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Wireless Networks for v2v and v2i Communication

Wireless Networks for v2v and v2i Communication. CMU Kick-off meeting 01 March 2004. GM’s Global Telematics Vision. Connected Vehicles…Connected People

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Wireless Networks for v2v and v2i Communication

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  1. Wireless Networks for v2v and v2i Communication CMU Kick-off meeting 01 March 2004

  2. GM’s Global Telematics Vision Connected Vehicles…Connected People Connected vehicles save our customers time, keep them in control, safe, informed, and entertained. When our customers allow their connected vehicles to be part of a network, it makes everyone’s life better by generating information that benefits everyone. ECI Focus: Explore the feasibility, limitations and potentials of wireless networks to deliver real-time traffic information services to our customers and to demonstrate automotive safety applications for GM vehicles Jay Parikh ECI Lab

  3. GSM, CDMA, PCS, 2.5/3G Ubiquity Wi-Fi (802.11x) XM Satellite Traffic Probe Vehicle Network Topology Wireless Networks • Mobile Ad-hoc (Self-forming, multihop) Jay Parikh ECI Lab

  4. Incidence notification to OnStar • Information relay to other vehicles for dynamic route guidance Example Traffic Scenario • Immediate spread of knowledge to surrounding vehicles within ad-hoc network Exit Jay Parikh ECI Lab

  5. Objectives Safety: • Develop a cooperative collision warning strategy using V2V communication • Replace/enhance collision avoidance sensors for GM vehicles Telematics: • Enable advanced telematics services through network • Create OnStar to the power of N Jay Parikh ECI Lab

  6. Our Approach • Explore mobile ad hoc network concept using proprietary and standards based solutions • Develop and demonstrate active safety and possible telematics applications to assess feasibility and establish requirements • Conduct research to address network performance, scalability and capacity using analytical and simulation tools for real-world scenarios • Leverage expertise of our research partners and integrate the concept into GM vehicles Jay Parikh ECI Lab

  7. Mobile Ad Hoc Network Solutions • Proprietary Solution from Mesh Networks • 2.4 GHz unlicensed band • Off-the-shelf hardware • Proprietary routing and communication protocols • Ready for quick integration and concept validation • Standards - DSRC • 5.9 GHz licensed band • FCC approval granted in Dec. 03 • Communication protocols under development • No commercial H/W available yet • No plans for network routing protocols Jay Parikh ECI Lab

  8. Our Plan • By Fall ’04: • Develop and demonstrate Rear-End, Intersection, Lane Change/Merge countermeasures and collect real-time vehicle data using commercially available hardware • Conduct ad hoc network research to answer: • Network performance, RF power control, network scalability, etc. • Conduct network simulation research to answer: • RF propagation model, data channel capacity, effect of vehicle density, etc. • By Fall ’05: • Integrate research results into concept vehicles • Investigate possibility to enhance or replace DAS (Driver Assistance System) for production Jay Parikh ECI Lab

  9. SafetyApplications Safety Warnings Intersection Collision Avoidance (Infrastructure-Assisted) • Traffic Signal Violation Warning • Stop Sign Violation Warning • Left Turn Assistant • Stop Sign Movement Assistant • Intersection Collision Warning • Pedestrian Crossing Information at Intersection • Emergency Vehicle Signal Preemption Non-Intersection Collision Avoidance (Infrastructure-Assisted) • Curve Speed Warning – Rollover Warning • Low Bridge Warning • Low Parking Structure Warning • Work Zone Warning • Wrong Way Driver Warning • Road Condition Warning • Blind Merge Warning • Highway/Rail Collision Warning Normal Driving • Cooperative Adaptive Cruise Control • In-Vehicle Signage • In-Vehicle Amber Alert Safety Warnings Cooperative V-V Collison Avoidance • Emergency Electronic Brake Lights • Cooperative Forward Collision Warning • Blind Spot Warning • Lane Change Warning • Vehicle-to-Vehicle Road Condition Warning • Vehicle-to-Vehicle Road Feature Notification • Visibility Enhancer • Highway Merge Assistant • Cooperative Collision Warning • Approaching Emergency Vehicle Warning Collision Mitigation • Pre-Crash Sensing for Cooperative Collision Mitigation, e.g. enhanced air-bags & seat-belts, truck/car compatibility, brake assist Post Collision and Other Safety • Post-Crash Warning, e.g. ACN • SOS Services Jay Parikh ECI Lab

  10. Example Application Scenarios Jay Parikh ECI Lab

  11. Vehicle as Traffic Probe • Vehicles periodically report its speed and position to a data center for real-time traffic • Vehicles directly communicate with data center • Data center must be capable of managing communication channels and data from large number of vehicles • How can ad hoc network help? • Reduce communication requirements by aggregating and processing data from networked vehicles before reporting to data center • Reduce required data transfer • Reduce dependability on infrastructure • Quickly spread emergency information among networked vehicles Jay Parikh ECI Lab

  12. UC Berkeley / PATH • Demonstrate active safety applications - Fall ‘04 • Utilize 6 AHS vehicles (Buick) to demonstrate: • Rear-end crash warning • Intersection warning • Lane change/merge warning • Develop protocols and algorithms for cooperative situational awareness • Establish communication content and performance requirements • Develop and demonstrate warning / interface strategy • Collect, analyze, and visualize data • Implement using commercially available hardware solution from Mesh Networks Jay Parikh ECI Lab

  13. Carnegie Mellon University • Create and demonstrate ad hoc network based on evolving DSRC standard capable of supporting safety and telematics applications – Fall ‘04/05 • Define latency requirements for: • Network connection and packet transmission/retransmission • Determine network scalability and reliability • How many hops can ad hoc network reliably cover? • Optimize protocols for automotive environment • Routing protocols - proactive, reactive and hybrid • Targeting or controlling a flood fill • Adaptive power control for sparse/dense traffic • Develop algorithms to cooperate between Mobile IP, ad hoc network and infrastructure • Demonstrate real-time vehicle data collection using ad hoc network and communication with infrastructure Jay Parikh ECI Lab

  14. Hughes Research Laboratory • Develop and validate a cooperative 360° collision warning strategy through simulation - Dec ‘04 • Develop RF propagation model • Simulate communications protocols • Evaluate channel capacity • Simulate network throughput • Simulate dense and sparse traffic conditions • Simulate ranging schemes • Integrate with CORSIM traffic simulator for real-world traffic scenarios and validation • Evaluate possible impact on traffic flow and vehicle safety Jay Parikh ECI Lab

  15. Ad Hoc Network for Active Safety and Telematics R&D Approach: • Explore ad hoc network using commercial and standards based solutions • Develop and demonstrate active safety and telematics applications • Research to address network performance, capacity and scalability using analytical and simulation tools for real-world scenarios • Leverage expertise of our collaborative research partners and integrate the concept into GM vehicles UC Berkeley / PATH: • Demonstrate active safety applications – Fall ’04 • Forward collision warning • Intersection warning • Lane change/merge warning • Develop protocols and algorithms for situational awareness • Implement using commercially available solution Budget – 460k Resources – 1 Faculty, 2 Res. Eng., 1 Grad Student CMU: • Demonstrate based on DSRC – Fall ’04/05 • Develop a test-bed using 5.8GHz 802.11a for: • Real-time propagation model • RF channels management (control and data) • Determine network scalability, reliability, latency • Develop and optimize routing protocols • Develop algorithms to cooperate between ad hoc network & infrastructure for telematics applications Budget – CRL $$$ Resources – 2 Faculty, 1 post doc, 4 grad students HRL: • Develop and validate a cooperative 360° collision warning strategy via simulation – Dec. ’04 • Develop RF propagation model • Simulate communication protocols • Simulate different traffic conditions • Simulate network throughput • Evaluate impact on traffic flow and vehicle safety Budget – 275K Resources – ¾ FTE Jay Parikh ECI Lab

  16. dy1 v1 f dx1 Moving Vehicle Results • 1 stationary, 1 dynamic antenna, with obstruction • Receiving vehicle ~ 40 mph, no lost packets Jay Parikh ECI Lab

  17. Moving Vehicle Results • 2 vehicles ~ various speeds, same direction • Distances up to 150 m, no lost packets Jay Parikh ECI Lab

  18. Moving Vehicle Results • Various vehicle speeds, same direction, 150 m • Cut-in SUV, no lost packets Jay Parikh ECI Lab

  19. Moving Vehicle Results • Highway, light traffic, 60mph • Reception good, generally dependent on line of sight large truck blocking Jay Parikh ECI Lab

  20. Internal Project Plans for 2004 • Investigate V-V communications and GPS as a low-cost solution for remote sensing between vehicles • Development of a 360 degree collision warning strategy using V-V communications • Analyze, develop and demonstrate prototype vehicle safety applications using V-V communications Jay Parikh ECI Lab

  21. Issues and Challenges • Analysis of communication technologies and standards • Network protocols for V-V communication • Standardized data messages • Communication channel capacity and availability • Infrastructure integration • Range of coverage, intelligent power management • Interference, connection reliability • Connection Latency • Security, Privacy • (D)GPS/Map integration • Antenna, etc. Jay Parikh ECI Lab

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