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

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.

How this challenges a model Maximum Volume Most Congested Condition

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

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

How this challenges a model

How this challenges a model Demand Volume

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

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

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

Case Study 1 - Evacuation

Case Study 1 - Evacuation

Case Study 1 - Evacuation

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

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

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

Case Study 2: Project Evaluation I-83 Connection Users

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

Case Study 2: Project Evaluation PM congested speeds

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

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

Case Study 3: Project Evaluation Users of the roadway

Case Study 3: Project Evaluation I-95 Project Diversions

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

Scott Thompson-Graves Jonathan Avner Javner@wrallp.com Questions Scott Thompson-Graves sthompson-graves@wrallp.com Subrat Mahapatra smahapatra@sha.state.md.us Li Li lli@wrallp.com Mark Radovic mradovic@sha.state.md.us Jonathan Avner Javner@wrallp.com