Nouveaux concepts de mobilité urbaine: retour sur l'expérience de CityMobil



Similar documents
3D Vision An enabling Technology for Advanced Driver Assistance and Autonomous Offroad Driving

FURBOT : un nouveau système de transport de marchandises en ville. Evangeline Pollard INRIA-RITS

The demonstration will be performed in the INTA high speed ring to emulate highway geometry and driving conditions.

Last Mile Intelligent Driving in Urban Mobility

Applications > Robotics research and education > Assistant robot at home > Surveillance > Tele-presence > Entertainment/Education > Cleaning

Editorial. Project update. Towards advanced transport for the urban environment ISSUE 8 May

Integration of PTC and Ride Quality Data. Presented by: Wabtec Railway Electronics, I-ETMS PTC Supplier. and

JEREMY SALINGER Innovation Program Manager Electrical & Control Systems Research Lab GM Global Research & Development

3D Vision An enabling Technology for Advanced Driver Assistance and Autonomous Offroad Driving

Data Sheet. Remote Presence for the Enterprise. Product Overview. Benefits of Video Collaboration Robots

IMARA Informatique, Mathématiques et. Automatique pour la Route Automatisée

Common platform for automated trucks and construction equipment

Mobile Access Controller

«Construction Equipment in an Agile World» Plenary Session, 16th October 2014, Crowne Plaza -Antwerp

HAVEit. Reiner HOEGER Director Systems and Technology CONTINENTAL AUTOMOTIVE

SECURITY AND EMERGENCY VEHICLE MANAGEMENT

TITLE A CTS FOR THE NEW ROME EXHIBITION

September 8th 8:30 AM 10:00 AM PL1: Reinventing Policy to Support the New ITS

URBAN MOBILITY IN CLEAN, GREEN CITIES

Existing safety technology is the driverless vehicle already here? Matthew Avery Safety Research Director

Industrial Internet, Internet of Things and Big Data: business issues pure players vs bricks & mortars

Impact on Society and Economy

Management of electric vehicle fleet charging

The Future of Mobile Robots In 2020, 26 Million Mobile Robots Will Enable Autonomy in Smart Factories, Unmanned Transportation, and Connected Homes

Parking Management. Index. Purpose. Description. Relevance for Large Scale Events. Options. Technologies. Impacts. Integration potential

Introduction CHAPTER 1

Management of electric vehicle fleet charging

Current Challenges in UAS Research Intelligent Navigation and Sense & Avoid

Traffic Management for a Smarter City:Istanbul Istanbul Metropolitan Municipality

Computer Networking. Definitions. Introduction

Simulation-based traffic management for autonomous and connected vehicles

Montgomery County Bus Rapid Transit System Information Technology Needs

URBAN PUBLIC TRANSPORT PLANNING IN TEHRAN AND THE OUTCOME OF THE IMPLEMENTED BRT LINES

Farshad Jalali. Hojat Behrooz

By: M.Habibullah Pagarkar Kaushal Parekh Jogen Shah Jignasa Desai Prarthna Advani Siddhesh Sarvankar Nikhil Ghate

Project Overview Mapping Technology Assessment for Connected Vehicle Highway Network Applications

Demand Responsive Transport as integration to urban regular transport service: a case in Cape Town

INTERNET FOR VANET NETWORK COMMUNICATIONS -FLEETNET-

Rail research Successes and challenges

Channels of Delivery of Travel Information (Static and Dynamic On-Trip Information)

GPS & GSM BASED REAL-TIME VEHICLE TRACKING SYSTEM.

Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey

City of Vantaa New Plans and Projects

ACCIDENTS AND NEAR-MISSES ANALYSIS BY USING VIDEO DRIVE-RECORDERS IN A FLEET TEST

Current and Future Trends in Hybrid Cellular and Sensor Networks

Vehicle Tracking System using GPRS

Technical Trends of Driver Assistance/ Automated Driving

Mobile 360 Degree Imagery: Cost Effective Rail Network Asset Management October 22nd, Eric McCuaig, Trimble Navigation

M2M ATDI services. M2M project development, Business model, Connectivity.

Traffic Monitoring Systems. Technology and sensors

Definitions. A [non-living] physical agent that performs tasks by manipulating the physical world. Categories of robots

IP-S3 HD1. Compact, High-Density 3D Mobile Mapping System

The deployment of public transport innovation in European cities and regions. Ivo Cré, Polis

Right of way for mobility. The Bus Rapid Transit (BRT) traffic concept. MAN kann.

ETP 2010 Conference Urban Mobility the door-to. to-door strategy

sonobot autonomous hydrographic survey vehicle product information guide

Optimizing Enterprise Network Bandwidth For Security Applications. Improving Performance Using Antaira s Management Features

Can I Cost-Effectively Monitor Critical Remote Locations?

Visual Servoing using Fuzzy Controllers on an Unmanned Aerial Vehicle

SESAR Air Traffic Management Modernization. Honeywell Aerospace Advanced Technology June 2014

Mobile Mapping. VZ-400 Conversion to a Mobile Platform Guide. By: Joshua I France. Riegl USA

INTELLIGENT TRANSPORTATION SYSTEMS IN WHATCOM COUNTY A REGIONAL GUIDE TO ITS TECHNOLOGY

Cisco Mobile Network Solutions for Commercial Transit Agencies

SONOBOT AUTONOMOUS HYDROGRAPHIC SURVEY VEHICLE PRODUCT INFORMATION GUIDE

Tools and Operational Data Available st RESOLUTE Workshop, Florence

Aerospace Information Technology Topics for Internships and Bachelor s and Master s Theses

Automated road transport in Finland

An OSGi based HMI for networked vehicles. Telefónica I+D Miguel García Longarón

Transport demands in suburbanized locations

NAUTI FLY 75 AUTOMATIC 0,75m Ka band Trolley

Modelling and optimization of renewable energy supply for electrified vehicle fleet

What is this Course All About

2013 International Symposium on Green Manufacturing and Applications Honolulu, Hawaii

Development of an Automotive Active Safety System Using a 24 GHz-band High Resolution Multi-Mode Radar

VBA Macro for construction of an EM 3D model of a tyre and part of the vehicle

Simulation-based comparative analysis for the design of Laser Terrestrial Mobile Mapping Systems

DISASTER RECOVERY AND NETWORK REDUNDANCY WHITE PAPER

The Mobility Opportunity Improving urban transport to drive economic growth

Grant agreement no: FP SPENCER: Project start: April 1, 2013 Duration: 3 years XXXXXXXXXXDELIVERABLE 6.6XXXXXXXXXX

Use of GPS systems with people count sensors for transport planning studies

How To Fuse A Point Cloud With A Laser And Image Data From A Pointcloud

Innovative technologies and solutions for (e-)buses

From reconfigurable transceivers to reconfigurable networks, part II: Cognitive radio networks. Loreto Pescosolido

Demystifying Wireless for Real-World Measurement Applications

Location Identification and Vehicle Tracking using VANET(VETRAC)

Use of a Web-Based GIS for Real-Time Traffic Information Fusion and Presentation over the Internet

Recent developments in EU Transport Policy

The Wireless World - 5G and Beyond. Björn Ekelund Ericsson Research

Paris Action Plan for Air Quality

UAVNet: Prototype of a Highly Adaptive and Mobile Wireless Mesh Network using Unmanned Aerial Vehicles (UAVs) Simon Morgenthaler University of Bern

Sustainable Mobility in Almada

HidnSeek Tracker Solution: Standalone GPS Tracker ST- 1A

Mobile Cloud Networking FP7 European Project: Radio Access Network as a Service

T-REDSPEED White paper

Smart Transport ITS Norway

Novel AMR technologies and Remote Monitoring

SELF-DRIVING FREIGHT IN THE FAST LANE

Internet of Things, 5G, Big Smart Data Interplay. The Convergence and Integration of Mobile Communications, Internet, and Smart Data Processing

An IEEE static mesh network design for isolated rural areas in developing regions

Transcription:

: retour sur l'expérience de CityMobil Mines ParisTech, 08 Juin 2012 Fawzi Nashashibi INRIA Equipe-projet IMARA

Outline CityMobil : objectifs Les démonstrateurs de CityMobil Les navettes Cybus à La Rochelle: description and défis techniques Performances et évaluations Conclusion & travaux futurs 08/06/2012 2

The CityMobil project FP6 Project Project start: May 1, 2006 Project duration: 5 years Coordinator: TNO No. of Partners: 29 Project Budget: 40 million Euros EU funding: 11 million Euros Budget division: About 40% for demo s About 60% for R&D 08/06/2012 3

The CityMobil project: objectives To achieve a more effective and sustainable organisation of urban transport by: The development of advanced concepts for advanced road vehicles for passengers and goods. The introduction of new tools for managing urban transport Removing barriers in the way of large scale introduction of automated transport systems: By bringing the implementation of automated transport in urban areas a major step forward Through large and small scale demonstrations of Automated transport systems 08/06/2012 4

CityMobil demonstrations Advanced bus PRT Cybercar Advanced city cars Large demo Castellon (ES) Heathrow (UK) Rome (I) Small demo Showcases La Rochelle (F) Daventry (UK) Vantaa (FI) Trondheim (N) La Rochelle (F) Orta San Giulio (I) 08/06/2012 5

Examples of advanced transport systems Cybercars Advanced city vehicles Advanced Buses Personal Rapid Transit 08/06/2012 6

3 large scale implementations of advanced transport systems: city demonstrations Heathrow Rome Castellón 08/06/2012 7

City demos: Heathrow Connects Business Parking with T5 3.9 km of single guideway 21 vehicles 3 stations 5min journey time Business Car Park Traverses 2 rivers and 7 roads Green belt land Negotiates aircraft surfaces Bridges in-ground services Conforms to T5 architecture Looks Intended Terminal 5 station Terminal 5 08/06/2012 8

City demos: Heathrow 08/06/2012 9

City Demos: Rome A cybercar system that connects the car park with the entrance of the new Rome Exhibition buildings 08/06/2012 10

City Demos: Rome 29 passengers; Max speed: 24 km/h; Obstacle detection systems: laser scanner and bumper switches. 08/06/2012 11

08/06/2012 12

An advanced bus system that connects the university, the city centre of Castellón and the coast City Demos: Castellón 08/06/2012 13

City Demos: Castellón 08/06/2012 14

Expected results of CityMobil General results: A much better understanding of the possibilities of automated transport systems in cities An improved acceptance of advanced transport systems among the public as well as among authorities Less legal, administrative, operational and technological barriers for the implementation of advanced urban transport systems technical validation and evaluation of the systems 08/06/2012 15

La Rochelle Small Demos 08/06/2012 16

La Rochelle demo: objectives To test a real-life implementation of cybercars in an urban context To evaluate the system s performance: Technically Transportation efficiency Economically* Energy consumption To evaluate users acceptance 08/06/2012 17

La Rochelle demonstration The showcase motivated the City to host a demonstration of cybercars The City proposed an urban test site: 2 km 5 stations Mixed traffic 4 crossings with car traffic Traffic priority given to cybercars (stop signs) Infrastructure not to be equipped! 08/06/2012 18

La Rochelle demonstration 2-3 INRIA s CyBus platforms On-demand service as an horizontal elevator Speed limited to 15 Km/h An operator is always on-board (legal reasons) Demonstration ran between May and July 2011 and in November-December 2012 at INRIA 08/06/2012 19

La Rochelle: site Old city centre Paris La Rochelle Electric boat line Demo site BRT line 08/06/2012 20

La Rochelle: site Car-sharing station Electric boat stop Bike-sharing Museums area Conference Centre Technoforum (University) / BRT stop Cybercars depot 08/06/2012 21

INRIA s CyBus vehicles Capacity: 5 pax Max. speed: 18 Km/h Mass: 500 Kg Front & rear LIDARs Ultrasounds IP cameras Guidance: LIDAR-based SLAM DEMO 08/06/2012 22

INRIA s CyberGo vehicle Capacity: 8 pax Speed: 30 Km/h Mass: 700 Kg Sensors : - 4 LIDARs guidance - US - Cameras 08/06/2012 23

Stations Accessibility for elderly Vehicle call interface Wi-Fi network relay Users information on the booths: Instructions Usage conditions Electricity for stations Solar energy not feasible Batteries recharged overnight from public lightning 08/06/2012 24

Demonstration site constraints Road narrowness = stations only on 1 side Vehicle must drive forward & backwards 08/06/2012 25

Cybercars Demonstration Full IPv6 architecture Communications ~200 m between stations Interference of trees Wifi routers and antennas were installed on 4,5 m poles Full Wi-Fi coverage from the depot to the last station (~1 Km) 08/06/2012 26

Cybercars circulation scheme 08/06/2012 27

Demonstration site constraints Pedestrian area = limited speed 08/06/2012 28

Demonstration site constraints Intersections = cybercars priority crossing at limited speed 08/06/2012 29

08/06/2012 30

08/06/2012 31

08/06/2012 32

08/06/2012 33

Technical challenges of the navigation in dense urban areas 08/06/2012 34

Challenges Environment mapping and localization in crowded areas: GPS shortage, laser masking, vehicle «kidnapping» Fusion of GPS-IMU and Laser-based SLAMMOT Perception: Obstacle detection and tracking Behavior modeling: cognitive perception Uncertain obstacle classification Cooperative perception Precise docking: GPS/SLAM-based: 10 cm error Tomorrow: Vision based docking (cf. AMARE project)? Beacons detection and localization 08/06/2012 35

Challenges Path planning in an unknown dynamic environment: Navigation strategy Planned paths vs. Reactive planning Overtaking strategies (obstacles types, sizes and speeds) Communication in dense and noisy areas Technology Centralized vs. Decentralized Optimization of the demand: fleet management Vehicle management System (VMS) based on a new V2I COM architecture Task planning and supervising (scheduling) Fault tolerance Sensors, Processors, Communication bus Distributed architecture: Redundancy 08/06/2012 36

Global architecture of the CYBUS 08/06/2012 37

Sensors configuration for obstacle detection, localization and mapping 08/06/2012 38

Precise Localization System Solution 1. Laser based SLAM For Providing an Accurate Map and Position 2. Fuse With IMU Data Using EKF For Improving Localization precision 3. Fusion of GPS/SLAM for a geo-referenced localization 08/06/2012 39

New embedded system Simple distributed architecture Based on DSPIC and Syndex software: Tasks (re-)scheduling Handles redundancy and fault tolerance 08/06/2012 40

Communication architecture New architecture: clearly separates the layers Discovery services : Avahi / Bonjour Embedded communication libraries: dohc / chassis / cables Logic layer : RTMaps 08/06/2012 41

Communication and the VMS Using high frequency wifi Dynamic IPv6 network and routing at the kernel level using Batman Standards: IPv6/CALM Operates on layer 2 : Allow IPv4, IPv6, DHCP... Nodes do not need an IP Based on connection quality 08/06/2012 42

The VMS Knows all the vehicles Aware of the static map Takes decision when needed 08/06/2012 43

Vehicles Interactions Definition: Take into account all vehicles parameters in the decision process Centralized vs. Decentralized Centralized : VMS based V2I COM + Global environment modeling reasoning + optimized - Sensible to COM outages general perturbation Decentralized : V2V based - Local model - Non-optimal + COM outages local perturbation 08/06/2012 44

Objectives: Vehicles Interactions Ensure optimal system planning: Fleet management for the transportation service Handle complex situations Handle conflicts and blockages Example : static obstacle avoidance Design & development of 2 techniques for vehicle avoidance maneuvers : 1. Planning and Nonlinear Adaptive Control 2. Use of elastic bands for autonomous local guidance 08/06/2012 45

Planning and Nonlinear Adaptive Control Developed for both CityMobil and HAVEit projects! (published in IEEE ITSC 2011 Washington) e y e θ e x 08/06/2012 46

Planning and Nonlinear Adaptive Control The overtaking maneuver involving two vehicles is established as a three-phase maneuver Our approach: Consecutive tracking of reference virtual points R 1, R 2, R 3 situated at desired distances from the overtaken vehicle with a virtual reference point L attached to the overtaking vehicle. Phase 1 Phase 2 Phase 3 R 1 R 2 L d R 3 08/06/2012 47

Mathematical model for the 1st phase 0 0 1 0 0 0 0 0 1 0 1 0 0 cos 0 sin sin 0 cos 1 1 1 1 2 2 Rx t n x y x v L L v e L e e L e e e e Planning and Nonlinear Adaptive Control v x L a 2 tan α front wheel steering angle (e x, e y ) coordinates of the reference point L in R 1 x 1 y 1; (L 1t, L 1n ) coordinates of the reference R1 in A1xy linked to the overtaken vehicle. 08/06/2012 48

Trajectory planning Generation of smooth trajectories for point-to-point motion for every phase in terms of the posture errors (e x, e y ) with respect to the moving reference frames R i x Ri y Ri which are rigidly linked to the overtaken vehicle. Planning and Nonlinear Adaptive Control 3 0 3 2 0 2 0 1 0 3 0 3 2 0 2 0 1 0 ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( t t a t t a t t a a t e t t a t t a t t a a t e y y y y d y x x x x d x 0 0 0 0 ) ( ) ( x d x x d x e t e e t e 0 0 0 0 ) ( ) ( y d y y d y e t e e t e Initial conditions Final conditions ) ( ) ( 0 ) ( f Rx f d x f d x t v t e t e 0 ) ( 0 ) ( f d y f d y t e t e Our approach: R 1 R 2 R 3 L d 08/06/2012 49

[m] Planning and Nonlinear Adaptive Control First validation with simulated data Second validation with the Cybus 3 2.5 2 1.5 1 0.5 0-0.5 0 10 20 30 40 50 60 70 80 [m] 08/06/2012 50

Planning and Nonlinear Adaptive Control Problems: Needs the exact vehicle dimensions (OK for communicating vehicles!) Needs an accurate position and speed estimation (measurement) What if there are several «hidden» vehicles? What if the vehicle moves again? What if a hostile obstacle threatens the vehicle? 08/06/2012 51

Elastic (bubbles) bands Elastic bands are proposed to close the gap between global path planning and real-time sensor-based robot control. An elastic band is a deformable collision-free path. Subjected to artificial forces, the elastic band deforms in real time to a short and smooth path that maintains clearance from the obstacles. While providing a tight connection between the robot and its environment, the elastic band preserves the global nature of the planned path. Adapted to holonomic (non-) vehicles. [Khatib M. and Jaouni H., 1996] [Quinlan and Khatib O.] 08/06/2012 52

Elastic (bubbles) bands Objective Laser impacts L Our approach: Figure: Willow Garage implementation Reference trajectory: Registered path or; Planned trajectory Figure: SIVIC simulator (INRIA) 08/06/2012 53

Scenarios demonstrations 08/06/2012 54 08/06/2012 54

Extension scenarios Scenario 1 Scenario 2 08/06/2012 55

Extension scenarios Scenario 3 Scenario 4 CM General Assembly 08/06/2012 56

Extension scenarios Scenario 5 Scenario 6 CM General Assembly 08/06/2012 57

Scenarios 1 CityMobil Presentation 08/06/2012 58

Scenario 2 CityMobil Presentation 08/06/2012 59

Scenario 3 CityMobil Presentation 08/06/2012 60

Scenario 6 Movie CityMobil Presentation 08/06/2012 61

System evaluation 08/06/2012 62 08/06/2012 62

Users acceptance (1/2) 6 indicators evaluated: Ease of use ranking (in a rate from 5 to 1): 3.8 User willingness to pay: 0.6 Info availability, info comprehensibility, perception of safety, fear of attack 08/06/2012 63

STATISTICS 899 Passengers (200 interviews) GENDER < 16 years 9% AGE M 51% F 49% > 60 years 31% 16-25 years 27% 46-60 years 15% 36-45 years 10% 26-35 years 8% 08/06/2012 64

User acceptance (2/2) 08/06/2012 65

Transportation results Total operation time: 73 days Total Veh Km: 343,3 Total vehicle trips: >1700 Total passengers: >1000 Average vehicle occupancy: 33% Average journey time per OD pair: 1 15 2 40 Average waiting time: 2 30 Effective system capacity: 100 pax/h Nouveaux concepts de mobilité CM General urbaine Assembly 08/06/2012 66

Environment Daily consumption: 1.95 kwh Energy efficiency: 0.38 kwh/pax km 08/06/2012 67

Technological success Failure rate of the control indicator: 7% Mean time between failures: 14 days 08/06/2012 68

Origin of users They come from They came Specialement De passage La Rochelle Agglomération de La Rochelle En Charente Maritime France, Etranger 23% 41% 35% 14% 77% 10% CM General Assembly 08/06/2012 69

How did you hear about the system? Télevision, radio 22% Internet Office du tourisme 57% 10% 1% 1% Bouche à oreilles Presse En passant devant 9% 08/06/2012 70

Advantages Other (modern, available..): 14% Economique 8% Automated 14% Practical 10% Quiet 20% Green 34% 08/06/2012 71

Disadvantages Imposed circuit 6% Other 9% Waiting time 3% Short travel 8% Low speed 42% Small size 23% Pas sûr 3% Confort 6% 08/06/2012 72

Security and safety Do you feel safe? Are you afraid of having an accident? oui non oui non 27% 35% 73% 65% 08/06/2012 73

Could this transport system be: Adapted to the city? Generalized? oui non oui non 6% 7% 94% 93% 08/06/2012 74

Are you willing to pay? oui non 5% 36% 43% 52% 64% Carte Yélo < 2 >2 08/06/2012 75

Vandalism 08/06/2012 76

Accident 08/06/2012 77

Conclusion & Future work 1. Technical perspectives Extended perception Allows complex situations handling Allows more intelligent overtaking Example: overtaking of stopped aligned vehicles Example: barricades, crossing pedestrians Handles non communicating vehicles Introduction of vision technology Fusion & redunduncy 08/06/2012 78

Conclusion & Future work Deployment of advanced communications New «communication boxes» under design Achieve sensor-based docking: GPS based Vision based (AMARE project) Magnets 08/06/2012 79

Conclusion & Future work Test new scenarios with multiple vehicles / multiple platforms Compliance & genericity Introduce/study «tricky» situations : moving obstacles Approaching hostile obstacle Introduce platooning Autonomy vs. VMS based architecture 08/06/2012 80

Conclusion & Future work 2. General perspectives At INRIA : Permanent demonstrator / service in 2012 (Rocquencourt) In France: Mobilité 2015 / SYSMO 2015 Europe : CityMobil-2 Address technical and legal issues acceptability and certification 08/06/2012 81

Thank you! 08/06/2012 82

On demand transport system in La Rochelle. 08/06/ CityMobil Presentation 83