2017 CE Survey Methods 

Symposium

Washington, D.C.

July 18, 2017

Josh DeLaRosa

Use of GPS Devices to Enhance Travel 

Behavior Diaries
Overview

1. Understanding of Household Travel 

Surveys (HTS)

2. Limitations of Travel Diaries

3. GPS and Cellular Assisted Enhanced 

Diaries

4. Logistical, Privacy and Technical 

Considerations

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Summary

A. HTS: capture key data to understand 

travel behavior

B. Detailed data = respondent burden

C. GPS/cellular data to minimize 

measurement error & item-nonresponse

D. GPS/smartphone data introduces project 

management & measurement issues

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Understanding Travel Behavior

• Travel Demand Modeling

– Transportation planning

• High Resolution

– Spatial

– Temporal

• Household

– Number of vehicles

• Person

– Demographics

• Trip

– Purpose of trip

– Mode

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1

2

3

4

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National Academies of Sciences, Engineering, and Medicine. 

2014. Activity-Based Travel Demand Models: A Primer. 

Washington, DC: The National Academies Press. 

https://doi.org/10.17226/22357.
HTS Study Design

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Household 

Survey

Roster

Demographics

Contact information

Person 

Level 

Travel 

Diary

Address - Geocodable to the Census block

Time (HH:MM)

Purpose (e.g. school, shopping, work, etc.)

Mode (vehicle, transit, etc.)
Travel Diary Data Quality

• Item nonresponse

– Zero trip days

– Unreported trips

• Measurement error

– Trip times

– Trip locations

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GPS Data Enhancements

• Subsample given GPS logger or 

smartphone app

• Location data is collected passively at 

prescribed intervals

• Purpose inferred by location

• Mode inferred by speed

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Typology of Location Data

• Trace files

• Cellular Tower Data

• WiFi

• Bluetooth Beacons

• GPS

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GPS Logging

• Devices log location 

and time

• Data processed ex 

post facto

• Diary data matched 

and compared to 

device data

• Develop 

underreported trip 

estimate

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Prompted Recall

• Location data 

processed near real 

time (GSM/Wifi)

• Parsed GPS are 

transformed to trips 

(O/D)

• Machine Learning is 

used to pre-fill diary

• Respondent 

verifies/edits trips

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Zhao, F.; Ghorpade, A.; Pereira, F.C.; Zegras, C.; Ben-Akiva, M. Stop 

Detection in Smartphone-based Travel Surveys. Transp. Res. Proc. 

2015, 11, 218–226.
Tel-Aviv

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Trip counts

Prompted Recall vs Diary

Nahmias-Biran B., Han Y.,Taepan K., Zhao F., Bekhor S., Zegras C., Ben-Akiva M. “Enriching 

Activity Based Models Using Smartphone-Based Travel Surveys.” SMART Future Urban 

Mobility Symposium 2017. 11 July 2017, Singapore. 
Singapore

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Trip counts

Prompted Recall vs Diary

Nahmias-Biran B., Han Y.,Taepan K., Zhao F., Bekhor S., 

Zegras C., Ben-Akiva M. “Enriching Activity Based Models 

Using Smartphone-Based Travel Surveys.” SMART Future 

Urban Mobility Symposium 2017. 11 July 2017, Singapore. 
Location Quality Issues

• Location data 

vulnerable to 

measurement error

– User error

– Device error

– Processing error

– GPS signal quality

http://bit.ly/AAPOR17_GPS

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Logistical and Privacy Issues

• Data privacy

• Recruitment Bias?

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Logistical and Privacy Issues (2)

• Smartphone 

ownership

• Cost

– Device/shipping cost

– GSM cost

– App cost

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Conclusion

• Travel diaries have a high level of 

respondent burden

• GPS and cellular data can improve the 

quality of travel diary data

• Passive location data add complexity and 

cost

• Location data is subject to error

• Diaries still need to capture attitudes and 

opinions

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Questions?

Use of GPS Devices to Enhance Travel 

Behavior Diaries

Josh_delarosa@abtassoc.com

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