Travel Buddy: a multimodal journey planning app
Travel Buddy: a multimodal journey planning app
Rethinking the way we plan and make a trip with a journey planning app that personalizes a route recommendation
Rethinking the way we plan and make a trip with a journey planning app that personalizes a route recommendation
Year
2021
Duration
2 weeks
Sector
Mobility
Type
Personal Project
Introduction
Introduction
This self-initiated UI/UX project extends insights from my Master’s thesis, exploring the key determinants of journey planning across different contexts. The project leverages these contextual factors as variables to optimize route recommendations.
Travel Buddy is a trip-planning app that enables users to customize and save trip parameters, allowing them to repeat their journeys effortlessly. By integrating phone data such as calendar events and incorporating real-time feedback from other travelers, the app streamlines travel planning and enhances decision-making.
This self-initiated UI/UX project extends insights from my Master’s thesis, exploring the key determinants of journey planning across different contexts. The project leverages these contextual factors as variables to optimize route recommendations.
Travel Buddy is a trip-planning app that enables users to customize and save trip parameters, allowing them to repeat their journeys effortlessly. By integrating phone data such as calendar events and incorporating real-time feedback from other travelers, the app streamlines travel planning and enhances decision-making.
Challenge
Challenge
To establish a collaborative relationship between users and a smart (AI-driven) travel assistant to enhance autonomy of users and engagement and to make that relations visible through implicit human-computer interaction data.
To establish a collaborative relationship between users and a smart (AI-driven) travel assistant to enhance autonomy of users and engagement and to make that relations visible through implicit human-computer interaction data.
To establish a collaborative relationship between users and a smart (AI-driven) travel assistant to enhance autonomy of users and engagement and to make that relations visible through implicit human-computer interaction data.
Discover
Discover
During the research phase, diverse research activities including mind-mapping session and survey were conducted and research participants have shared how they plan and make a trip and what influences them to make a decision.
During the research phase, diverse research activities including mind-mapping session and survey were conducted and research participants have shared how they plan and make a trip and what influences them to make a decision.
From these conversations, I identified key determinants of travel behavior, which I later mapped from independent to dependent factors to understand their influence on journey planning—and to use those factors as variables for AI-driven journey recommendations.
From these conversations, I identified key determinants of travel behavior, which I later mapped from independent to dependent factors to understand their influence on journey planning—and to use those factors as variables for AI-driven journey recommendations.
Quotes from users
Quotes from users
01 Travel behavior varies by context 💭
01 Travel behavior varies by context 💭
“It depends on the type of trip I’m making. For a trip across Europe, I want micro-level customization. Within the Netherlands, I’m fine with less control.It’s never about just one factor, all influence my decision.”
"In most cases, being on time matters most. But when I plan my weekend, I choose a store to visit and then wander around to discover new places. When I’m tired, I prefer the most convenient route.”
02 Multi-app journey planning 🤳 is common
02 Multi-app journey planning 🤳 is common
“I use multiple apps throughout my trip. I check the NS app for public transport schedules, Google Maps for navigation, and listen to Spotify while traveling. I don’t know any good app for cyclists though.”
“For cycling, my planning gets even more complex. I first browse Google Maps, then export the route to Komoot to find a suitable cycling path, and finally open Strava to track my ride.”
03 Emotional impact 💥 of journey planning
03 Emotional impact 💥 of journey planning
“Although getting to the destination matters, it’s not always about efficiency. I like taking the scenic route—stopping by a local café, or getting off the train one stop early for a short walk.
I use Google Maps because it works everywhere, but I usually open it when I’m stressed or short on time—so whether it helps or frustrates me depends on if I make it on time.”
04 Preferences 😍 and decision-making 🤔
04 Preferences 😍 and decision-making 🤔
“I prefer planning on a laptop so I can see the entire route. Even when going to familiar places, I use apps to discover something new along the way.”
“I procrastinate more now because I rely on apps until the last minute. Also, walking and cycling speed estimates vary by country, making travel time harder to predict.”
Key determinants of travel factors
Key determinants of travel factors
To dependent factors
To dependent factors
From independent factors
From independent factors
✦ Contextual factors
✦ Contextual factors
Weather, time of a day, emotion, disruption, need of a guidance specific to the mode of transport
Weather, time of a day, emotion, disruption, need of a guidance specific to the mode of transport
✦ Characteristic of a trip
✦ Characteristic of a trip
Familiarity of a location, purpose of a journey, motivation of a journey, companion
Familiarity of a location, purpose of a journey, motivation of a journey, companion
✦ Personal preference
✦ Personal preference
Transport mode, walking distance, the number of transfer, type of a train and etc.
Transport mode, walking distance, the number of transfer, type of a train and etc.
✦ Personal disposition
✦ Personal disposition
Way of making decisions, personality, dependency on technology, need of travel information
Way of making decisions, personality, dependency on technology, need of travel information
Define
Define
To foster a collaborative human-computer relationship, I established the design principle for Travel Buddy. The system should not only understand and adapt to a user’s evolving travel patterns and needs but also work alongside the user to identify their travel type.
To foster a collaborative human-computer relationship, I established the design principle for Travel Buddy. The system should not only understand and adapt to a user’s evolving travel patterns and needs but also work alongside the user to identify their travel type.
This approach helps users become aware of their unconscious habits while allowing them to fine-tune preferences in a more intuitive way.
Building on this principle, I then defined key design goals to guide the development process.
This approach helps users become aware of their unconscious habits while allowing them to fine-tune preferences in a more intuitive way.
Building on this principle, I then defined key design goals to guide the development process.
Learning
Understand and adapt to users’ travel patterns and underlying needs
Learning
Understand and adapt to users’ travel patterns and underlying needs
Learning
Understand and adapt to users’ travel patterns and underlying needs
Defining
Define and customize a user’s travel type together
Defining
Define and customize a user’s travel type together
Defining
Define and customize a user’s travel type together
Design goal
Design goal
The users should be able to repeat the quality of a trip when contextual factors and journey characteristics remain the same.
Users should have direct access to route parameters to flexibly adjust their journey and understand how recommendations are generated.
The app should make optimal use of relevant device data while maintaining user consent and control over data usage.
The users should be able to repeat the quality of a trip when contextual factors and journey characteristics remain the same.
Users should have direct access to route parameters to flexibly adjust their journey and understand how recommendations are generated.
The app should make optimal use of relevant device data while maintaining user consent and control over data usage.
The users should be able to repeat the quality of a trip when contextual factors and journey characteristics remain the same.
Users should have direct access to route parameters to flexibly adjust their journey and understand how recommendations are generated.
The app should make optimal use of relevant device data while maintaining user consent and control over data usage.
First Prototype
First Prototype
This early low-fidelity prototype illustrates the envisioned user experience within the app. It was utilized for user testing to gather insights and inform iterative refinements.
This early low-fidelity prototype illustrates the envisioned user experience within the app. It was utilized for user testing to gather insights and inform iterative refinements.
User Story
User Story
Scene 1: Weekday
Scene 1: Weekday
It’s Monday morning. She turns off her alarm and gets ready for work.
It’s Monday morning. She turns off her alarm and gets ready for work.
She checks her phone to review today’s schedule and the weather forecast to plan her commute.
She checks her phone to review today’s schedule and the weather forecast to plan her commute.
She has an important client meeting at the office this afternoon. Since the app predicts rain, she selects the "Commute - Rain" mode and schedules her trip.
She has an important client meeting at the office this afternoon. Since the app predicts rain, she selects the "Commute - Rain" mode and schedules her trip.
While she’s working, her smartwatch sends a notification reminding her to leave soon.
While she’s working, her smartwatch sends a notification reminding her to leave soon.
As she waits for the tram, the app blinks, confirming that it has detected the start of her trip.
As she waits for the tram, the app blinks, confirming that it has detected the start of her trip.
As she walks to Den Haag Centraal station, she receives a notification that her train will arrive in three minutes at Platform 4.
As she walks to Den Haag Centraal station, she receives a notification that her train will arrive in three minutes at Platform 4.
Scene 2: Weekend
Scene 2: Weekend
It’s Saturday morning. She wakes up and starts her day with a cup of coffee.
It’s Saturday morning. She wakes up and starts her day with a cup of coffee.
The weather looks amazing outside. With no set plans, she decides to go out.
The weather looks amazing outside. With no set plans, she decides to go out.
She opens the app and browses previously saved places on the map.
She opens the app and browses previously saved places on the map.
She finds a place she wants to visit and notices other saved locations nearby. She selects the "Good Mood, Nice Weather" travel mode.
She finds a place she wants to visit and notices other saved locations nearby. She selects the "Good Mood, Nice Weather" travel mode.
She adds her favorite café to the route, and the app automatically adjusts her trip schedule.
She adds her favorite café to the route, and the app automatically adjusts her trip schedule.
She cycles along the canal, enjoying the perfect weather on her way to the café.
She cycles along the canal, enjoying the perfect weather on her way to the café.
Outcome
Outcome
Home page
01 | Map-Centered Interface with Modular Widgets
The homepage features an interactive map as the primary interface, complemented by modular widgets and quick-access buttons.
Key travel insights—such as real-time weather updates, available mobility services, and nearby points of interest—are prioritized to support efficient journey planning.
The homepage features an interactive map as the primary interface, complemented by modular widgets and quick-access buttons.
Key travel insights—such as real-time weather updates, available mobility services, and nearby points of interest—are prioritized to support efficient journey planning.
Home page
02 | Quick Access to Saved Locations & Travel Modes
A persistent bottom sheet provides seamless access to frequently used locations and travel modes.
Route recommendations dynamically adapt to the selected mode, prioritizing relevant factors based on the user’s current travel situation.
A persistent bottom sheet provides seamless access to frequently used locations and travel modes.
Route recommendations dynamically adapt to the selected mode, prioritizing relevant factors based on the user’s current travel situation.
Home page - Calendar
03 | Work-Travel Integration
The homepage features an interactive map as the primary interface, complemented by modular widgets and quick-access buttons.
Key travel insights—such as real-time weather updates, available mobility services, and nearby points of interest—are prioritized to support efficient journey planning.
The homepage features an interactive map as the primary interface, complemented by modular widgets and quick-access buttons.
Key travel insights—such as real-time weather updates, available mobility services, and nearby points of interest—are prioritized to support efficient journey planning.
Travel Mode
04 | Personalized & Repeatable Travel Experience
Travel Modes offer customizable presets that incorporate users' preferences and real-world contextual factors.
Users can fine-tune route parameters—such as preferred transport type, cost, and time efficiency—to create personalized travel experiences that Travel Buddy can learn and refine over time.
Travel Modes offer customizable presets that incorporate users' preferences and real-world contextual factors.
Users can fine-tune route parameters—such as preferred transport type, cost, and time efficiency—to create personalized travel experiences that Travel Buddy can learn and refine over time.
Routes
05 | Adaptive Route Overview
Travel Buddy provides real-time route recommendations tailored to the selected mode.
Users receive a clear visual overview of essential travel details, including estimated duration, cost, transit points, and alternative options.
Travel Buddy provides real-time route recommendations tailored to the selected mode.
Users receive a clear visual overview of essential travel details, including estimated duration, cost, transit points, and alternative options.
Device Integration
06 | Seamless Wearable Assistance
Travel Buddy extends its functionality to wearable devices, ensuring real-time notifications, proactive travel updates, and hands-free assistance for a smoother commuting experience.
Travel Buddy extends its functionality to wearable devices, ensuring real-time notifications, proactive travel updates, and hands-free assistance for a smoother commuting experience.
Wireframe
Drop me a line at yeonjujuliejeon at gmail dot com
Currently based in the Washington D.C. Area