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![• Low latency
• Predictable latency
• Reduce worst case delays
• Priority scheduling/pre-emption
• Instant switching to alternate
paths
• Ensure delivery
• Reliable for critical operations
• Under fading conditions
• Congestion and Doppler
• Fault tolerance and redundancy
• Security and Privacy
• Time delay implies distance
• Regulatory compliance
• Scalable to larger networks
17 January 2016
Time Sensitive Network Issues
IEEE Network Specs
802.11p – Wireless Vehicles
[DSRC]
802.1AS – Time Sync
1588v2 – Precise Time Protocol
802.1Qac – Path Control
802.1Qbv – Scheduled Traffic
802.1Qbu – Pre-emption
802.1Qca – Path Control
802.1Qcb – Seamless Redundant
802.11Qcc – Stream Reservation
802.11Qci – Filtering and Policing
802.11Qv – Time Mgmt Protocol](https://image.slidesharecdn.com/timing-considerations-driverless-car-160202223137/75/The-Importance-of-Timing-to-Autonomous-Vehicle-Navigation-17-2048.jpg)
![18 January 2016
Time Sensitivity for Automotive Networks
Let’s do the numbers [Order of Magnitude]
• 60 mph => 100 km/hr
30 m/s => 3 cm/millisecond
• System level response => msec
=> 1KHz update rates minimum
• Subsystem responses =>
10 – 100 usec range
• Network latency =>
< 100 usec over multiple hops [5-7]
• alternate fault tolerant paths
• all Bit Error Rate [BER] conditions
Latency is key if the network is part of the control loop:
• Stability
• Dynamic performance](https://image.slidesharecdn.com/timing-considerations-driverless-car-160202223137/75/The-Importance-of-Timing-to-Autonomous-Vehicle-Navigation-18-2048.jpg)
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- 1. The Importance ofTiming to Autonomous Vehicle Navigation John Fischer, CTO jfischer@spectracom.com
- 2. 2 January 2016 Spectracom:Precise, Secure, Synchronized Bringing Technology to: Military, Aerospace UAV’s Electronic Warfare C4ISR High-End Commercial Apps Datacenters Robotics/Telematics IDM GIS Data Mining Spectracom simplifies Position, Navigation, and Timing integration into our customer’s systems.
- 3. 3 January 2016 GlobalOrganization 3 Multi-domestic strategy 100+ Employees in 6 countries High reliability and superior service All sites ISO 9001 Registered USA Brazil UK France Russia China
- 4. • ADAS alreadyin luxury cars and moving to mainstream • Anti-lock brakes and anti-slip traction control • Lane departure warning system • Speed assistance and autonomous emergency braking • Automatic parking • Driver wake-up and attention control • Pedestrian and low-speed obstacle avoidance Advanced Driver Assisted Systems 4 January 2016
- 5. • Mix ofcorrelated sensors for navigation • Radar and proximity sensing • Optical, vision systems • GNSS • Accurate map matching • New regulations for safety • Four US states have laws for autonomous vehicles on public roads • Google – over 1 million miles tested • UK -2013 – testing on public roads • France – 2015 – 2000 km roads for testing – Peugeot-Citroen • Toyota Lexus GS autonomous car on Tokyo expressways • Canada – starting 2016 testing 5 January 2016 ADAS -> Driverless Car
- 6. 6 January 2016 Safeand Secure Navigation GNSS GNSS by itself is insufficient • Weak signal / interference • Not always available • Tunnels • Parking garages • Urban canyons • City skyscrapers
- 7. 7 January 2016 Safeand Secure Navigation GNSS Vision Systems Radars / Proximity Sensors Inertial Measurement Road / Map Matching Real Time Data Networking GNSS by itself is insufficient Hybrid system must: • be safer than a human driver • have high reliability and integrity • utilize many sensors • including real time networks • Weak signal / interference • Not always available • Tunnels • Parking garages • Urban canyons • City skyscrapers
- 8. Map Matching Database mustbe constantly updated to be current IMUs Self contained but not accurate over the long term Autonomous Nav No interference or spoofing possible Reference Nav Determine position in relation to other reference points GPS Weak signal but ubiquitous in open sky, most accurate Vision Systems Inhibited by smoke, fog precipitation Spotty coverage, inaccurate; Skyhook + E911 requirements Cellular Ubiquitous but inaccurate RFID Low cost, place sensors where needed – warehouse, controlled space Active Tx Radar, Lidar, Sonar Crowd-Sourced Via a network, location and proximity data is shared Signals of Opportunity Not necessarily designed for navigation, but useful for determining range or bearing DSRC Dedicated Short Range Comm – real time networking for V2V and V2X links 8 January 2016 Alternative PNT in Autonomous Unmanned Systems Automotive autonomous navigation is part of a larger subject of robotic navigation in the absence of GPS.
- 9. Autopilot Systems from Guided Missilesand Spacecraft to UAVs and Driverless Car over 50 years of Technology Advancement 9 January 2016
- 10. 10 January 2016 AutopilotExample – Cruise Control Automatically maintain a set speed
- 11. Underdamped – fastbut erratic Overdamped – smooth but slow Critically damped – optimum 11 2 February 2016 Dynamic Response and Stability Too much delay in feedback loop – instability and oscillation Low delay – tracking
- 12. 12 2 February2016 Closed Loop Control – a Primer • Control a process via feedback • Accuracy determined primarily by the sensor • PID Controller – error value drives the system Proportional Integrative Differential Error = Setpoint – Measured Output
- 13. • Setpoint <=desired trajectory or waypoint • Measured output <= realtime position sensors • Error => steering commands • Same process as: • Guided missiles • Spacecraft • Aircraft • Robotics 13 2 February 2016 Autopilot Navigation GNSS Vision Systems Radars / Proximity Sensors Inertial Measurement Road / Map Matching Real Time Data Networking
- 14. The Connected Car thenetwork as part of the autopilot navigation system 14 January 2016
- 15. 15 January 2016 V2XCommunications • V2V – Vehicle to Vehicle • V2I – Vehicle to Infrastructure V2X communications integrated with navigation system can increase safety greatly 1. Real time data network • Traffic lights • Emergency vehicles • Construction zones 2. Coordination / early warning • Advanced braking • Platooning 3. “Crowd-sourced” location • Shared location • Proximity detection DSRC – Dedicated Short Range Communications
- 16. 16 January 2016 TheConnected Car –Two Separate Networks Real Time / Critical Connectivity Non-Real Time / User Experience Connectivity where every millisecond matters where a few seconds is ok Navigation Internet, Infotainment, Telematics, etc. cellular DSRC
- 17. • Low latency •Predictable latency • Reduce worst case delays • Priority scheduling/pre-emption • Instant switching to alternate paths • Ensure delivery • Reliable for critical operations • Under fading conditions • Congestion and Doppler • Fault tolerance and redundancy • Security and Privacy • Time delay implies distance • Regulatory compliance • Scalable to larger networks 17 January 2016 Time Sensitive Network Issues IEEE Network Specs 802.11p – Wireless Vehicles [DSRC] 802.1AS – Time Sync 1588v2 – Precise Time Protocol 802.1Qac – Path Control 802.1Qbv – Scheduled Traffic 802.1Qbu – Pre-emption 802.1Qca – Path Control 802.1Qcb – Seamless Redundant 802.11Qcc – Stream Reservation 802.11Qci – Filtering and Policing 802.11Qv – Time Mgmt Protocol
- 18. 18 January 2016 TimeSensitivity for Automotive Networks Let’s do the numbers [Order of Magnitude] • 60 mph => 100 km/hr 30 m/s => 3 cm/millisecond • System level response => msec => 1KHz update rates minimum • Subsystem responses => 10 – 100 usec range • Network latency => < 100 usec over multiple hops [5-7] • alternate fault tolerant paths • all Bit Error Rate [BER] conditions Latency is key if the network is part of the control loop: • Stability • Dynamic performance
- 19. 19 January 2016 Frameworkfor Simulation and Test Visualization View into simulated stimuli and responses Enhanced Simulation Instrumentation Test equipment to monitor signal points Traditional Test Vision SensorsNetwork Connections Vehicle Dynamics and Motion Control Road, Hazards and Weather Conditions Autopilot VUT Navigation Traffic – Vehicles, Pedestrians Vehicle Under Test
- 20. 20 January 2016 Simulationvs. Test Model • Fully simulated models in Matlab or similar tools • Target system, environment, test stimulus all simulated SIL • SW models replaced by executable code for the real target • HW, environment, test stimulus all simulated HIL • Selected components replaced with target HW and SW -- ECUs • Mixed of simulation and test Lab • Real code and HW • Simulated environment with mix of some real stimuli Field • Target system fully integrated • Controlled environment and stimuli – test track User • Human in the loop – road test • ADAS – human in VUT; Driverless – humans in other cars Simulation Live Testing
- 21. • Driver assistedand driverless cars are here today… • …requiring very complex navigation systems • Much more than just GNSS • INS, mapping, radars, vision systems, realtime networks • Simulation and Test must address interaction effects in complex control loops • Traffic and road conditions, objects, weather • Wireless network latency a key factor in the control system • Fault tolerance, route changes, re-transmission, multiple hops • Time Sensitive Networks Summary 21 January 2016
- 22. • Hiro Sasaki– Director, Architected Solutions • hsasaki@spectracom.com • Lisa Perdue – GNSS Systems • lperdue@spectracom.com • Gilles Boime – Senior Scientist • gboime@spectracom.com • Emmanuel Sicsik-Pare -- Strategic Product Mgr • Emmanuel.sicsik-pare@spectracom.orolia.com • John Fischer - CTO • jfischer@spectracom.com Acknowledgements 22 January 2016