Performance Management Research Data Set 21 st ITS World Congress - - PowerPoint PPT Presentation

Wisconsin Traffic Operations and Safety Laboratory

Crafting Measures from the National Performance Management Research Data Set

21st ITS World Congress September 11, 2014 Peter Rafferty & Chip Hankley Wisconsin TOPS Lab

Overview

• Introductions and Background Motivation
• Data Purposes and Objectives
• Traffic Probe Data and the NPMRDS
• Accessing and Utilizing the Data
• Visualizing TMCs in GIS
• Questions

Non-Intrusive Traffic Detection

• Wire loop
• bsolescence
• Classes of non-intrusive detection
• Traffic probes and traffic data providers
• Wireless detectors
• Advantages: maintenance, portability,

accuracy, cost, reliability

Traffic Probes - Overview

• Probes by
• Automatic vehicle location (AVL)
• Cellular signal processing
• GPS enabled mobile apps
• Aggregated and provided (sold)

by third parties

• E.g., Google,

TomTom, Inrix, Nokia

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 4 6 8 10 12 14 16 Cumulative Probaility Segment Travel Time (minutes) 7:00 7:15 7:30 7:45 8:00 8:15 8:30

7:00 7:15 7:30 7:45 8:00 8:15 8:30

Multistate Operations

Interactive Map Online at www.glrtoc.org/map/npmrds/pti2013

Incident and Event Performance

• Example shown on next two slides:
• North/West Passage Coalition
• I-94 in North Dakota and Minnesota
• February 9-11, 2013 Winter Weather
• Hundreds of miles of interstate closed 12-18 hours

Question – How best to handle this in analysis…

Multistate Operations

West < I-94 Link Location > East 2/1/13 < Date & Hour > 2/20/13

Observations Present in NPMRDS

ND

• MN

West < I-94 Link Location > East 2/1/13 < Date & Hour > 2/20/13

Average Speed from NPMRDS

ND

• MN

Business Applications

• Mobility Performance Measures
• Vehicle Delay and User Cost
• Travel Time Reliability

Business Applications

• Planning Processes
• Operational Needs Assessment
• Reliability Valuation

National Performance Management Research Data Set (NPMRDS)

• Covers complete National Highway System
• By short segments, “Traffic Message Channel”

(TMC)

• 5-minute bins
• Made available to states as of October 2013
• Minimally processed
• Clean file structure

and data integrity

NPMRDS Coverage

• 261 thousand TMCs
• 1.8 million GIS features
• Several billion travel time observations

(potentially 20+ billion per year)

• Passenger
• Freight
• Combined

Performance Measure Process Overview

Accessing NPMRDS

• Suggest FTP
• File Structure
• 2012q3, 2013q2, etc.
• americas

– additional_content_americas

» … static files, archive, monthly updates,

shapefile (2013q2)

• documentation_tools

– documentation

» … technical references, availability dates,

points of interest (poi), etc.

transportal.cee.wisc.edu/products/fhwa-here/

Utilizing NPMRDS

• Hardware, software, and skill set requirements
• Don’t try to open CSVs in Excel
• Access has 2 GB per table limit, also quickly exceeded
• Requires database and scripting resources
• If mapping, requires GIS expertise

Handling Outliers

Hourly Volume Travel Time Sigma (per TMC)

It’s NOT like this …rather an undifferentiated cloud Nice distribution, but with long tails

Missing Observations

• Assumptions
• Imputation vs

parameterization

Wyoming Interstates

Missing Observations

Question – What’s an efficient way to handle this?

65 mph Posted Speed 3-hr grids 36 epochs

Freight vs Passenger

• Freight and Passenger travel times provided

separately

• Fewer freight observations (but increasing…)
• See www.glrtoc.org/map/npmrds/pti2013
• St. Louis (city and county),

July-December 2013 Average Observations per TMC

Freight vs Passenger

• Freight speeds are systematically lower
• St. Louis (city and county), July-

December 2013, Interstates and US Highways, paired observations

Comparisons to Other Data

• mean error
• mean absolute error
• mean square error
• mean absolute

percentage error

• mean square

percentage error

• root mean square error
• root mean square

percentage error

• Theil inequality
• Thiel bias
• Thiel variance
• Thiel covariance
• PTI delta %
• Obs delta %
• Etc…
• Etc…

Integration w ith GIS

• Performance data is based on Traffic Message

Channel (TMC) segments.

• TMCs are

associated with roads by name

• r route ID –

lots of overlap

Visualizing TMCs in GIS

• Raw data coded by “LINK”
• Lookup table provides ability to map LINK to TMC
• Many to many relationship

LINK TMC A 120N06503 C 120N06503 E 120N06503 B 118N14321 C 118N14321 D 118N14321

Displaying Road Direction

• Want to show different directions at all scales (no overlap)
• The lookup table has a field called DIR (so does the shapefile –

DIR_TRAVEL, but that’s different!)

• Values are T or F
• (could be B, but only found one instance of this in the entire data set)
• Indicates Direction of Travel along the link with respect to the reference

node (the SOUTHERN end of the link, or WESTERN end if it’s an E-W line)

• T = Direction of travel TOWARDS reference node
• F = Direction of travel FROM reference node

Towards Reference Node From Reference Node

Sometimes the geometry of roadways are shown offset (e.g. divided interstate highways), other times geometry will be coincident (e.g. non-divided US highway)

Displaying Road Direction

• Offset the line to the RIGHT or LEFT depending on the DIR value
• FROM -> RIGHT
• TO -> LEFT

If you are trying to symbolize with a performance measure, you may need to add TWO layers, one for the FROM and one for the TWO Arrows indicate geometric direction of

• line. Reference node is

always the S or W end

• f the line. This

example has two sets

• f coincident lines

representing different traffic directions Allows you to see BOTH lines at all scales Symbolize linework by offseting FROM lines RIGHT and TO lines LEFT

Traffic Direction: BLUE – CW UPPER, CCW LOWER GREEN – CCW UPPER CW LOWER

Getting to the Spatial View …

• Single spatial dataset provided with NPMRDS
• NHS_NPMRDS_Shape_file_HERE_QX_YYYY
• All major US highways
• Made up of

“links” (road segments)

• LINK – TMC

lookup table provided as DBF

1,792,650 features

Getting to the Spatial View …

• Import DBF into SQL Server (using import wizard in

SSMS)

• Import shapefile into SQL Server
• Shape2SQL tool from www.sharpgis.net
• Create an empty SDE feature class and append
• If you use SDE, leave the feature class unversioned
• Build your query logic with SSMS

Working w ith Spatial View s

• Great for exploring datasets when you need a

more powerful query environment

• Performance isn’t great – probably want to

export the query to a stand alone dataset for better performance in a production environment (e.g. web map)

• May be a reflection of SQL Server expertise
• Next up is trying this in PostgreSQL/PostGIS

Online Examples

• Wisconsin DOT Mobility

Performance Measures

• http://www.dot.wi.gov/about/

performance/goalmobility.htm

• Mid-America Operations
• http://www.glrtoc.org/map/

mafc_region/

• National NPMRDS

Reliability Map

• http://www.glrtoc.org/map/

npmrds/pti2013/

I-94 Betw een Milw aukee and IL State Line

Each Day of 2013 Southbound Northbound

IL Line IL Line Marquette Marquette Mitchell Mitchell WIS 50 WIS 50 Racine Racine

Wisconsin Traffic Operations and Safety Laboratory

Thank You

Peter Rafferty 608-890-1218 or prafferty@ wisc.edu Chip Hankley 608-890-2441 or hankley@ wisc.edu