1. ActionWebs Hamsa Balakrishnan, David Culler, Edward A. Lee, S. Shankar Sastry, Claire Tomlin (PI) University of California at Berkeley July 23 2010

2. Goals of today’s meeting 1.Present and discuss research results and plans 2.Discuss how to better work together 3.Discuss results and ideas for education and outreach 4.Discuss budget 5.Prepare for CPS PI meeting (August 10-12, DC)

3. Schedule 9-9.45: Claire Tomlin, ActionWebs Overview 10-10.45:Shankar Sastry, Closing the loop around sensor networks 11-11.45:Hamsa Balakrishnan: CPS and Air Transportation 12-12.30: Lunch 12.30-1.15: Edward Lee: Hybrid and embedded systems 1.30-2.15:David Culler: CPS and buildings 2.30-2.50:Kristen Gates: CPS Education 3.00-4.20:Students and Postdocs (Eleftherios Matsikoudis, Wei Zhang, Anil Aswani) 4.20-5:Discussion and next steps

4. Energy efficient air transportation systems In 2007, domestic air traffic delays cost the US economy $41 billion 24% of arrivals at least 15 min late (avg. delay: 46 min) ~20% of total domestic flight time was delay 1,565 flights delayed on the ground (not at gate) for over 3 hours

5. Energy efficient, high productivity buildings 40% total energy consumption, 72% electricity usage Isolated subsystems, not much modeling Better operations needed

6. ActionWebs Observe and infer with a viewpoint to planning and modifying action: 1.Dealing with uncertainty 2.Tasking sensors 3.Programming the ensemble 4.Multiple objectives 5.Embedding humans

7. Research projects Optimization of Traffic Flow in the National Airspace System (Wei Zhang, Maryam Kamgarpour) System Identification combining physics-based models and data (Anil Aswani, Jeremy Gillula) Localization in buildings (Michael Vitus, Wei Zhang) Game-theoretic routing of GPS-Assisted Vehicles for Energy Efficiency (Anil Aswani) Estimation and control of discrete time stochastic hybrid systems (Jerry Ding, Alessandro Abate) Designing automation that works well with humans (Haomiao Huang)

8. Goals of today’s meeting 1.Present and discuss research results and plans 2.Discuss how to better work together –ActionWebs Seminar: Tuesdays 4-5pm? 3.Discuss results and ideas for education and outreach –CPS Education Workshop (August 12, DC) http://cyberphysicalsystems.org/cpsew –Intro textbook for undergrad class http://LeeSeshia.org –Robotics, undergrads, and high school students 4.Discuss budget 5.Prepare for CPS PI meeting (August 10-12, DC)

9. Environmental impacts of air transportation Aviation is responsible for 3% of total global carbon emissions –Aircraft contribute about 12% of CO 2 emissions from the transportation sector –According to the European Union, international aviation is one the largest growing contributors to CO 2 emissions, having increased 87% between 1990 and 2004 The aviation sector was responsible for 187.5 million metric tons of CO 2 emissions in the US in 2007 (about 3% of total emissions) [Commission of the European Communities, 2006; EPA 2007] [Balakrishnan]

10. Surface emissions from taxiing aircraft In 2007, aircraft in the US spent over 63 million minutes taxiing in to their gates, and over 150 million minutes taxiing out to their runways –An estimated 6 million tons of CO 2, 45,000 tons of CO, 8,000 tons of NOx and 4,000 tons of hydrocarbons are emitted annually by aircraft taxiing out for departure These flights burn fuel and contribute to emissions at low altitudes, and adversely impact local air quality Taxi-out emissions correspond to about 5% of the fuel burn and emissions from aircraft operations How do we optimize surface traffic movement to reduce aircraft emissions from taxi processes? [FAA ASPM database; Balakrishnan et al. 2008]

11. Aircraft taxi trajectories from surface surveillance data

12. Effect of stopping and starting while taxiing Potential fuel burn impact from stopping on the surface No significant impact

13. Estimate impact of different taxi profiles ICAO emissions databank assumes that aircraft taxi at a constant throttle setting of 7% Using CFDR data (from Swiss Air) corresponding to taxi profiles of various aircraft, we –Developed a regression model for fuel burn, that considers the baseline fuel burn and the impact of stop-start events Stop-start impact: Estimate of the form “The extra fuel burn from a start-stop event is equivalent to x additional minutes of taxi time” –Developed a (linear) regression model between fuel burn and throttle settings –Conducted above analysis for 9 aircraft types Fuel burn = Baseline fuel burn rate  (taxi time) + (Stop-start impact)  (# of stop-start events)

14. Minimizing fuel burn impacts of aircraft trajectories Multi-objective control of taxi trajectories Identification of hybrid system model of taxi trajectory Surface surveillance Flight data recorder Identification of fuel burn model Surface surveillance Flight data recorder (archival data) (real-time data)

15. Analyzing Benefits of Continuous Descent Approach (CDA) Analysis Approach Take current aircraft arrival trajectories Move the constant altitude (Level) section to a high altitude Objective: Study fuel benefits of implementing CDA in the current airspace structure [Kamgarpour]

16. Results on Airport Savings Airport Average (kg) Maximum (kg) TypeAnnual Savings $$ ATL33317B7631.18E+07 DFW38721MD117.75E+06 SFO881623B7441.39E+07 LAX20507B7411.92E+06 JFK40479B7447.57E+06 Scope of the Study 5 days of data for ATL, SFO, LAX airports 4 days of data for DFW, 1 day of data for JFK

17. Energy efficient Buildings 17[Culler]

18. 10-8-2008 Structural: Soda Electrical 12 KV dist. 2x Substation 1200 A 277/480 3 phase 2500 A 120/208 3 phase 2x Chiller MCM1 HP1A 400 HP1A 400 HP2A 600 HP3A 400 HP4A 400 HP5A 400 HP6A 100 HP7A 400 MCM2 Lighting Pumps Fans LP2E 225 LP2D 225 LP2C 225 LP1A 400 LP2A 800 HP3A 400 HP4A 400 HP5A 400 HP6A 100 HP7A 400 LP1B 400 LP2B 225 LP2G 225 LP2F 225 LP2E 225 LP2D 225 LP2C 225 LP3B 225 LP2E 225 LP2D 225 LP2C 225 LP4B 225 LP2E 225 LP2C 225 LP5B 225 LP2D 225 LP2C 225 LP2B 225 LP2D 225 LP2C 225 LP2B 225 LP2K 225 LP2J 225 LP2I 225 LP2H 225 LP2G 225 LP2F 225 LP2K 225 LP2J 225 LP2I 225 LP2H 225 LP2G 225 LP2F 225 LP2J 225 LP2I 225 LP2H 225 LP2G 225 LP2F 225 ~42 circuits each Machine rooms Classrooms Offices

19. Testbeds 1.Future air transportation systems testbed Connections with NASA Ames (SDO, separation assurance), NASA Langley (safety) Simulators (FACET, ACES), actual flight data (CFDR) 2.Mobile sensor net testbed 3.Buildings Berkeley campus: Soda, Cory, Sutardja Dai, California Halls LBL (DOE2)

20. Education and Outreach Cyber-physical systems science (CPSS) Curriculum development at Berkeley/MIT Outreach –Robotics at the RFS –Curriculum development at SJSU –SUPERB-CSS –Research Experience for Teachers (RET) [Gates]