research-article

Understanding the Cost of Driving Trips

Authors:

Caleb Southern,

Gregory D. AbowdAuthors Info & Claims

CHI '17: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

Pages 430 - 434

https://doi.org/10.1145/3025453.3025686

Published: 02 May 2017 Publication History

Abstract

Driving is the second highest expense for the average American household. Yet few people know the total cost of owning and operating their vehicles, and most cannot estimate accurately how much a common driving trip (like a daily commute) costs. There are an increasing number of viable alternatives for personal transportation, such as car services (e.g. Uber, Lyft), in addition to ridesharing, transit, biking, and walking. Cost is one factor in transportation mode choice, and awareness of the cost of driving is useful in making better informed decisions. To bridge this awareness gap, we built and deployed a system that makes the total cost of each driving trip (including depreciation, maintenance, insurance, and fuel) visible to the user. After this intervention, participants were able to more accurately and confidently estimate costs of their driving commutes, and transfer this knowledge to other trips for which they had not seen a cost.

Supplementary Material

MP4 File (p430-southern.mp4)

Download
149.37 MB

References

[1]

Bureau of Labor Statistics. 2016. CONSUMER EXPENDITURES - 2015. Retrieved September 21, 2016 from http://www.bls.gov/news.release/pdf/cesan.pdf

[2]

Daniel A. Epstein, An Ping, James Fogarty, and Sean A. Munson. 2015. A lived informatics model of personal informatics. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp '15), 731--742. http://dx.doi.org/10.1145/2750858.2804250

Digital Library

[3]

E. Ferguson. 1990. Transportation Demand Management Planning, Development, and Implementation. Journal of the American Planning Association 56, 4: 442--456.

[4]

Brian Ferris, Kari Watkins, and Alan Borning. 2010. OneBusAway: results from providing real-time arrival information for public transit. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '10), 1807--1816. http://dx.doi.org/10.1145/1753326.1753597

Digital Library

[5]

Jon Froehlich, Tawanna Dillahunt, Predrag Klasnja, Jennifer Mankoff, Sunny Consolvo, Beverly Harrison, and James A. Landay. 2009. UbiGreen: investigating a mobile tool for tracking and supporting green transportation habits. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '09), 1043--1052. http://dx.doi.org/10.1145/1518701.1518861

Digital Library

[6]

Ian Hawkins. 2016. Torque - OBD Performance and Diagnostics for your Vehicle. Retrieved September 21, 2016 from https://torque-bhp.com/

[7]

Jin-Hyuk Hong, Ben Margines, and Anind K. Dey. 2014. A smartphone-based sensing platform to model aggressive driving behaviors. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '14), 4047--4056. http://dx.doi.org/10.1145/2556288.2557321

Digital Library

[8]

Kelley Blue Book Co. 2016. Kelley Blue Book - New and Used Car Price Values, Expert Car Reviews. Retrieved September 21, 2016 from http://www.kbb.com/

[9]

Ian Li, Anind Dey, and Jodi Forlizzi. 2010. A stagebased model of personal informatics systems. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '10), 557--566. http://dx.doi.org/10.1145/1753326.1753409

Digital Library

[10]

M. D. Meyer. 1999. Demand management as an element of transportation policy: using carrots and sticks to influence travel behavior. Transportation research. Part A, Policy and practice 33, 7-8: 575--599.

[11]

James O. Prochaska and Wayne F. Velicer. 1997. The transtheoretical model of health behavior change. American journal of health promotion 12,1: 38--48.

[12]

Richard H. Thaler and Cass R Sunstein. 2008. Nudge: Improving Decisions about Health, Wealth, and Happiness. Yale University Press.

[13]

Johannes Tulusan, Thorsten Staake, and Elgar Fleisch. 2012. Providing eco-driving feedback to corporate car drivers: what impact does a smartphone application have on their fuel efficiency? In Proceedings of the 2012 ACM Conference on Ubiquitous Computing (UbiComp '12), 212--215. http://dx.doi.org/10.1145/2370216.2370250

Digital Library

[14]

M. Wachs. 1991. Policy Implications of Recent Behavioral Research in Transportation Demand Management. Journal of Planning Literature 5.4: 333--341.

[15]

P. L. Winters. 2000. Transportation Demand Management. Retrieved September 21, 2016 from http://onlinepubs.trb.org/onlinepubs/millennium/00123.pdf

Cited By

Kjærup MSkov Mvan Berkel N(2021)E-Scooter Sustainability – A Clash of Needs, Perspectives, and ExperiencesHuman-Computer Interaction – INTERACT 202110.1007/978-3-030-85613-7_26(365-383)Online publication date: 30-Aug-2021
https://dl.acm.org/doi/10.1007/978-3-030-85613-7_26
Kjærup MSkov MAgerholm NBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)Digital-Enabled Last Mile: A Study of Passenger Trips in Rural, Low-density Populated AreasProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376509(1-12)Online publication date: 21-Apr-2020
https://dl.acm.org/doi/10.1145/3313831.3376509
Dec IChan EBasapur S(2018)SwayProceedings of the 32nd International BCS Human Computer Interaction Conference10.14236/ewic/HCI2018.132(1-5)Online publication date: 4-Jul-2018
https://dl.acm.org/doi/10.14236/ewic/HCI2018.132
Show More Cited By

Index Terms

Understanding the Cost of Driving Trips
1. Human-centered computing
  1. Human computer interaction (HCI)

Recommendations

Using an OpenDS Driving Simulator for Car Following: A First Attempt
AutomotiveUI '14: Adjunct Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

This paper describes the modifications to free, open-source driving simulator software to simulate a car-following task resembling that in the NHTSA driver distraction protocol. In brief, the peak-to-peak amplitudes of the lead vehicle were sharply ...
Gaze guidance reduces the number of collisions with pedestrians in a driving simulator

Our study explores the potential of gaze guidance in driving and analyzes eye movements and driving behavior in safety-critical situations. We collected eye movements from subjects instructed to drive predetermined routes in a driving simulator. While ...
Calling while driving: effects of providing remote traffic context
CHI '05: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Cell phone conversations distract drivers. This research explores the possibility of reducing distracting by providing callers with remote information about the driver's traffic. We asked whether providing such contextual information would change the ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

CHI '17: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

May 2017

7138 pages

ISBN:9781450346559

DOI:10.1145/3025453

General Chairs:
Gloria Mark
University of California Irvine
,
Susan Fussell
Cornell University
,
Program Chairs:
Cliff Lampe
University of Michigan
,
m.c. schraefel
University of Southampton
,
Juan Pablo Hourcade
University of Iowa
,
Caroline Appert
Université Paris-Sud
,
Daniel Wigdor
University of Toronto

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 May 2017

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

CHI '17

Sponsor:

SIGCHI

CHI '17: CHI Conference on Human Factors in Computing Systems

May 6 - 11, 2017

Colorado, Denver, USA

Acceptance Rates

CHI '17 Paper Acceptance Rate 600 of 2,400 submissions, 25%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

5
Total Citations
View Citations
785
Total Downloads

Downloads (Last 12 months)19
Downloads (Last 6 weeks)3

Reflects downloads up to 11 Aug 2024

Other Metrics

View Author Metrics

Citations

Cited By

Kjærup MSkov Mvan Berkel N(2021)E-Scooter Sustainability – A Clash of Needs, Perspectives, and ExperiencesHuman-Computer Interaction – INTERACT 202110.1007/978-3-030-85613-7_26(365-383)Online publication date: 30-Aug-2021
https://dl.acm.org/doi/10.1007/978-3-030-85613-7_26
Kjærup MSkov MAgerholm NBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)Digital-Enabled Last Mile: A Study of Passenger Trips in Rural, Low-density Populated AreasProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376509(1-12)Online publication date: 21-Apr-2020
https://dl.acm.org/doi/10.1145/3313831.3376509
Dec IChan EBasapur S(2018)SwayProceedings of the 32nd International BCS Human Computer Interaction Conference10.14236/ewic/HCI2018.132(1-5)Online publication date: 4-Jul-2018
https://dl.acm.org/doi/10.14236/ewic/HCI2018.132
Pinder CVermeulen JCowan BBeale R(2018)Digital Behaviour Change Interventions to Break and Form HabitsACM Transactions on Computer-Human Interaction10.1145/319683025:3(1-66)Online publication date: 12-Jun-2018
https://dl.acm.org/doi/10.1145/3196830
Verame JCostanza EFischer JCrabtree ARamchurn SRodden TJennings NMandryk RHancock MPerry MCox A(2018)Learning from the Veg BoxProceedings of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3173574.3174021(1-13)Online publication date: 21-Apr-2018
https://dl.acm.org/doi/10.1145/3173574.3174021

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents