A Preliminary Study: Applications of Smart Phone Truck Data

to Develop Freight Performance Measures and Support Transportation Planning

Katherine E. Bell, P.E.Dr. Miguel A. Figliozzi

2012 Annual Western District ITE MeetingSanta Barbara, CA

Tuesday, June 26th, 2012

1

Outline

• Project Background

• Literature Review

• Data Description & Preliminary Analysis

• Ancillary Applications & Future Research

2

• No diesel fuel tax on heavy trucks in Oregon

• Weight-mile tax: trucks over 26,000 lbs

• Axle-based weight-mile tax: trucks over 80,000 lbs

• Mileage currently self-reported

• Oregon Trucking Online (25% in 2009)

• Audits using weigh station records

Project Background

3

Oregon Commercial Truck Weight-Mile Tax

• Simplify weight-mile tax collection

• Smartphone application that tracks satellite GPS data

• Automated taxing process; view mileage online

• Reduces administrative burden

• Reduces reporting errors and tax avoidance

• February 2010 – ODOT TRUE Pilot Project

• 3 Motor Carriers, 15 trucks

• Locations recorded every 5 minutes for over 1 year

Project Background

4

Truck Road Use Electronics (TRUE)

5

Proprietary Applications

Smartphone Applications in Transportation

• Travel time estimates

• INRIX – Urban Mobility Report

• Xata Turnpike – Fleet management & optimization

• EROAD – New Zealand truck tax

• Emissions estimates

Literature Review

Literature Review

6

• 2008 Trip Identification Algorithm – Greaves & Figliozzi

• 2010 Validation of traffic models, off-peak deliveries – Holguin-Veras et al

• 2011 Multi-Criteria Performance Measures (Mobility, Emissions, Cost) – Wheeler & Figliozzi

• Combined GPS data & loop sensor data

• Emissions estimations using MOVES 2010

• 2012 Clean Trucks Program – You & Ritchie

• Identify truck depots

• Measure truck turnaround time at Ports

Academic Research (not a comprehensive review)

7

Project Background

8

Literature Review

Data Description

9

Location & Time Data

Data Description

10

Link to License Plate

Data Description

11

Link to WIM Data

Data Description

12

WIM Data

Preliminary Analysis

13

Primary Users by Weight Class

Preliminary Analysis

14

Class 1030 Counts

Next Steps – Short Term

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• Mobility

• Travel Time Reliability & Speed Measures

• Compare to PORTAL (Portland Oregon Regional

Transportation Archive)

• Planning & Modeling

• Emissions Estimations – MOVES (Motor Vehicle Emission Simulator)

• GreenSTEP Model – Greenhouse Gas Statewide Transportation Emissions Planning Model

• SWIM2 – ODOT Second Generation StateWide Integrated Model

• Oregon Freight Plan

• Data Improvements

TT – Travel Time

TTR – Travel Time Reliability

TTI – Travel Time Index

PTI – Planning Time Index

16

Acknowledgements

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Oregon Transportation Research and Education Consortium (OTREC)

Oregon Department of Transportation (ODOT)Greg Dal Ponte & Gina Salang (MCTD)

Becky Knudson (TPAU) & Myra Sperley (Research)Steve Ross, Chris Howell, Peter Douglas, Michael Bolliger (MCAD)

Questions

Katherine Bellbell2@pdx.edu

Miguel Figliozzifigliozzi@pdx.edu

Civil and Environmental EngineeringPortland State University

18

Literature Review

19

Future Research

Analysis Framework

20

Project Background

21

Freight Performance Measures

•Mobility, Congestion & Reliability

• Travel Time Reliability

• Congestion at bottlenecks

• System Condition – Maintenance & Preservation

• Bridge wear – f(Gross Vehicle Weight)

• Pavement wear – f(axle weights)

TT – Travel Time

TTR – Travel Time Reliability

TTI – Travel Time Index

PTI – Planning Time Index

cc

Pvmt / Bridge Forensics

Design Estimates

Weight limit violations

Applications

Freight Performance Measures

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• Environment – Emissions estimates (especially GHG)

• Safety

• Accessibility & Connectivity – ports, airports, highways

• Longer Combination Vehicle (LCV) Network Access

• Truck turnaround time at ports

Equipment

Cargo

Delay

Applications

23

Applications

Planning & Modeling

•Oregon Freight Plan – policy/investments vs. economic forecasts

•SWIM2 – ODOT Second Generation StateWide Integrated Model

•EPA MOVES – Motor Vehicle Emission Simulator

•GreenSTEP Model – Greenhouse Gas Statewide Transportation Emissions Planning Model

•Trip Generation Rates – Route, vehicle and mode choice