Handover Guidance AI for Self-Driving
Handover Guidance AI for Self-Driving
Handover Guidance AI for Self-Driving
Developed a multisensory AI guidance system for transitions from “autonomous” to “manual” driving, which reduced driver anxiety by 72% and shortened response time by 2.7 sec.
Developed a multisensory AI guidance system for transitions from “autonomous” to “manual” driving, which reduced driver anxiety by 72% and shortened response time by 2.7 sec.
Developed a multisensory AI guidance system for transitions from “autonomous” to “manual” driving, which reduced driver anxiety by 72% and shortened response time by 2.7 sec.
Overview

Genty: AI guide for Level 3 Autonomous Driving Transition

Genty: AI guide for Level 3 Autonomous Driving Transition

Role: Product Design l Period: 12 weeks, 2023 l Client: Independent Project

Role: Product Design l Period: 12 weeks, 2023 l

Client: Independent Project

Level 3 is the only stage where handovers from autonomous to manual driving occur. To address the safety risks inherent in these transitions, I designed a comprehensive AI-driven guide that delivers multi-sensory alerts—combining AI conversation, visual cues, HVAC, adjustments, and audio—across 6 critical handover scenarios. Internal validation demonstrated a 72% reduction in driver anxiety, a 2.7-second faster reaction time, an 87% improvement in safety, and a user satisfaction score of 4.8 out of 5.

Tools/Tech: Figma, Framer, Photoshop, etc.

Category

User experience

UI design

Visual design

Challenge

Only Level 3 autonomous vehicles require the driver to retake control during a handover, a moment that often involves delayed reaction, stress, and significant safety risks. However, existing systems lack real-time, intuitive support to guide drivers through this critical transition.

Objective

The goal was to design a comprehensive UX solution for Level 3 control transitions by identifying key scenarios based on real driving data, and applying LLM-powered AI guidance with multisensory feedback to reduce driver anxiety and improve response time.

Result

The system, optimized for six real-world scenarios, reduced driver anxiety by 72%, improved reaction time by 2.7 seconds, increased safety by 87%, and achieved a user satisfaction score of 4.8/5 in internal testing.

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