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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. Contents. Project motivation & goals Eastern shore overview Traffic monitoring system Travel time prediction system
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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
Contents • Project motivation & goals • Eastern shore overview • Traffic monitoring system • Travel time prediction system • Evacuation system • Hurricane Irene • Summary
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
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
Research Goals • To provide a safe and efficient evacuation plan based on empirical data • Provide accurate travel time information to mitigate traveler delay
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
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
Eastern Shore Region Real-Time Traffic Monitoring System • Provides real-time traffic conditions (speed and volume) • UM Website (http://oceancity.umd.edu) • CHART (http://chart.state.md.us) • Interactive speed map of eastern shore region with locations of sensor • Provides historical sensor data
Website Display • Website (http://oceancity.umd.edu) • Travel Time Prediction • US 50 • MD 90 • Sensor Locations • Current Sensor Data • Historical Sensor Data • Historical Predicted Travel Time
Interactive mapping Historical traffic data, travel time, OC traffic, evacuations Current Detector Data
Website Display (Cont’d) (a) Real time predicted travel time (b) Current detector data (c) Current speed map (d) Current volume map
Website Display (Cont’d) (e) Historical detector data (f) Historical travel times
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)
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
Travel Time System Operation Flowchart • Prediction travel time every minute • Detection of incidents • Handling of missing data Real-Time Detector Data at Time t Database of Traffic Data Incident Detection Module Travel Time Estimation Module Links with Detected Incident Links with No Detected Incident Database of Historical Travel Times Data Missing? N Y Missing Data Estimation Module Stop Predicting for Impacted Segments Links with Unreliable Missing Data Links with Reliable Missing Data Estimation Only N Travel Time Prediction Module t=t+1 Predicted Travel Time for Time t
VMS Display • ATIS (Advanced Travelers Information System) • Travel time information for both routes • Route guidance to travelers • Traffic conditions toward to Ocean City
LPR System • Two LPR trailers are deployed • Hall Road and Inlet Isle Lane • Data is collected for travel time estimationand for prediction module calibration
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
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
Evacuation System • Organizing an evacuation plan • Identifying critical control points • Develop traffic control parameters • Improving efficiency Satellite image of hurricane Irene Aug 2011
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
Evacuation system System Demonstration
System demonstration • Total throughput for each target area
System demonstration Hourly volume for each target area
System demonstration Speed changes over time
System demonstration Identified Bottleneck
Ocean City Traffic Data Before and After Evacuation Evacuation for Hurricane Irene Aug 2011
Number of vehicles in ocean city8/18/2011 – 9/13/2011 Evacuation 8/25/2011 14:00 ~ 8/26/2011 17:00
Number of Vehicles in Ocean City During Evacuation Evacuation 8/25/2011 14:00 ~ 8/26/2011 17:00
Inbound/Outbound Traffic Volume from Ocean City8/18/2011 – 9/13/2011 Evacuation 8/25/2011 14:00 ~ 8/26/2011 17:00
Inbound/Outbound Traffic Volume from Ocean City8/25/2011 – 8/30/2011 Evacuation 8/25/2011 14:00 ~ 8/26/2011 17:00
Hourly Evacuation Route Usage 8/25/2011 – 8/26/2011 Evacuation 8/25/2011 14:00 ~ 8/26/2011 17:00 * Only outbound volume
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
Thank you Questions & Comments Dr. Gang-Len Chang gang@umd.edu Sung Yoon Park alza102@gmail.com