INLane
english
中文

Overview

InLane is your AI driving coach that analyzes your driving behavior through camera recording, helping you identify weaknesses and improve your skills with personalized feedback.

Industry/

Technology

Personality/

Intuitive
Helpful
Trustworthy

Services/

Brand Identity
research
User Journey
Storyboard
Usability Testing
Mobile Design

tool/

figma

Overview

InLane 是一款尖端的移动应用程序，旨在增强您的驾驶体验。 它利用先进技术，提供个性化指导和实时分析，使您成为更熟练、更安全的驾驶员。 借助 InLane，您可以识别弱点、跟踪进度并从虚拟顾问那里获得量身定制的指导。 无论您是寻求提高技能的经验丰富的驾驶员，还是希望建立自信的新手，InLane 都是您值得信赖的路上伴侣，确保每次旅程顺利而愉快。

Industry/

科技

Personality/

直观的
有帮助的
值得信赖的

SERVICES/

命名
品牌形象
研究
用户旅程
故事版
线框图
可用性测试
APP设计

工具/

figma
Jitter

The Problem

New drivers are facing no one or/the right person to help them practice. 
This leads to difficulty in developing their weakness which causes them to be able to be a proficient driver on the road alone.

Design Thinking Process

Empathize

Deliver

Define

Ideate

Test

The Problem

Many inexperienced drivers have their licenses and are facing no one beside to help them master driving skills.

Design Thinking Process

Empathize

Define

Deliver

Test

Ideate

Research

I made survey and user interview to understand the needs and challenges faced by the drivers during their driving experiences and also developed an interview guide for driving instructors.

Pain Points

Through the empathy mapping exercise, which helped me better understand drivers' experiences and emotions, I identified three primary pain points from our research findings:

Pain 1

  • Difficulty remembering all the details of past driving experiences

Pain 2

  • No one available to provide assistance

Pain 3

  • Physical driving coaches are too expensive at $120 per hour

Analyze Users’ Daily Driving Workflow

To better understand users' driving needs and provide effective assistance, I also analyzed users' daily driving patterns.

User Mindset

  • Before driving:
    A mix of anticipation and anxiety, often under time pressure.
  • Brief rest periods immediately after driving

Optimal Usage Times

  • Evening leisure hours
  • Weekend mornings or afternoons
  • Brief rest periods immediately after driving

Usage Locations

  • At home
  • In parking lots
  • Inside the car (when not driving)

Key Findings

  • Users need to review and learn in a non-driving state
  • Easy to get distracted while driving, making real-time feedback unsuitable
sketches

Competitor

sketches

The Solution

Data collection is crucial at this case- to help drivers practice effectively, we first need to capture their driving behavior to identify weaknesses and provide guidance.

Potential Data Sources options:

  • Direct camera footage
  • Car manufacturers' built-in systems
  • ADAS-equipped vehicles or OBD hardwear to read CPU
  • VR driving simulations

Due to:

  • Cost-effective solution for users
  • The universal applicability of cameras to any vehicle
  • Lower implementation complexity
  • Independence from car manufacturers' systems

I chose to focus on direct camera footage, developing a solution that captures and analyzes driving behavior using:

  • 360° camera recording
  • AI-powered driving analysis

Brainstorming The Solutions  

Styleguide

Product Feasibility

After identifying our drivers' pain points, I now need to answer two critical questions: Can this solution be built, and will it truly solve drivers' problems?

Value Proposition

User Journey

Storyboard

sketches

Wireframe

Design System

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sketches

Usability Testing

sketches

Full Fidelity Design

key features

Onboarding

What I would Iterate

Based on further consideration, these areas I will explore and develop:

Enhanced Playback Experience

  • Map visualization for route memory
  • Interior camera footage for behavior recall

Technical Optimization

  • Video quality adjustment for different networks
  • Wi-Fi connection reliability
  • Software version compatibility

User Support

  • Accessible contact system
  • Clear help documentation
  • Inside the car (when not driving)

Onboarding

With utilizes a friendly Dwindle mascot guides user through initial setup, coupled with a customizable social media plan and  visualized data time usage,to  approach makes it easier for users to accept the need to disengage from their phone screens.

Key Feature

A 'Quick Focus Zone' equipped with a timer and pickup tracking encourages focused work sessions. Dwindle also offers interest-based guidance to cultivate habits beyond the screen, thereby supporting mental health, fostering user engagement, extending focus duration, and enhancing workplace productivity

Heading

Fynspo

UI/UX