1. 1 Congestion Measurement Mark Hallenbeck TRAC

2. 2 Historical Use of volume data –AADT –AWDT, –Hourly volumes To estimate delays Can produce a reasonable value of average delay, based on v/c relationship

3. 3 Historical Limitations: –Doesn’t account well for operational plans Only applies to computation of “c” –Doesn’t account well for variation in day-to- day congestion Incidents Number, size, and duration of special events Weather

4. 4 Solution (?) Measure performance directly and continuously –Volume –Speeds / delays / travel times

5. 5 Problems with the Solution Cost of data collection Need to determine what we really want to report, and how to report it

6. 6 Initial WSDOT Steps Use existing roadway management (control) systems to provide the needed data –An archive already existed –Cost of data collection born by the control system –Generally exists where problems (congestion) are the greatest

7. 7 Initial WSDOT Steps For existing, instrumented freeway systems: –Volumes –Average speeds –Frequency of congestion –Travel time and reliability (10 routes) –Geographic extent of congestion –Geographic extent of frequent congestion

10. Time PMAM 02468101224681012 Time PMAM 02468101224681012 405 5 Montlake Blvd. 520 Arboretum 92nd Ave. B’vue. Way 148th Ave. NE 60th St. 84th Ave. Lk. Wash. Uncongested, near speed limit Restricted movement but near speed limit More heavily congested, 45 - 55 mph Extremely congested, unstable flow Westbound SR 520 Traffic Profile General Purpose Lanes 1997 Weekday Average Eastbound

14. 14 What We Are Doing Now Using surveillance data –Measuring and reporting trends –Investigating recurring versus non-recurring congestion Gives a better understanding of –What is causing our problems, and –The relative importance of each of those causes

15. 15 Trends and Operational Analysis

16. 16 Recurring ConditionNon-Recurring Congestion Oct 24, 2002 I-90 WB Time of Day Direction of Travel Incident

17. 17 Recurring Congestion I-90 EB Non-Recurring Congestion Oct 31, 2002 Time of Day Direction of Travel Incidents

18. 18 Where Are We Going? Better analysis of the data we have (data integration) in order to learn more about cause / effect Lower cost surveillance (multi-use) Different types of surveillance Different ways of looking at the surveillance data we have

19. 19 Goal To provide better information at more geographic locations, without breaking the data collection budget

20. 20 Use Existing Data Differently Use management systems as surveillance –Ramp metering systems –Traffic signal systems –CVISN truck tags –Toll tags Get more out of what already exists

21. 21 More Where Are We Going Measure what travelers experience So that we can improve that experience