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SARTRE Demonstration System. Eric Chan, Ricardo UK Ltd [email protected] 21 st October 2012. 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. SARTRE Overview. - PowerPoint PPT Presentation
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© Ricardo plc 2012
Eric Chan, Ricardo UK [email protected] 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 allowssystem response withminimal 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
– Comparablesteering wheelmovements
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 automatedlongitudinal 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