HAVEit Highly Automated Vehicles for Intelligent Transport

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1 HAVEit Highly Automated Vehicles for Intelligent Transport Holger Zeng Project Manager CONTINENTAL AUTOMOTIVE

2 HAVEit General Information Project full title: Highly Automated Vehicles for Intelligent Transport Project coordinator: Dr. Reiner Hoeger, Continental Automotive GmbH Integrated project: ICT , project no Start: 01 February 2008 End: 31 July 2011 Budget / funding: 28 M / 17 M Consortium 18 Partners plus 5 Third Parties: 2

3 HAVEit Motivation and Background Motivation: Improvement of safety and environmental friendliness Approach highly automated vehicle applications supporting the driver in overload and underload situations Background Driver strengths: take responsibility, draw conclusions, monitor systems Driver weakness: tendency to get distracted and inattentive in long-lasting monotonous driving situations Automation strength: attentiveness independent of trip duration 3

4 HAVEit Proposed Solution Automation spectrum Automated Driving is a multiple use technology Less accidents Less traffic jams by steady flow, no disturbance injection Improved energy efficiency Automation and cooperative technologies go hand in hand 4

5 HAVEit Technical Objectives Technical objectives Research Needs Provide technologies for situation awareness (driving scene, vehicle state, driver state) Develop effective and efficient algorithms to define maneuvers and trajectories Decide on the optimum automation level (task repartition driver automation) Develop suitable HMI concept Elaborate safe vehicle architecture Show new capabilities and functions in seven demonstrator vehicles (passenger cars, trucks and bus) Integration and optimisation progressing according to plan. 5

6 HAVEit Main Outcomes Common HAVEit Architecture Driver interface components to assess the driver state and to integrate the driver in the automation loop Command layer to define maneuver, trajectory and automation level and to generate the safe motion control vector Driver monitoring Driver Driver state assessment HMI Mode selection unit automation level Environment sensors maneuver trajectory Command generation and validation Sensor data fusion Co-Pilot motion control vector Vehicle sensors joint system Perception layer for real-time scene recognition Execution layer Drivetrain control to perform the safe motion control vector Steering Brakes Engine Gearbox 6

7 HAVEit Main Outcomes Joint System: Driver Co-System Co-pilot º Performs motion planning accounting a current situation º Generates optimal trajectories that fit with the objectives: - Collision free trajectories - Lane departure supervision º Optimal trajectories in terms of e.g. trajectory lengths, fuel consumption, safety margins º Two level computation - Strategy level for maneuvers selection (coarse level) - Planning level: trajectory planning and risk assessment (fine level) Maneuver grid 7

8 HAVEit Main Outcomes Joint System: Driver Co-System Mode Selection and Arbitration Unit (MSU) º Situation dependent selection of the automation level Driver State Assessment (DSA) º Driver s activity and driving performance correlate with increasing drowsiness level and distraction º Fusion of direct (camera based) and indirect (driver activity based) attentiveness and drowsiness information (fusion is based on state and confidence parameters) º Verification via simulator studies Information Warning Take over request 8

9 HAVEit Main Outcomes Highly automated vehicle applications Safety and functional architecture applications Joint system Brake-by-wire Architecture migration demonstrator truck demonstrator 9

10 HAVEit Main Outcomes Highly automated functions for use on public roads Automated assistance in roadworks and congestion Temporary auto-pilot Automated queue assistance Active green driving 10

11 HAVEit Main Outcomes Automated assistance in roadworks and congestion º Inquiry of the German expert organization DEKRA among 1700 drivers about roadworks 46% feel here frequently uncertain one out of six drivers (17%) feels sometimes real fear usually 42% even avoid the left lane º Challenging environment multiple/missing lane marks other vehicles construction barriers narrow space Driver needs assistance but today's assistance systems can t provide sufficient confidence to support him 11

12 HAVEit Main Outcomes Automated assistance in roadworks and congestion º Sensor system to observe environment 12

13 HAVEit Main Outcomes Automated assistance in roadworks and congestion (ARC) Example scenario: 1 st system functionality 13

14 HAVEit Milestones Milestones plan Kick-off meeting M1 Requirement and specification phase completed M2 Concept phase completed M3 Generic development completed M4 Vehicle integration completed, first system operation M5 Optimised demonstration vehicles Feb 2008 Jan 2009 Apr 2009 Jan 2010 Oct 2010 Jul 2011 Milestone status in progress according to plan 14

15 HAVEit Next steps Remaining technical challenges for all HAVEit applications º Implement further use cases and scenarios º System optimisation Perception layer: Sensors and data fusion Command layer: Joint system driver co-system including mode selection and transitions Execution layer: Control of vehicle actuators HMI: º Push (pre-)homologation activities Further harmonisation of HAVEit HMI Pre-homologation of brake-by-wire system (e.g. for trucks) Preparation of dissemination measures, in particular Final Event 15

16 HAVEit Final Event Don t miss our final event and save the date Date: and at First Grand Hotel, Borås and Volvo Proving Ground, Hällered, Sweden Interested to attend the event and feel highly automated driving? Please send an with your contact details to: registration@haveit-eu.net We are looking forward to welcoming you to our final event! 16

17 Vejforum 2010, 09 December 2010 Nyborg, Denmark Thank you for your attention More information: 17

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