping road barrier detection using stereo camera
� Lane-keeping – any border
Applications
LDW assists the driver for vehicle lateral control
Key Features
�Single line tracking
�Detect and track multiple markers (up to 7)
�Lane estimation up to 90m
�Lane marker height check (road works)
�Exit detection (also used for no-navi TSA)
�Classification of multiple marker types
�Lateral Position,
�Lane Curvature, Lane Width, Marker Width, Marker
Type, marker colors, Relative Yaw
› Driver information and warning
› Automatic speed regulation
› Fusion with Navigation possible
Traffic Sign Assist (TSA)
13 October 201718Author, © Continental AG
In the sign post forests of today it’s not always easy to stay on top of things.The Traffic Sign Assist (TSA) features automatic recognition functions through a link between images captured by a camera and the speed limit information stored in the navigation system.
Application
Traffic Light Detection
19
Traffic light recognition intends at localizing, detecting and classifying traffic light and warn the driver about potential violations. Identification of the color (red, yellow, red_yellow, green), the light mode (continuous, blinking) and the shape (circular, arrow left/right…) of the detected traffic lights
Applications Key features
� Warn the driver of potential missed traffic signals
� Start/stop assist
� Emergency Braking
� detection distance up to 80m
� speed up to 80kph
Benefits
› Comfortable, stress-free driving with the flow of traffic
› Greater safety due to defined distance and warning if emergency braking is needed
ADAS FunctionAdaptive Cruise Control + Stop&Go (ACC+S&G)
13 October 201720Author, © Continental AG
This system controls the distance to the traffic in front, even if it’s only stop-and-go. It makes things a whole lot easier for the driver, particularly in congested traffic and tailback situations.
EU NCAP: City – Urban – PedestrianEmergency Brake Assist (EBA)
October 13, 201721Author, © Continental AG
Emergency Brake Assist detects critical traffic situations and ensures optimum braking.If rear-end collision is imminent, the driver is alerted and the braking system is put on emergency standby or even sometimes applies a slight pre-brake to save valuable stopping distance.
�MFCXXX stereo camera or Radar+ camera or SRL cam
�Different processes on the information delivered by the sensors
� Optical flow, Classification
� Object clustering, Object tracking
Key features
Applications
EBA City (2014)EBA Urban (2014) EBA Pedestrian (2016)
� Enhanced driving safety thanks to active braking support
� Reduction of impact speed and impact energy
� Possible interfaces for pre-crash applications, restraint systems or pedestrian protection
Emergency Brake Assist (EBA)Pedestrian Protection with stereoscopic vision
RectificationRectification
Disparityestimation
Optical Flow
ObjectClustering
(FOD)Autocalibration
(online)
Calib L Calib R
Image L Image R
Rect. Image R
2D flow map Disparity map
Object list
Calibration(offline)
ObjectTracking(POD)
Pedestrianclassification
Tracked Object
Rect. Image L
ADAS functions Automated parking
Application
�Surround view image with variable perspectives
�Camera-based environment perception
�Occupancy grid
�Parking space borders (lines, curbs)
�Remote Parking via Smartphone
Automated Parking System with Surround View for more Safety and Comfort
�4 Megapixel 185°-Fisheye Cameras
�Camera-based detection of parking spaces
� Automated longitudinal and lateral control
� Electrical brake control
� Electromechanical steering
� Spaces are displayed on a touchscreen
� Selection of parking space by driver
� Automated parking and maneuvering
24
Vehicle automation – New challenges
Vehicle Automation raises new problems of cooperation between vehicle and driver � Task sharing, Degree of freedom
� Authority, level of automation
� Trust, comprehension and conscience of activated modes
� Management of transition phases (systems hands over command to driver and vice versa)
� Situation awareness
� Workload Achieve reliable and robust models and
monitoring of the driver
Humans will remain part of the system for a long time
25
Why monitoring the driver?
� Road accident main factors: On the contrary to pilots, drivers are responsible of many of the on road accidents.
� Driver’s impairment: It is a critical issue and drivers are not aware of the occurrence of critical phases.
� Advanced driver Assistance: Should be adapted to the driver condition, behavior and environment.
� Driver's availability and ability: When active Driver assistance (lane keeping,…) handovers, drivers’ availability and ability to drive is critical; ADAS can result in driver under load situations.
� Driver's mobility: is a critical issue especially for elderly and disabled drivers but also for Driver with health constraints.
26
Overview of Driver monitoring functions and models
Attention & Distraction
Visual attentionDriving style
Drowsiness classification
Fatigue,Sleepiness& Alertness
Intention
Peripheral distraction
EmotionWorkload
DrivingBehavior
Driving performance
Driver health
Driver awareness
Two Measurement concepts
27
Measurement concepts
i. From in-vehicle sensors and communicationbusesDriving activity :Steering wheel, Pedals, Gearsnon driving activities: phone, radio, navigation,…
ii. From assistance functions camera and radarsensorsHead way, Lateral position,
iii. From vision sensors: Drivermovements/postures/activity
Direct measures
i. From camera sensors looking at driver face
ii. From biomedical sensors: Physiological information, Electro encephalogram, heart rate, etc
Indirect measures
28
Driver MonitoringExample of use case
Features
► Eye Gaze
► Head Pose
► Eye Lid opening
► On-board & ADAS data
► …
Dynamic adaption of driver assistance and the HMI to the driver state
New Warnings
Suppression of annoying warnings
Higher end user acceptance
Adaptive assistance
► Fatigue & Drowsiness
► Inattention & Distraction
► Awareness
► Driving performance
► Driving style
► ….
Main Trigger
Driver behavior
Criticality vs. Driver actions
AdequacyAppropriate?
HMI
Driver wishesLevel of assistance
Driving situation
Driver monitoring & models
Driver statemonitoring
29
Market share for Autonomous Cars
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