1. Development of New Supply Models in Maryland Using Big Data
Jonathan Avner, Scott Thompson-Graves and Ashley Tracy (WRA)
Subrat Mahaptra, Mark Radovic (MDOT SHA)
15th TRB National Transportation Planning Applications Conference
Raleigh, NC
May 15, 2017

2. Agenda
Challenge
Project
Options Evaluated
Approach
Findings

3. Challenge
MDOT SHA is working on several fronts to improve the capabilities of its tools for addressing both traditional and non-traditional applications
Trip Based Model
Activity Based Model
DTA Lite
Agent Based Freight Model
By having a suite of tools available, able to align the tool with the type of question being asked including
Resolution or detail of the analysis
Runtime
Desired performance measures

4. Challenge
Ability to develop accurate forecasts in highly congested areas
The way the traditional volume delay functions treat congested condition is less than ideal
Challenge in ability to model peak hour conditions that make sense

5. Project Can volume delay functions be developed: Requirements:
Improve sensitivity in the model
Preform better under high volume conditions providing more realistic speeds
Provide better performance measures including delay and level of service that would more closely replicate observed system conditions
Requirements:
Be developed using data available from the Statewide Model, Centerline and Route datasets and count program which includes speeds at select locations

6. Project
Create a methodology to clean data for use in development of free flow speeds and volume delay functions
Use of the data to identify variations in behavior that warrant unique facility types in the model platforms
Use of the detailed centerline attribute data to capture these behavioral differences in improved speed and capacity

7. Approach Data Collection MSTM Statewide Model Network
Model Facility Type
Model Number of Lanes
Free Flow Speed and Hourly Per Lane Capacity
Centerline Data
Urban / Rural Designation
Roadway Functional Class
Number of Lanes
ATR Data
15 minute counts by speed bin

8. Approach Leverage MDOT SHA’s own Big Data – ATR Data
Observed travel speed by direction including volumes at 53 locations across the state
Data provided by 15 minute interval for the month of September, 2015
Stations distributed by statewide model facility type:
Freeways = 21
Expressways = 2
Arterials = 30
Stations distributed by urban / rural:
Urban = 18
Rural = 29

9. Approach

10. Approach

11. Approach

12. Approach Data Cleaning Data Preparation Validate Speed, Capacity Logic
Aggregate of 15 minute data to hour by station by direction for each day
Identify data that was inconsistent
Stations that included support facilities
Inconsistent data
Data Preparation
Calculation of weighted hourly volume and observed speed
Assignment of Free Flow Speed
Assignment of Capacity
Validate Speed, Capacity Logic
Validate Volume Delay Functions

13. Approach Validate Speed Validate Capacity Volume Delay Functions
Comparison of observed speed under low volume (uninterrupted) conditions to input speeds used in MSTM
Validate Capacity
Comparison of observed volume under high volume (interrupted) conditions to hourly capacity used in MSTM
Volume Delay Functions
Comparison of observed speed relationship using observed volumes to model delay functions

14. Data Preparation – Observed Volume and Speed
For each hour
Estimate of Flow (Veh/Hr/Ln)
Estimate of Speed
Data
Volume by 5 mph Speed Bin

15. Data Preparation - Capacity
For purposes of calculation volume to capacity ratio, assignment of capacity by station
Relied upon MSTM Capacity by SWFT (Functional Class) and Area Type
Future enhancement is to calculate capacity in MSTM using geometric data
Compared observed flow to MSTM capacity
SWFT
Urban
Suburban
Rural
Halo
External
Interstate 1
2350
2450
2400
Freeway 2
2200
2300
2250
Expressway 3
2150
Major Arterial 4
860
780
1300
Minor Arterial 5
750
650
1400
1350
Collector 6
700
Med Ramp 8
1100
1150
1200
1250
High Ramp 9
1700
1750
1800
Connector 11
9999

16. Data Preparation – Free Flow Speed
Considered several approaches
Posted Speed
Model Free Flow Speed
Observed Max Speed by Station

17. Observed Speed - Freeway
MSTM assumes:
Posted Speed + 7
Posted
Min
Max
55 (62) 64 71
60 (67) 60 69
65 (72) 73

18. Observed Speed - Expressway
MSTM assumes:
Posted Speed + 7
Posted
Min
Max
55 (62) 65 70

19. Observed Speed - Arterial
Posted
Min
Max
30 (35) 45 46
35 (40) 42 44
40 (45) 49 53
45 (50) 59
50 (55) 61
55 (60) 68

20. Validation – Volume Delay Functions
Plot of Speed vs. V/C
Speed: because grouping of locations, normalized to percent of free flow (PFFSPD)
Free Flow Speed based on observed speed by station
Capacity: MSTM capacity
Testing goodness of fit using %RMSE
Observed vs Model VDF
Consider urban vs rural sections
Testing typical values of VDF for goodness of fit

21. Validation – Volume Delay Functions
Reviewed data to ensure meet expected relationships
Speed drop due to traffic delay
Identified conditions of lower speed during low volume conditions

22. Validation – Volume Delay Functions
Observation of decreasing speed under low V/C
Silver Springs, MD on the Beltway

23. Validation – Volume Delay Functions
Goodness of fit urban vs rural
Locations of decreasing flow removed from curve testing

24. Diminishing Flow Conditions (Freeway)

25. Validation – Volume Delay Functions
Isolation of point observations where speed is decreasing consistently with volume (before reaching capacity)

26. Validation – Volume Delay Functions
Observed variation in response to V/C ratio
Consistent area type
Need to investigate location and roadway geometrics
Classify model links to capture variation

27. Validation – Volume Delay Functions
Arterial includes SWFT 4-6 (Arterial – Collector)
Urban Suburban: issue with capacities and speeds
Rural: several patterns

28. Validation – Volume Delay Functions
Urban / Suburban
MSTM capacities are low as observed conditions exceed capacity
Rural
Additional factors influencing volume delay

29. Validation – Volume Delay Functions
Consistency with volume delay functions except at low volume conditions – variability of speed under uninterrupted conditions

30. Validation – Volume Delay Functions
Overall
Urban
Rural
Freeway – All Points
10.708
11.575
7.0618
Freeway – Pre Jam Density
7.0705
7.1023
6.9676
Expressway
9.5834
Arterial – All
Major Arterial
Minor Arterial
Collector

31. Next Steps Free flow speeds Capacity
Calibrate to low volume conditions
Capacity
Localized capacities
SWFT
ATYPE2
PSPD
MIN
MAX 4 2
55 (60) 53 58 3
45 (50) 52 59
50 (55) 49 56 68 5
40 (45) 57
35 (40) 42 44 45 47 51 60 62 6
30 (35) 46

32. Next Steps Volume Delay Functions Diminishing Flow Conditions
Improved goodness of fit with refinement by functional class, area type and other geometric factors
Diminishing Flow Conditions
2 phase volume delay function
Planning for autonomous vehicles

33. Jonathan Avner javner@wrallp.com Scott Thompson-Graves
Questions
Jonathan Avner
Subrat Mahapatra
Scott Thompson-Graves
Ashley Tracy