1. Application of a Macro Based Capacity Constraint Assignment Technique
Scott Thompson-Graves, Li Li, Jonathan Avner (WRA)
Subrat Mahaptra, Mark Radovic (MDOT SHA)
15th TRB National Transportation Planning Applications Conference
Raleigh, NC
May 15, 2017

2. Challenge
Congestion is increasing with demand more frequently exceeding capacity
Investments are becoming more focused on improvements that may reduce the duration of congestion rather than eliminating congestion
Planners and decision-makers are asking for more information from models, including applications and results requiring hourly assignments.

3. How this challenges a model
Maximum Volume
Most Congested Condition

4. Congested Condition Speed Flow Relationship
Capacity Reduces when volume exceeds capacity
When the reduced capacity is exceeded volume spills over into the next hour
Increased delay in the current hour
Impacts delay in the subsequent hours

5. How this challenges a model
Need a refined approach that accounts for conditions when demand exceeds capacity
Reduce capacity based upon congestion
Impact subsequent hours for route choice and delay

6. How this challenges a model

7. How this challenges a model
Demand Volume

8. Approach to Capacity Constraint
Use speed flow relationship to determine reduced capacity during congested hours
Calculate V/C ratio
If volume exceeds capacity
Estimate revised capacity and determine excess demand
Adjust congested speed
Apply excess trips to subsequent hours

9. Approach to Capacity Constraint
Two options explored
Strict Capacity Constraint – move over-capacity trips to the subsequent hour
Soft Capacity Constraint – allow congested trips to complete their journey but include the residual trips from current hour to impact travel time in the subsequent hours

10. Case 1 - Evacuation Frederick, MD Evacuation Scenario
Evacuate Frederick Maryland during the AM Peak

11. Case Study 1 - Evacuation

12. Case Study 1 - Evacuation

13. Case Study 1 - Evacuation

14. Case Study 1 - Evacuation
Indicate Evacuation Duration and total hours of spillover time
Evacuation Duration lasted 5 hours
Vehicle Hours of Spill-over:
313,475

15. Case Study 2: Adding Capacity
Project Evaluation Model (PEM)
Determines who would use a proposed facility
Determines what facility they would use without the propose facility
Calculates network impacts of proposed facility on users
Calculates network impacts of entire network
Can be used to evaluate reducing capacity

16. Case Study 2: Project Evaluation
Construct an new connection from I-83 South to I-83 North in Baltimore, MD

17. Case Study 2: Project Evaluation
I-83 Connection Users

18. Case Study 2: Project Evaluation
I-83 Users with and without connection

19. Case Study 2: Project Evaluation
PM congested speeds

20. Case Study 2: Project Evaluation
Project Evaluation of I-83

21. Case Study 3: Project Evaluation
Closing 2 lanes on I-95 Southbound between MD 100 and MD 175

22. Case Study 3: Project Evaluation
Users of the roadway

23. Case Study 3: Project Evaluation
I-95 Project Diversions

24. Case Study 3: Project Evaluation
Project Evaluation of I-95 Lane Closure

25. Scott Thompson-Graves Jonathan Avner Javner@wrallp.com
Questions
Scott Thompson-Graves
Subrat Mahapatra
Li Li
Mark Radovic
Jonathan Avner