1. Regional Traffic Monitoring System for Maryland’s Eastern Shore Dr. Gang-Len Chang Traffic Safety and Operations Lab University of Maryland, College Park Aug, 2012

2. Contents Project motivation & goals Eastern shore overview Traffic monitoring system Travel time prediction system Evacuation system Hurricane Irene Summary

3. Motivation (1) During the peak season, the Eastern shore is plagued with heavy congestion from tourists desiring to enter the Ocean City area. An accurate travel time prediction system is needed to provide motorists with information effecting route choice

4. Motivation (2) Maryland’s Eastern shore is prone to hurricane threats During hurricane season, the Eastern shore is crowded with tourists An evacuation plan is needed to safely and efficiently move people from the immediate impact area

5. Research Goals 1.To provide a safe and efficient evacuation plan based on empirical data 2.Provide accurate travel time information to mitigate traveler delay

6. Eastern Shore Region Counties: Cecil, Kent, Queen Anne’s, Talbot, Caroline, Dorchester, Wicomico, Somerset, Worcester Total population: 449,226 (2010 U.S Census Bureau) Major arterials: US 301, US 50, US 13, US 113, MD 662, MD 565, MD 16, MD 90

7. Eastern Shore Region Real-Time Traffic Monitoring System 43 microwave sensor stations are maintained and operated by UM Wireless communication between sensors and UM Data collection 30 seconds interval data by each lane (volume, speed, occupancy) UM provides data to MDSHA, DelDOT, and other agencies via RITIS

8. Sensor Stations

9. Eastern Shore Region Real-Time Traffic Monitoring System Provides real-time traffic conditions (speed and volume) UM Website (http://oceancity.umd.edu)http://oceancity.umd.edu CHART (http://chart.state.md.us)http://chart.state.md.us Interactive speed map of eastern shore region with locations of sensor Provides historical sensor data

10. Website Display Website (http://oceancity.umd.edu)http://oceancity.umd.edu Travel Time Prediction US 50 MD 90 Sensor Locations Current Sensor Data Historical Sensor Data Historical Predicted Travel Time

11. Interactive mapping Current Detector Data Historical traffic data, travel time, OC traffic, evacuations

12. Website Display (Cont’d) (a) Real time predicted travel time(b) Current detector data (c) Current speed map(d) Current volume map

13. Website Display (Cont’d) (e) Historical detector data(f) Historical travel times

14. Ocean City Ocean City, MD A famous tourist destination in Maryland’s Eastern Shore Population Summer peak season: 150,000 – 300,000 people Off-peak: 7,000 – 25,000 Serious congestion on the major eastbound entry road (US 50 and MD 90)

15. Ocean City Travel Time Prediction System Two routes from Hall Road to Ocean City (MD90, US50) Travel time may vary from 15 minutes to 90 min 23 detectors for travel time predictions Including 18 HD traffic sensors

16. Travel Time System Operation Flowchart Prediction travel time every minute Detection of incidents Handling of missing data Database of Traffic Data t=t+1 Real-Time Detector Data at Time t Travel Time Estimation Module Missing Data Estimation Module Incident Detection Module Database of Historical Travel Times Travel Time Prediction Module Predicted Travel Time for Time t Data Missing? N Stop Predicting for Impacted Segments Links with Detected Incident Links with No Detected Incident Y N Links with Unreliable Missing Data Links with Reliable Missing Data Estimation Only

17. VMS Display ATIS (Advanced Travelers Information System) Travel time information for both routes Route guidance to travelers Traffic conditions toward to Ocean City

18. LPR System Two LPR trailers are deployed Hall Road and Inlet Isle Lane Data is collected for travel time estimation and for prediction module calibration

19. Travel Time Information System Provide real-time travel time information to drivers The system showed positive effects on drivers’ route choice behavior during congested condition Assist travelers in making proper route choice More efficient use of existing roadway capacity

20. Efficiency in Relieving Congestion and Increasing Throughput from VMS 6492 6037 Time-varying system throughputs to Ocean City (With VMS versus without VMS) Peak-season Saturday

21. Evacuation System Organizing an evacuation plan Identifying critical control points Develop traffic control parameters Improving efficiency Satellite image of hurricane Irene Aug 2011

22. Evacuation System (cont’d) Simulator tool for eastern shore region emergency evacuation Off-line simulator (old version) On-line simulator (new version) User friendly interface Output can be used to analyze evacuation plans by: DOTs (MD, DE, VA) Emergency management agencies Interstate 45 at Houston, Texas Evacuation from hurricane Katrina 2005

23. Evacuation system System Demonstration

24. System demonstration Total throughput for each target area

25. System demonstration Hourly volume for each target area

26. System demonstration Speed changes over time

27. System demonstration Identified Bottleneck

28. Ocean City Traffic Data Before and After Evacuation Evacuation for Hurricane Irene Aug 2011

29. Number of vehicles in ocean city 8/18/2011 – 9/13/2011 Evacuation 8/25/2011 14:00 ~ 8/26/2011 17:00

30. Number of Vehicles in Ocean City During Evacuation Evacuation 8/25/2011 14:00 ~ 8/26/2011 17:00

31. Number of Vehicles Changes in Ocean City During Evacuation MD 528US 50MD 90TOTAL Change DateINBOUNDOUTBOUNDINBOUNDOUTBOUNDINBOUNDOUTBOUNDINBOUNDOUTBOUND 08/25/2011 14:0095910631303131977484030363222-186 08/25/2011 15:00108211681503138684291234273466-39 08/25/2011 16:001094139413751661827131332964368-1072 08/25/2011 17:001166154012681547702126031364347-1211 08/25/2011 18:001094160712321590595130629214503-1582 08/25/2011 19:00906146910541389419125823794116-1737 08/25/2011 20:0076412288131305407117819843711-1727 08/25/2011 21:0058697964797848055317142510-796 08/25/2011 22:0035964743782429468010912151-1060 08/25/2011 23:002123862625231694796431388-745 08/26/2011 0:00532087632635285164819-654 08/26/2011 1:0031914310927144100344-244 08/26/2011 2:0015641869136446197-151 08/26/2011 3:0012501869149643215-172 08/26/2011 4:0012120221112322256453-397 08/26/2011 5:00322236717055404153797-644 08/26/2011 6:001283191902791545594721157-684 08/26/2011 7:002175152994442967328131691-878 08/26/2011 8:003206863565702868969632152-1189 08/26/2011 9:0028571440762220310108952346-1451 08/26/2011 10:003018283129661749567872750-1963 08/26/2011 11:0029487322983610010156222724-2102 08/26/2011 12:002105502387311057835532064-1511 08/26/2011 13:00167418241610445804531608-1155 08/26/2011 14:00146347236484304384121269-857 08/26/2011 15:0087258168428233622781048-770 08/26/2011 16:008116912233614330216835-619 08/26/2011 17:0047124422151020799546-447

32. Inbound/Outbound Traffic Volume from Ocean City 8/18/2011 – 9/13/2011 Evacuation 8/25/2011 14:00 ~ 8/26/2011 17:00

33. Inbound/Outbound Traffic Volume from Ocean City 8/25/2011 – 8/30/2011 Evacuation 8/25/2011 14:00 ~ 8/26/2011 17:00

34. Hourly Evacuation Route Usage 8/25/2011 – 8/26/2011 Evacuation 8/25/2011 14:00 ~ 8/26/2011 17:00 * Only outbound volume

35. Evacuation route usage

36. Eastern Shore Region Traffic Monitoring System - Summary Traffic Monitoring System Provides 43 detectors’ real-time traffic data Provides historical data Travel Time Prediction System Provides travel time to motorists Improves usage of existing roadway capacity Detects incidents Provides traffic condition ahead Evacuation System On-line and off-line simulation tool with advanced GUI Evaluating evacuation plans Identifying critical control points Estimating time needed for evacuation Improving efficiency of evacuation

37. Thank you Questions & Comments Dr. Gang-Len Chang gang@umd.edu Sung Yoon Park alza102@gmail.com