WWS 527 a Transportation Policy and Planning

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Addressing the Real-time Aspects In Turn-by-turn Navigation PROBLEM: How to get from A to B • Many Paths • Each with a Different Value to the Decision Maker • Each Segment Changing with Uncertainty over Time 1 2 6 1 8 3 2 4 9 2 5 3 3 6 5 8 6 3 1 6 1 Week 8

Link Travel Times Historic, Actual & Forecast During Day One week-day on one link WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Things change! Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 The Measurement Problem • How to collect the real time Speed Data? – Incremental Infrastructure • In pavement loop detectors (single point) • radar/laser/video signpost systems (single point) • EZ Pass readers (2 point span measurement, Excellent) – Crowd. Sourced Data • Map data: NYT article • Wireless Location Technology (Cellular Probes, see Fontaine, et al) – Cell-tower trilateration » Yet to demonstrate sufficient accuracy – Cell-handoff processing » maybe OK for simple networks • Floating Car (Vehicle Probe) data processing (see Demers et al) Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Cell Probe Technology • Practical success requires more than cell phones • Cell phone movement based on cell location and “hand-offs” from one cell to another • Pattern recognition techniques filter out data from those not on the highway • Then traffic algorithms generate travel times and speeds on roadway links • Cell phones need to be turned on, but not necessarily in use • Full regional systems in place in Baltimore, Antwerp, and Tel Aviv = 4, 600 miles, Shanghai Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Cell Probe Technology Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Cell Probe Privacy Week 8

WWS 527 a – Transportation Policy and Planning Analysis Handset 49, part 1 Fall 2009/10 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Handset 49, part 2 Fall 2009/10 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Handset 49, part 3 Fall 2009/10 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Handset 49, part 4 Fall 2009/10 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Handset 49, part 5 Fall 2009/10 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Handset 49, part 6 Fall 2009/10 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Handset 49, full trip Fall 2009/10 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Path-Finding Drive Tests Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Baltimore MMTIS • At one point this was the first regional deployment of commercial-quality cellular traffic probes in North America Mutually profitable public-private partnership • – – – • Test commercial markets during project Integrate with existing public data – including transit and E-911 Encourage public applications beyond traditional ITS Contract signed September 2004; data flow to Maryland DOT began April 2005 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Baltimore MMTIS – Private Firms • Delcan-NET – Transportation and technology consultants – Fifty plus years in business – Profitable every year; staff = 500 plus • ITIS Holdings – Leader in traffic probes; staff = 100 – Commercial customers – 16 automobile firms, for-profit 511 – Profitable! – Publicly traded on London exchange • National cellular firms (Verizon and AT&T) Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 3/18/201811/9/2008 Week 8

MARYLAND DOT CAMERAS SHOW ACCURACY OF TRAFFIC WWS 527 a – Transportation Policy and Planning Analysis INFORMATION BEING CAPTURED USING CELL PROBES Fall 2009/10 I-695 at HARTFORD ROAD Monday, June 6 th 2005 9: 02: 18 am 3/18/201811/9/2008 Week 8

CELL PROBES ACCURATELY UPDATE WWS 527 a – Transportation Policy and Planning Analysis TRAFFIC CONDITIONS AS CHANGES OCCUR Fall 2009/10 I-695 at HARTFORD ROAD Monday, June 6 th 2005 9: 33: 06 am 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Produced by Dr Hillel Bar Gerd, Associate Professor, Ben Gurion Negev University, Israel 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Baltimore Comparison with RTMS Data Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Analysis Route Overview Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Performance data I-695 – July 2005 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Baltimore I-695 Weekday Patterns Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Baltimore I-695 Saturday Patterns Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Baltimore I-695 Route Travel Time Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 What about Travel Time Variability? • An excellent empirical study: Black, I, T. K. Chin “Forecasting Travel Time variability in Urban Areas”Rept # 0010 -GD 01017 TCF-02 Hyder Consulting (UK) Nov, 2007 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Vehicle Probes • INRIX a current leader • Google traffic; crowd. Sourcing • Assign Speed data to network segments of Digital Map database, or • Maintain travel times between strategically located virtual monuments Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Vehicle Probes • Assign Speed data to network segments of Digital Map database, or • Maintain travel times between strategically located virtual monuments Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 North American Monument Network • ~125, 000 North American “Monuments” • ~106 (mi, mj) • Can create Median travel Tims by Time-of-Day – For Example: AM Peak, Midday, PM Peak, Night, Weekend day (mi, mj) near Troy (mi, mj) larger area Week 8

Median Speed WWS 527 a – Transportation Policy and Planning Analysis (by direction) Fall 2009/10 on National Highway Network 2: 30 pm 11/16/09 > 40 mph < 40 mph 3/18/201811/9/2008 Week 8 height ~ speed 2: 30 pm 11/15/09

Average Speed WWS 527 a – Transportation Policy and Planning Analysis (by direction) Fall 2009/10 on National Highway Network 2: 30 pm 11/19/09 > 40 mph height ~ speed < 40 mph 2: 30 pm 11/15/09 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Real-Time Dynamic Minimum ETA Sat/Nav The late 90 s “Advance” project & Illinois Universities Transportation Research Consortium Conducted its version of the abandoned “ADVANCE” (Advanced Driver and Vehicle Advisory Navigation Conc. Ept )project • 250 Volunteers using Co. Pilot|Live commuting to/from RPI • Co. Pilot continuously shares real-time probe-based traffic data • Co. Pilot continuously seeks a minimum ETA route Won ITS America’s 2007 “Best Innovative Research” Award 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Project Objectives • Create: real-time data collection from vehicles and dissemination to vehicles of congestion avoidance information which is used to automatically reroute drivers onto the fastest paths to their destinations • Target locations: small to medium-sized urban areas • Aspects: operations, observability, controllability, users, information transfer to travelers 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Experiment Details 3 -month field test Capital District (Albany), NY, USA Journey-to-work 200 participants 80 Tech Park employees 120 HVCC staff & students “Techy” travelers Network: Freeways & signalized arterials Congested links Path choices exist 3/18/201811/9/2008 Week 8

Basic Operational Architecture WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Two-way cellular data communications between Customized Live|Server at ALK Customized Co. Pilot|Live In vehicles 6 1 3/18/201811/9/2008 2, 4 3 5 Week 8 7 8 Destinati on

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Every Second Co. Pilot|Live Determines “Where am I”, Then… If Momument, mj , is passed Send mi , mj , ttk(mi, mj )= t(mi) - t(mi) (52 bytes) Co. Pilot|Live Set i=j Updates: TT(mi, mj ) “Where Am I”, Then… 3/18/201811/9/2008 ALK Server Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Every “n” Minutes Co. Pilot|Live … Send… Current Location & Destination, Last update time (42 bytes) ALK Server … Determines Uk : set of TT(mi, mj ) within “bounding polygon” of (Location; Destination)k that have changed more than “y%” since last update. ALK Server … Send… New TT(mi, mj ) for every (i, j) in Uk Co. Pilot|Live Sends: “Where am I”, Dest. , Last update Receives/Posts: updates Computes: Min. ETA Updates route, if better 3/18/201811/9/2008 (280 bytes/100 arcs) Co. Pilot|Live … Updates TT(mi, mj ) in Uk , ETA on current route, Finds new Min. ETA route, if Min. ETA “substantially” better then… Adopt new route Week 8 ALK Server Builds: set Uk Sends: TT(mi, mj ) for every (i, j) in Uk

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 When Available ALK Server … Receives: Other congestion information from various source, blends them in TT(mi, mj ) ALK Server Updates: TT(mi, mj ) 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 What We Heard I'm very impressed with the Co. Pilot program thus far. The directions are accurate and it adapts quickly to route changes. I find it interesting how willing I am to listen to a machine tell me which route to take I like using it for when I have no idea on how to get somewhere, and it is good for my normal route because it keeps me out of traffic on route 4. This thing is awesome. I was a little skeptical at first but once i got the hang of it I don’t know how I went along without it. I think any student commuting to school will benefit from this. It is great, it took a while to trust it telling me where to go, but i like it because i cant get lost! Thanks. 3/18/201811/9/2008 Week 8

also Can Watch Vehicles WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 1 2 3/18/201811/9/2008 Week 8 3

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Forecasting Travel Times Using Exponential Smoothig 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Historical Expectation: Concepts • Patterns Differ over Days & Time of Day • Most Significant Difference is Between Weekdays and Weekends Zoo Interchange – Hale Interchange (All Days) 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Historical Expectation: Concepts • Two Peak Periods • Each appears to be Bell Shaped • Afternoon Peak Period Appears to have “Extra Hump” 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Historical Expectation: Solution 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Historical Expectation: Application Downtown – Zoo Interchange Minimize the SSE between Historical Estimation Function and actual data points 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Historical Expectation: Application 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Using Real-Time Information to Improve our Estimate 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Including Real-Time Information: Concepts Real-Time Information “Since a desirable route needs to be given when the driver asks for, it the computation of such a route but requires travel times which occur later, we need to be able to forecast such travel times. ” DEFINITION: A real-time travel time is a data point that can be received or constructed and measures the time it takes to traverse a specific route from one location to another location ending now. 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Including Real-Time Information: Concepts Peak Hour Characteristics & Return to Normalcy Burleigh - Zoo Moorland Downtown During Peak Hours, Traffic Patterns Remain at a relatively constant distance to Historical Estimate There will be a time at which traffic patterns will return to free flow conditions 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Including Real-Time Information: Concepts Exponential Smoothing • Method of “smoothing” a time series of observations • Most recent observations are given a high weight and previous observations are given lower weights that decrease exponentially with the age of the observation Single Double Triple 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Including Real-Time Information: Solution • During Peak Periods: • Adaptation of Double Exponential Smoothing • Trend is the Trend of the Historical Estimate • Observation weighted with Most Recent Estimate + Slope for Smoothed Estimate • Forecast done by adding trend to most recent estimate 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Including Real-Time Information: Solution • During Non-Peak Periods • Adaptation of Double Exponential Smoothing • Trend is decay to free flow Conditions 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Including Real-Time Information: Solution 3/18/201811/9/2008 Burleigh – 8 Zoo (June 14) Week

WWS 527 a – Transportation Policy and Planning Analysis Fall 2009/10 Including Real-Time Information: Application 3/18/201811/9/2008 Week 8

WWS 527 a – Transportation Policy and Planning Analysis Progression Through Sample Day: Fall 2009/10 Moorland – Downtown. June 14, 2002 THETA 0. 3000 Time Step PHE 0. 8000 CAI 0. 5000 0. 85 C 3/18/201811/9/2008 Week 8 0: 03: 00