We think you have liked this presentation. If you wish to download it, please recommend it to your friends in any social system. Share buttons are a little bit lower. Thank you!
Presentation is loading. Please wait.
Published byEmilie Soller
Modified about 1 year ago
© Ricardo plc 2012 Eric Chan, Ricardo UK Ltd email@example.com 21 st October 2012 SARTRE Demonstration System The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 233683.
2 © Ricardo plc 2012 SARTRE Overview SARTRE objectives –Develop strategies and technologies for vehicle platoons Operating on public motorways / highways No changes to the road and roadside infrastructure –Develop a prototype platooning system Assess under real world scenarios –Evaluate the environmental, safety, congestion and convenience benefits –Illustrate new business models Benefits to lead vehicle operators and platoon subscribers Overall concept –Lead vehicle driven normally by a trained professional driver –Following vehicles have automated driving
3 © Ricardo plc 2012 Concept Definition Use Cases –Lead and following vehicle drivers –Road / traffic situations Traffic modelling –Platoon vehicles –Other non-platoon vehicles Human factors –Drivers in the platoon –Drivers in other surrounding vehicles –Driving simulator Safety analysis –Extended standard techniques to cover a system of multiple automated vehicles –Deliberate external malicious threats –Human factors such as operator error/confusion.
4 © Ricardo plc 2012 Demonstrator System Five-vehicle road train demonstration system –Mixed vehicle types Truck, sedan, estate / station wagon, SUV FH12 truck S60, V60, XC60 cars –Support a range of user scenarios Normal use –Joining, leaving, maintaining Interaction with non-platoon traffic Constraints –Use existing technologies, or slightly enhanced versions of existing technologies, combined with advanced software –No changes to road infrastructure
5 © Ricardo plc 2012 Sensors and Sensor Fusion On-vehicle sensors –Radars: front, side, rear –Lasers (fixed) –Cameras Lead vehicle driver monitoring sensors –Alco-lock –Camera Sensor fusion – vehicle –Combine data from sensors –Different sensors have different strengths under different conditions Sensor fusion – road train –Combine data from vehicles –Form platoon-wide situational awareness
6 © Ricardo plc 2012 Control Systems, Actuators, V2V Communications Automated control of vehicle –Longitudinal Acceleration and braking –Lateral Steering Information used –On-vehicle sensors –Shared vehicle data Actuators build on existing technologies –ACC (Adaptive Cruise Control) –EPAS (Electric Power Assisted Steering) V2V (Vehicle-to-Vehicle) Communications –Shared real-time vehicle data –Enables coordinated control of road train vehicles with minimal delays
7 © Ricardo plc 2012 Longitudinal Control Longitudinal Control has two elements –Using data from the host vehicle sensors Control of the distance to the preceding vehicle –Using data from the other vehicles Coordinated control of all platoon vehicles Transmitted over V2V Driver can always override –Accelerator pedal –Brake pedal –System will take over at the end of the override Harsh braking –Coordinated control allows system response with minimal delays
8 © Ricardo plc 2012 Lateral Control Lateral Control has two elements –Using data from host vehicle sensors and from preceding vehicles (over V2V) Creation and tracking of the lead vehicle’s trajectory –Using data from the lead vehicle, transmitted over V2V Coordinated control of all platoon vehicles Driver can always override steering wheel –System will take over at the end of the override Automated steering vs. manual steering –Comparable steering wheel movements
9 © Ricardo plc 2012 Use Cases Use Case scenarios cover the sequences of actions which the system will have to deal with –Join & leave from rear or side Back Office or ad-hoc –Maintain platoon Speed changes Lane changes Gap changes –Special scenarios Driver manual overrides Degraded modes Non-platoon vehicles
10 © Ricardo plc 2012 Human Machine Interface HMI (Human Machine Interface) components –Touch screen Status of the SARTRE vehicle Status of the whole road train Driver interaction with the system –Voice prompts Important status updates Driver keeps eyes on the road –Haptic seat Alerts driver of status changes –Steering wheel Natural override of automated lateral system –Accelerator and brake pedals Natural override of automated longitudinal system
11 © Ricardo plc 2012 Back Office Register road train availability –Lead vehicle drivers indicate availability and destination of road train Reservation in a road train –Following vehicle drivers find suitable road trains –Potentially join multiple different road trains in a single journey, depending on destinations Handles payments and receipts of fees
12 © Ricardo plc 2012 Conclusions Five vehicle road train of mixed types Based on existing technologies with some software enhancements, combined with advanced control software Up to 90 km/h and 4 m gaps Some real-world scenarios –Interactions with non-platoon traffic Tested on test tracks and public roads Demonstrator system –Not a production implementation Fuel consumption results –16% for following vehicles –8% for lead vehicle
European Truck Platooning Conference Amsterdam, 07 April 2016 Liam Breslin Sustainable Surface Transport DG Research & Innovation European Commission Research.
1. NV DMV FollowupProprietary and Confidential 2 Peloton Technology Founded 2011, Menlo Park CA To dramatically improve highway safety and the efficiency.
1 Development and Evaluation of Selected Mobility Applications for VII (a.k.a. IntelliDrive) Steven E. Shladover, Sc.D. California PATH Program Institute.
1 6th ACSF meeting Tokyo, April 2016 Requirements for “Sensor view” & Environment monitoring version 1.0 Transmitted by the Experts of OICA and CLEPA.
Innovative ITS services thanks to Future Internet technologies ITS World Congress Orlando, SS42, 18 October 2011.
Cooperative crash prevention using human behavior monitoring Susumu Ishihara*† and Mario Gerla† (*Shizuoka University / †UCLA) Danger ! ! !
Ian Fraser Highways Agency Co-operative Vehicle - Highway Systems Research.
1 Challenge the future The Dutch Automated Vehicle Initiative: Challenges for automated driving Dr. R.(Raymond) G. Hoogendoorn Assistant Professor Delft.
Status of ITS research May Peter Sweatman David Kapp.
The Automated Highway System (AHS) and The Intelligent Vehicle Initiative (IVI)
Safety All The Time Oyuki Ogawa Executive Vice President DENSO CORPORATION.
The future of road safety Michael Meyer Robert Bosch GmbH.
CRUISE CONTROL DEVICES Presented by Anju.J.S. CRUISE CONTROL DEVICES.
© Siemens AG, 2002 s CP RS Agenda The Role of IT for Accident-free Driving Interaction with driver’s physical condition Interaction with the roadside environment.
IntelliDrive SM Update AASHTO SCOHTS Annual Meeting May 1, 2009.
Submitted To: Submitted By: Seminar On ADAPTIVE CRUISE CONTROL.
Driver Behavior Models NSF DriveSense Workshop Norfolk, VA Oct Mario Gerla UCLA, Computer Science Dept.
PRESENTED BY:- P.SREENIVASULU ROLL NO:-12AT5A0420 IV-B.Tech ECE.
Safety Distances and Object Classifications for ACSF Informal Document: ACSF
SMART CAR Natural User Interface Technology CAR CUSTOMIZATION BY USER RECOGNITION.
MGM’S COLLEGE OF ENGINEERING NANDED. Presented By: ALEEMUDDIN K.M T.E MECH ROLL NO:72 Guided By: A.I.RAHMAN SIR.
1 Challenge the future Meng Wang Department of Transport & Planning Department of BioMechanical Engineering Supervisor(s): Winnie Daamen, Serge Hoogendoorn,
V2V Target Crash Scenarios, Research Performance Measures, and Prototype Objective Testing John Harding ITS Connected Vehicle Public Meeting Moving From.
IHRA-ITS UN-ECE WP.29 ITS Informal Group Geneva, March, 2011 Design Principles for Advanced Driver Assistance Systems: Keeping Drivers In-the-Loop Transmitted.
Overview of Team Ford: Active Park Assist Software Engineering - CSE435 Michigan State University Fall 2014 Team members: Project Manager: Joe Reeder Facilitator:
SP1 – Meeting April 23 rd Schieberdingen Electronic Systems Page 1 of 13 Integrated Project Co-operative Systems for Road Safety “Smart Vehicles.
Date: 1 October2013 Meeting: Concertation meeting VRA Speaker and organisation: Maarten Oonk, TNO [ Roadmap Automation in Road Transport.
Field evaluation of an advanced brake warning system David Shinar Human Factors 1995 Presented by: Derrick Smets.
THE RISE OF THE CRASH-PROOF CAR John Capp & Bakhtiar Litkouhi IEEE Spectrum May 2014 IS 376 September 4, 2014.
Cooperative Intersection Collision Avoidance Systems Initiative May 2005, ITS America Annual Meeting Mike Schagrin ITS Joint Program Office U.S. Department.
INTRODUCTION APPLICATION IN THE DRIVING SEAT THE DOCTOR WILL SEE WIRED WEARABLES DO NOT KEEP YOUR EYES ON ROAD ADAPTIVE CRUISE CONTROL(A.C.C.) WORKING.
Reimagining the HMI Jay Hotchkiss Research & Innovation Engineer.
PRIVATE/PROPRIETARY Integrated Safety & Drowsy Drivers 2007 Wake Up, Michigan! September 20 th 2007 The Worldwide leader in Automotive Safety Systems Autoliv.
AUTOMOBILES Dimitris Milakis, Transport Institute, Delft University of Technology Envisioning Automated Vehicles within the Built Environment: 2020, 2035,
Mike Schagrin US Department of Transportation ITS Joint Program Office IntelliDrive Safety Program Overview.
SAFESPOT Integrated Project Co-operative Systems for Road Safety “Smart Vehicles on Smart Roads” Roberto Brignolo Centro Ricerche Fiat SAFESPOT Integrated.
The SIPDE and Smith System “Defensive Driving Techniques”
ECOGEM Cooperative Advanced Driver Assistance System for Green Cars Burak ONUR Project Coordinator R&D Support Executive
IntelliDrive Safety Workshop July 20, 2010 Alrik L. Svenson US Department of Transportation National Highway Traffic Safety Administration IntelliDrive.
overview Motivation Ongoing research on VANETs Introduction Objectives Applications Possible attacks Conclusion.
Bringing intelligent systems to the market: the new European research challenge of Field Operational Tests Fabrizio Minarini Head of Sector ICT for Transport.
Automated vehicles on public roads Alwin Bakker.
Wireless traffic service platform for combined vehicle-to-vehicle and vehicle-to-infrastructure communications Authors : T. Sukuvaara and P. Nurmi IEEE.
What is SBC ? Sensotronic Brake Control (SBC) is the name given to an innovative electronically controlled brake system which will fit to future passenger.
Intelligent and Non-Intelligent Transportation Systems 32 Foundations of Technology Standard 18 Students will develop an understanding of and be able to.
Research on HMI Homework item 1 (ACSF-01-13) ACSF Toshiya Hirose, Toru Kojima Vehicle Safety Research Department National Traffic Safety and Environment.
INTRODUCTION SELF-DRIVING CARS FUTURE OF AUTOMOBILES HYDROGEN POWERED CARS 1 GROUP 10 1)G.V.S.ABHISHEK 2)MOHIT AGARWAL 3)T.R.GOKUL.
Maarten Oonk MSc.Joakim Svensson Sr. Market Manager TNO [ Automation in Road Transport Past, Present & Future Date: 7th of March 2013.
Synergies Between PRT and Driverless Cars Prof. Em. Ingmar Andreasson LogistikCentrum AB.
Automated vehicles on public roads Marieke Kassenberg.
© 2017 SlidePlayer.com Inc. All rights reserved.