SlideShare a Scribd company logo
1 of 21
Download to read offline
Improving transport timetables
usability for mobile devices:
a case study
Manuel Martin Salvador, Marcin Budka, Tom Quay, Anthony Carver-Smith
11th International Conference on the Practice and Theory of Automated Timetabling
24/08/2016 - Udine, Italy
Mobile vs Desktop traffic
Mobile
Tablet
Desktop
August 2016
TransXChange: UK nationwide
standard for exchanging bus
schedules and related data.
● bus schedules including stops,
routes, departures times,
departure frequencies, etc.
● the days on which the services run
● bus operators information
● information about accessibility of
stops and services for wheelchair
and other users
● 316 pages PDF!
Transport data in the UK
NCT bus information system
TransXChange
file (XML)
Importing script
Journeys
Database
Timetable
generator
Journey
planner
Departure
boards
Real-time
information
Fares UI
UI
UI
NCT bus information system
TransXChange
file (XML)
Importing script
Journeys
Database
Timetable
generator
Journey
planner
Departure
boards
Real-time
information
Fares UI
UI
UI
Challenges
Timetable generation
- Support TransXChange
- Grouping lines with similar routes
- Day shifting (buses running after 00:00)
- On the move → Dynamic timetables
based on location and time
Timetable UX
- Small screen size (too large timetables)
→ Compress rows and columns
- Variable resolution (vertical vs horizontal
orientation) → Responsive
- User interaction → UI controls
Usability study
● Set some tasks for the user to solve
● Ask the user to think out loud
● Let the user freely interact with the app
● Take notes!
● Optional: eye tracking
Continuous usability testing
Hypothesis Design Develop Test Decide
Continuous usability testing
Hypothesis Design Develop Test Decide
Formulate the initial hypothesis. For example:
“90% of users can find the time to catch the next 1A bus at County Hall stop in less than 20 seconds”
Continuous usability testing
Hypothesis Design Develop Test Decide
Design one or more solutions that help to test the hypothesis. For example:
1. Plain timetable
2. Plain timetable + search box
3. Compacted timetable
Continuous usability testing
Hypothesis Design Develop Test Decide
Implement the solutions in a testing environment.
Continuous usability testing
Hypothesis Design Develop Test Decide
Perform the usability test by selecting a number of users and splitting them in different groups
(one group per solution). We should collect as much qualitative and quantitative feedback as
possible that can help make a final decision.
Continuous usability testing
Hypothesis Design Develop Test Decide
Analyse the results, present a report to the stakeholders, and decide the next steps.
Continuous usability testing
Hypothesis Design Develop Test Decide
Ideally, the final decision would be to release the best solution to the production environment.
However, the decision could be to reformulate the hypothesis, test different solutions, or
increase the number of users, among others.
Key performance indicators
American Customer Satisfaction Index (ACSI) indicators:
● Overall satisfaction. How did you feel overall with finding the information in the
timetable? From 1 (very dissatisfied) to 10 (very satisfied).
● Level of difficulty. How difficult was it to find the information that you needed? From
1 (extremely difficult) to 10 (extremely easy).
● Expectancy. Do you think that this timetable is the most appropriate tool for finding
the bus information? From 1 (falls short of your expectations) to 10 (exceeds your
expectations).
Additional feedback
Quantitative. For example:
● Number of taps
● Time per screen
● Total time
Qualitative. For example:
● User direct feedback
(spontaneous or using a
questionnaire)
● User indirect feedback
(when thinking out loud)
Timetable UX changes
Time navigation buttons
Tap on table to
expand/collapse stops
column
Header
3 rows direction/date
Button to show all stops
Row and column
highlighting
Only main stops are
initially displayed
Compact times by
frequency
Results
3 Tasks: easy, medium, difficult.
Total participants: 12
Splitted in 2 groups:
● Group A: original timetables
● Group B: new timetables
3 Key performance indicators:
● Satisfaction
● Difficulty
● Expectancy
Lessons learnt
Initial assumptions are often wrong
→ Test more, test often
Finding people to do testing (for
free) is difficult
→ Incentives could help
There is no “average” user
→ Find people from different
backgrounds
Future work
Take advantage of other
information sources:
● User journeys (e.g. automatic
highlighting based on user common
routes)
● Realtime information (e.g. show
where are the current buses)
● Disruptions (e.g. adjust times based
on planned disruption information)
Accessibility testing with visually
impaired users
Thanks
Slides: http://www.slideshare.net/draxus
Email: manuel.martin@wearebase.com
Twitter: @draxus

More Related Content

Similar to Improving transport timetables usability for mobile devices

Designfor Strangers
Designfor StrangersDesignfor Strangers
Designfor Strangersguest08cd22
 
Designfor Strangers
Designfor StrangersDesignfor Strangers
Designfor Strangersguestbdd02b
 
Designfo#{1} #{2}trangers
Designfo#{1} #{2}trangersDesignfo#{1} #{2}trangers
Designfo#{1} #{2}trangersguest0437b8
 
Designfor Strangers
Designfor StrangersDesignfor Strangers
Designfor Strangersguru100
 
Designfor strangers
Designfor strangersDesignfor strangers
Designfor strangersguestc72c35
 
Design For Strangers
Design For StrangersDesign For Strangers
Design For Strangerstest99
 
Rashmi Xerox Parc
Rashmi Xerox ParcRashmi Xerox Parc
Rashmi Xerox Parctest98
 
Basics of-usability-testing
Basics of-usability-testingBasics of-usability-testing
Basics of-usability-testingWBC Software Lab
 
2017 SeeClickFix Workshop - Closing the Loop - Improving Transit through Crow...
2017 SeeClickFix Workshop - Closing the Loop - Improving Transit through Crow...2017 SeeClickFix Workshop - Closing the Loop - Improving Transit through Crow...
2017 SeeClickFix Workshop - Closing the Loop - Improving Transit through Crow...Sean Barbeau
 
Driveway to Highway: Driving Outcomes with Infrastructure as a Product
Driveway to Highway: Driving Outcomes with Infrastructure as a ProductDriveway to Highway: Driving Outcomes with Infrastructure as a Product
Driveway to Highway: Driving Outcomes with Infrastructure as a ProductVMware Tanzu
 
Corso Interazione Uomo Macchina e Sviluppo Applicazioni Mobile - GoBus
Corso Interazione Uomo Macchina e Sviluppo Applicazioni Mobile - GoBusCorso Interazione Uomo Macchina e Sviluppo Applicazioni Mobile - GoBus
Corso Interazione Uomo Macchina e Sviluppo Applicazioni Mobile - GoBusAlessandro Longo
 
Usability Testing and QA 7-18-14
Usability Testing and QA 7-18-14Usability Testing and QA 7-18-14
Usability Testing and QA 7-18-14Shilpa Thanawala
 
Combining Methods: Web Analytics and User Testing
Combining Methods: Web Analytics and User TestingCombining Methods: Web Analytics and User Testing
Combining Methods: Web Analytics and User TestingUser Intelligence
 
FLUX·3D - Forward Looking User eXperience
FLUX·3D - Forward Looking User eXperienceFLUX·3D - Forward Looking User eXperience
FLUX·3D - Forward Looking User eXperienceMario Guillo
 
Designing Progressive and Interactive Analytics Processes for High-Dimensiona...
Designing Progressive and Interactive Analytics Processes for High-Dimensiona...Designing Progressive and Interactive Analytics Processes for High-Dimensiona...
Designing Progressive and Interactive Analytics Processes for High-Dimensiona...Cagatay Turkay
 

Similar to Improving transport timetables usability for mobile devices (20)

Designfor Strangers
Designfor StrangersDesignfor Strangers
Designfor Strangers
 
Biblioteca.
Biblioteca.Biblioteca.
Biblioteca.
 
Designfor Strangers
Designfor StrangersDesignfor Strangers
Designfor Strangers
 
Designfo#{1} #{2}trangers
Designfo#{1} #{2}trangersDesignfo#{1} #{2}trangers
Designfo#{1} #{2}trangers
 
Designfor Strangers
Designfor StrangersDesignfor Strangers
Designfor Strangers
 
Designfor strangers
Designfor strangersDesignfor strangers
Designfor strangers
 
Design For Strangers
Design For StrangersDesign For Strangers
Design For Strangers
 
Qué es un blog?
Qué es un blog?Qué es un blog?
Qué es un blog?
 
Rashmi Xerox Parc
Rashmi Xerox ParcRashmi Xerox Parc
Rashmi Xerox Parc
 
Basics of-usability-testing
Basics of-usability-testingBasics of-usability-testing
Basics of-usability-testing
 
Usability testing
Usability testingUsability testing
Usability testing
 
2017 SeeClickFix Workshop - Closing the Loop - Improving Transit through Crow...
2017 SeeClickFix Workshop - Closing the Loop - Improving Transit through Crow...2017 SeeClickFix Workshop - Closing the Loop - Improving Transit through Crow...
2017 SeeClickFix Workshop - Closing the Loop - Improving Transit through Crow...
 
Intranet Usability Testing
Intranet Usability TestingIntranet Usability Testing
Intranet Usability Testing
 
Driveway to Highway: Driving Outcomes with Infrastructure as a Product
Driveway to Highway: Driving Outcomes with Infrastructure as a ProductDriveway to Highway: Driving Outcomes with Infrastructure as a Product
Driveway to Highway: Driving Outcomes with Infrastructure as a Product
 
Corso Interazione Uomo Macchina e Sviluppo Applicazioni Mobile - GoBus
Corso Interazione Uomo Macchina e Sviluppo Applicazioni Mobile - GoBusCorso Interazione Uomo Macchina e Sviluppo Applicazioni Mobile - GoBus
Corso Interazione Uomo Macchina e Sviluppo Applicazioni Mobile - GoBus
 
Usability Testing and QA 7-18-14
Usability Testing and QA 7-18-14Usability Testing and QA 7-18-14
Usability Testing and QA 7-18-14
 
Combining Methods: Web Analytics and User Testing
Combining Methods: Web Analytics and User TestingCombining Methods: Web Analytics and User Testing
Combining Methods: Web Analytics and User Testing
 
FLUX·3D - Forward Looking User eXperience
FLUX·3D - Forward Looking User eXperienceFLUX·3D - Forward Looking User eXperience
FLUX·3D - Forward Looking User eXperience
 
Usability
UsabilityUsability
Usability
 
Designing Progressive and Interactive Analytics Processes for High-Dimensiona...
Designing Progressive and Interactive Analytics Processes for High-Dimensiona...Designing Progressive and Interactive Analytics Processes for High-Dimensiona...
Designing Progressive and Interactive Analytics Processes for High-Dimensiona...
 

More from Manuel Martín

Automatizando el aprendizaje basado en datos
Automatizando el aprendizaje basado en datosAutomatizando el aprendizaje basado en datos
Automatizando el aprendizaje basado en datosManuel Martín
 
Modelling Multi-Component Predictive Systems as Petri Nets
Modelling Multi-Component Predictive Systems as Petri NetsModelling Multi-Component Predictive Systems as Petri Nets
Modelling Multi-Component Predictive Systems as Petri NetsManuel Martín
 
Brand engagement with mobile gamification apps from a developer perspective
Brand engagement with mobile gamification apps from a developer perspectiveBrand engagement with mobile gamification apps from a developer perspective
Brand engagement with mobile gamification apps from a developer perspectiveManuel Martín
 
Effects of change propagation resulting from adaptive preprocessing in multic...
Effects of change propagation resulting from adaptive preprocessing in multic...Effects of change propagation resulting from adaptive preprocessing in multic...
Effects of change propagation resulting from adaptive preprocessing in multic...Manuel Martín
 
Automating Machine Learning - Is it feasible?
Automating Machine Learning - Is it feasible?Automating Machine Learning - Is it feasible?
Automating Machine Learning - Is it feasible?Manuel Martín
 
Towards Automatic Composition of Multicomponent Predictive Systems
Towards Automatic Composition of Multicomponent Predictive SystemsTowards Automatic Composition of Multicomponent Predictive Systems
Towards Automatic Composition of Multicomponent Predictive SystemsManuel Martín
 
From sensor readings to prediction: on the process of developing practical so...
From sensor readings to prediction: on the process of developing practical so...From sensor readings to prediction: on the process of developing practical so...
From sensor readings to prediction: on the process of developing practical so...Manuel Martín
 
Quick presentation for the OpenML workshop in Eindhoven 2014
Quick presentation for the OpenML workshop in Eindhoven 2014Quick presentation for the OpenML workshop in Eindhoven 2014
Quick presentation for the OpenML workshop in Eindhoven 2014Manuel Martín
 
Online Detection of Shutdown Periods in Chemical Plants: A Case Study
Online Detection of Shutdown Periods in Chemical Plants: A Case StudyOnline Detection of Shutdown Periods in Chemical Plants: A Case Study
Online Detection of Shutdown Periods in Chemical Plants: A Case StudyManuel Martín
 
Artificial Intelligence for Automating Data Analysis
Artificial Intelligence for Automating Data AnalysisArtificial Intelligence for Automating Data Analysis
Artificial Intelligence for Automating Data AnalysisManuel Martín
 
Handling concept drift in data stream mining
Handling concept drift in data stream miningHandling concept drift in data stream mining
Handling concept drift in data stream miningManuel Martín
 
Minería de secuencias de datos
Minería de secuencias de datosMinería de secuencias de datos
Minería de secuencias de datosManuel Martín
 
Minería de secuencias de datos
Minería de secuencias de datosMinería de secuencias de datos
Minería de secuencias de datosManuel Martín
 
AndalucíaPeople: Un sistema de recomendación para sitios de ocio de Andalucía
AndalucíaPeople: Un sistema de recomendación para sitios de ocio de AndalucíaAndalucíaPeople: Un sistema de recomendación para sitios de ocio de Andalucía
AndalucíaPeople: Un sistema de recomendación para sitios de ocio de AndalucíaManuel Martín
 
Operaciones Colectivas en MPI
Operaciones Colectivas en MPIOperaciones Colectivas en MPI
Operaciones Colectivas en MPIManuel Martín
 
Introducción a GNU/Linux
Introducción a GNU/LinuxIntroducción a GNU/Linux
Introducción a GNU/LinuxManuel Martín
 
Presentación Día de la Libertad del Software 2011
Presentación Día de la Libertad del Software 2011Presentación Día de la Libertad del Software 2011
Presentación Día de la Libertad del Software 2011Manuel Martín
 
Presentacion Taller de Introducción a Linux SFD2010
Presentacion Taller de Introducción a Linux SFD2010Presentacion Taller de Introducción a Linux SFD2010
Presentacion Taller de Introducción a Linux SFD2010Manuel Martín
 

More from Manuel Martín (20)

Hogar (Des)Conectado
Hogar (Des)ConectadoHogar (Des)Conectado
Hogar (Des)Conectado
 
Automatizando el aprendizaje basado en datos
Automatizando el aprendizaje basado en datosAutomatizando el aprendizaje basado en datos
Automatizando el aprendizaje basado en datos
 
Modelling Multi-Component Predictive Systems as Petri Nets
Modelling Multi-Component Predictive Systems as Petri NetsModelling Multi-Component Predictive Systems as Petri Nets
Modelling Multi-Component Predictive Systems as Petri Nets
 
Brand engagement with mobile gamification apps from a developer perspective
Brand engagement with mobile gamification apps from a developer perspectiveBrand engagement with mobile gamification apps from a developer perspective
Brand engagement with mobile gamification apps from a developer perspective
 
Effects of change propagation resulting from adaptive preprocessing in multic...
Effects of change propagation resulting from adaptive preprocessing in multic...Effects of change propagation resulting from adaptive preprocessing in multic...
Effects of change propagation resulting from adaptive preprocessing in multic...
 
Automating Machine Learning - Is it feasible?
Automating Machine Learning - Is it feasible?Automating Machine Learning - Is it feasible?
Automating Machine Learning - Is it feasible?
 
Towards Automatic Composition of Multicomponent Predictive Systems
Towards Automatic Composition of Multicomponent Predictive SystemsTowards Automatic Composition of Multicomponent Predictive Systems
Towards Automatic Composition of Multicomponent Predictive Systems
 
From sensor readings to prediction: on the process of developing practical so...
From sensor readings to prediction: on the process of developing practical so...From sensor readings to prediction: on the process of developing practical so...
From sensor readings to prediction: on the process of developing practical so...
 
Quick presentation for the OpenML workshop in Eindhoven 2014
Quick presentation for the OpenML workshop in Eindhoven 2014Quick presentation for the OpenML workshop in Eindhoven 2014
Quick presentation for the OpenML workshop in Eindhoven 2014
 
Online Detection of Shutdown Periods in Chemical Plants: A Case Study
Online Detection of Shutdown Periods in Chemical Plants: A Case StudyOnline Detection of Shutdown Periods in Chemical Plants: A Case Study
Online Detection of Shutdown Periods in Chemical Plants: A Case Study
 
Artificial Intelligence for Automating Data Analysis
Artificial Intelligence for Automating Data AnalysisArtificial Intelligence for Automating Data Analysis
Artificial Intelligence for Automating Data Analysis
 
Handling concept drift in data stream mining
Handling concept drift in data stream miningHandling concept drift in data stream mining
Handling concept drift in data stream mining
 
Minería de secuencias de datos
Minería de secuencias de datosMinería de secuencias de datos
Minería de secuencias de datos
 
Minería de secuencias de datos
Minería de secuencias de datosMinería de secuencias de datos
Minería de secuencias de datos
 
AndalucíaPeople: Un sistema de recomendación para sitios de ocio de Andalucía
AndalucíaPeople: Un sistema de recomendación para sitios de ocio de AndalucíaAndalucíaPeople: Un sistema de recomendación para sitios de ocio de Andalucía
AndalucíaPeople: Un sistema de recomendación para sitios de ocio de Andalucía
 
Decompiladores
DecompiladoresDecompiladores
Decompiladores
 
Operaciones Colectivas en MPI
Operaciones Colectivas en MPIOperaciones Colectivas en MPI
Operaciones Colectivas en MPI
 
Introducción a GNU/Linux
Introducción a GNU/LinuxIntroducción a GNU/Linux
Introducción a GNU/Linux
 
Presentación Día de la Libertad del Software 2011
Presentación Día de la Libertad del Software 2011Presentación Día de la Libertad del Software 2011
Presentación Día de la Libertad del Software 2011
 
Presentacion Taller de Introducción a Linux SFD2010
Presentacion Taller de Introducción a Linux SFD2010Presentacion Taller de Introducción a Linux SFD2010
Presentacion Taller de Introducción a Linux SFD2010
 

Recently uploaded

9892124323 | Book Call Girls in Juhu and escort services 24x7
9892124323 | Book Call Girls in Juhu and escort services 24x79892124323 | Book Call Girls in Juhu and escort services 24x7
9892124323 | Book Call Girls in Juhu and escort services 24x7Pooja Nehwal
 
哪里有卖的《俄亥俄大学学历证书+俄亥俄大学文凭证书+俄亥俄大学学位证书》Q微信741003700《俄亥俄大学学位证书复制》办理俄亥俄大学毕业证成绩单|购买...
哪里有卖的《俄亥俄大学学历证书+俄亥俄大学文凭证书+俄亥俄大学学位证书》Q微信741003700《俄亥俄大学学位证书复制》办理俄亥俄大学毕业证成绩单|购买...哪里有卖的《俄亥俄大学学历证书+俄亥俄大学文凭证书+俄亥俄大学学位证书》Q微信741003700《俄亥俄大学学位证书复制》办理俄亥俄大学毕业证成绩单|购买...
哪里有卖的《俄亥俄大学学历证书+俄亥俄大学文凭证书+俄亥俄大学学位证书》Q微信741003700《俄亥俄大学学位证书复制》办理俄亥俄大学毕业证成绩单|购买...wyqazy
 
CALL ON ➥8923113531 🔝Call Girls Saharaganj Lucknow best sexual service
CALL ON ➥8923113531 🔝Call Girls Saharaganj Lucknow best sexual serviceCALL ON ➥8923113531 🔝Call Girls Saharaganj Lucknow best sexual service
CALL ON ➥8923113531 🔝Call Girls Saharaganj Lucknow best sexual serviceanilsa9823
 
Chandigarh Call Girls Service ❤️🍑 9115573837 👄🫦Independent Escort Service Cha...
Chandigarh Call Girls Service ❤️🍑 9115573837 👄🫦Independent Escort Service Cha...Chandigarh Call Girls Service ❤️🍑 9115573837 👄🫦Independent Escort Service Cha...
Chandigarh Call Girls Service ❤️🍑 9115573837 👄🫦Independent Escort Service Cha...Niamh verma
 
Call US Pooja 9892124323 ✓Call Girls In Mira Road ( Mumbai ) secure service,
Call US Pooja 9892124323 ✓Call Girls In Mira Road ( Mumbai ) secure service,Call US Pooja 9892124323 ✓Call Girls In Mira Road ( Mumbai ) secure service,
Call US Pooja 9892124323 ✓Call Girls In Mira Road ( Mumbai ) secure service,Pooja Nehwal
 
CALL ON ➥8923113531 🔝Call Girls Gomti Nagar Lucknow best Night Fun service
CALL ON ➥8923113531 🔝Call Girls Gomti Nagar Lucknow best Night Fun serviceCALL ON ➥8923113531 🔝Call Girls Gomti Nagar Lucknow best Night Fun service
CALL ON ➥8923113531 🔝Call Girls Gomti Nagar Lucknow best Night Fun serviceanilsa9823
 
Model Call Girl in Shalimar Bagh Delhi reach out to us at 🔝8264348440🔝
Model Call Girl in Shalimar Bagh Delhi reach out to us at 🔝8264348440🔝Model Call Girl in Shalimar Bagh Delhi reach out to us at 🔝8264348440🔝
Model Call Girl in Shalimar Bagh Delhi reach out to us at 🔝8264348440🔝soniya singh
 

Recently uploaded (7)

9892124323 | Book Call Girls in Juhu and escort services 24x7
9892124323 | Book Call Girls in Juhu and escort services 24x79892124323 | Book Call Girls in Juhu and escort services 24x7
9892124323 | Book Call Girls in Juhu and escort services 24x7
 
哪里有卖的《俄亥俄大学学历证书+俄亥俄大学文凭证书+俄亥俄大学学位证书》Q微信741003700《俄亥俄大学学位证书复制》办理俄亥俄大学毕业证成绩单|购买...
哪里有卖的《俄亥俄大学学历证书+俄亥俄大学文凭证书+俄亥俄大学学位证书》Q微信741003700《俄亥俄大学学位证书复制》办理俄亥俄大学毕业证成绩单|购买...哪里有卖的《俄亥俄大学学历证书+俄亥俄大学文凭证书+俄亥俄大学学位证书》Q微信741003700《俄亥俄大学学位证书复制》办理俄亥俄大学毕业证成绩单|购买...
哪里有卖的《俄亥俄大学学历证书+俄亥俄大学文凭证书+俄亥俄大学学位证书》Q微信741003700《俄亥俄大学学位证书复制》办理俄亥俄大学毕业证成绩单|购买...
 
CALL ON ➥8923113531 🔝Call Girls Saharaganj Lucknow best sexual service
CALL ON ➥8923113531 🔝Call Girls Saharaganj Lucknow best sexual serviceCALL ON ➥8923113531 🔝Call Girls Saharaganj Lucknow best sexual service
CALL ON ➥8923113531 🔝Call Girls Saharaganj Lucknow best sexual service
 
Chandigarh Call Girls Service ❤️🍑 9115573837 👄🫦Independent Escort Service Cha...
Chandigarh Call Girls Service ❤️🍑 9115573837 👄🫦Independent Escort Service Cha...Chandigarh Call Girls Service ❤️🍑 9115573837 👄🫦Independent Escort Service Cha...
Chandigarh Call Girls Service ❤️🍑 9115573837 👄🫦Independent Escort Service Cha...
 
Call US Pooja 9892124323 ✓Call Girls In Mira Road ( Mumbai ) secure service,
Call US Pooja 9892124323 ✓Call Girls In Mira Road ( Mumbai ) secure service,Call US Pooja 9892124323 ✓Call Girls In Mira Road ( Mumbai ) secure service,
Call US Pooja 9892124323 ✓Call Girls In Mira Road ( Mumbai ) secure service,
 
CALL ON ➥8923113531 🔝Call Girls Gomti Nagar Lucknow best Night Fun service
CALL ON ➥8923113531 🔝Call Girls Gomti Nagar Lucknow best Night Fun serviceCALL ON ➥8923113531 🔝Call Girls Gomti Nagar Lucknow best Night Fun service
CALL ON ➥8923113531 🔝Call Girls Gomti Nagar Lucknow best Night Fun service
 
Model Call Girl in Shalimar Bagh Delhi reach out to us at 🔝8264348440🔝
Model Call Girl in Shalimar Bagh Delhi reach out to us at 🔝8264348440🔝Model Call Girl in Shalimar Bagh Delhi reach out to us at 🔝8264348440🔝
Model Call Girl in Shalimar Bagh Delhi reach out to us at 🔝8264348440🔝
 

Improving transport timetables usability for mobile devices

  • 1. Improving transport timetables usability for mobile devices: a case study Manuel Martin Salvador, Marcin Budka, Tom Quay, Anthony Carver-Smith 11th International Conference on the Practice and Theory of Automated Timetabling 24/08/2016 - Udine, Italy
  • 2. Mobile vs Desktop traffic Mobile Tablet Desktop August 2016
  • 3. TransXChange: UK nationwide standard for exchanging bus schedules and related data. ● bus schedules including stops, routes, departures times, departure frequencies, etc. ● the days on which the services run ● bus operators information ● information about accessibility of stops and services for wheelchair and other users ● 316 pages PDF! Transport data in the UK
  • 4. NCT bus information system TransXChange file (XML) Importing script Journeys Database Timetable generator Journey planner Departure boards Real-time information Fares UI UI UI
  • 5. NCT bus information system TransXChange file (XML) Importing script Journeys Database Timetable generator Journey planner Departure boards Real-time information Fares UI UI UI
  • 6. Challenges Timetable generation - Support TransXChange - Grouping lines with similar routes - Day shifting (buses running after 00:00) - On the move → Dynamic timetables based on location and time Timetable UX - Small screen size (too large timetables) → Compress rows and columns - Variable resolution (vertical vs horizontal orientation) → Responsive - User interaction → UI controls
  • 7. Usability study ● Set some tasks for the user to solve ● Ask the user to think out loud ● Let the user freely interact with the app ● Take notes! ● Optional: eye tracking
  • 8. Continuous usability testing Hypothesis Design Develop Test Decide
  • 9. Continuous usability testing Hypothesis Design Develop Test Decide Formulate the initial hypothesis. For example: “90% of users can find the time to catch the next 1A bus at County Hall stop in less than 20 seconds”
  • 10. Continuous usability testing Hypothesis Design Develop Test Decide Design one or more solutions that help to test the hypothesis. For example: 1. Plain timetable 2. Plain timetable + search box 3. Compacted timetable
  • 11. Continuous usability testing Hypothesis Design Develop Test Decide Implement the solutions in a testing environment.
  • 12. Continuous usability testing Hypothesis Design Develop Test Decide Perform the usability test by selecting a number of users and splitting them in different groups (one group per solution). We should collect as much qualitative and quantitative feedback as possible that can help make a final decision.
  • 13. Continuous usability testing Hypothesis Design Develop Test Decide Analyse the results, present a report to the stakeholders, and decide the next steps.
  • 14. Continuous usability testing Hypothesis Design Develop Test Decide Ideally, the final decision would be to release the best solution to the production environment. However, the decision could be to reformulate the hypothesis, test different solutions, or increase the number of users, among others.
  • 15. Key performance indicators American Customer Satisfaction Index (ACSI) indicators: ● Overall satisfaction. How did you feel overall with finding the information in the timetable? From 1 (very dissatisfied) to 10 (very satisfied). ● Level of difficulty. How difficult was it to find the information that you needed? From 1 (extremely difficult) to 10 (extremely easy). ● Expectancy. Do you think that this timetable is the most appropriate tool for finding the bus information? From 1 (falls short of your expectations) to 10 (exceeds your expectations).
  • 16. Additional feedback Quantitative. For example: ● Number of taps ● Time per screen ● Total time Qualitative. For example: ● User direct feedback (spontaneous or using a questionnaire) ● User indirect feedback (when thinking out loud)
  • 17. Timetable UX changes Time navigation buttons Tap on table to expand/collapse stops column Header 3 rows direction/date Button to show all stops Row and column highlighting Only main stops are initially displayed Compact times by frequency
  • 18. Results 3 Tasks: easy, medium, difficult. Total participants: 12 Splitted in 2 groups: ● Group A: original timetables ● Group B: new timetables 3 Key performance indicators: ● Satisfaction ● Difficulty ● Expectancy
  • 19. Lessons learnt Initial assumptions are often wrong → Test more, test often Finding people to do testing (for free) is difficult → Incentives could help There is no “average” user → Find people from different backgrounds
  • 20. Future work Take advantage of other information sources: ● User journeys (e.g. automatic highlighting based on user common routes) ● Realtime information (e.g. show where are the current buses) ● Disruptions (e.g. adjust times based on planned disruption information) Accessibility testing with visually impaired users