Event Information
Information
© 2026 神奈川工科大学，ROAD
Sponsoring & Speaking at ROAD 2026 in KAIT
NTT DATA Automobiligence Research Center (ARC) is proud to sponsor ROAD 2026 in KAIT,
the 7th Roundtable on the Purpose of Autonomous Driving,
and will present a session during the Conference Dinner on Thursday, October 1.
We look forward to meeting you there.
Event Overview
ROAD 2026 in KAIT
The 7th Roundtable on the Purpose of Autonomous Driving
| Organizer | Vehicle Research Institute (VRI), Kanagawa Institute of Technology |
|---|---|
| Date & Venue | Wed, September 30 – Fri, October 2, 2026
Kanagawa Institute of Technology1030 Shimo-ogino, Atsugi-shi, Kanagawa, Japan |
| Admission | Please refer to the official website below for participation and registration details. |
| Official site | ROAD 2026: The 7th Roundtable on the Purpose of Autonomous Driving |
ARC Session
| Session title | Safety Assurance for E2E Autonomous Driving |
|---|---|
| Speaker | Nathan Boyer Associate Research Scientist, Advanced Laboratory NTT DATA Automobiligence Research Center, Ltd. |
| Time | Around 19:00, during the Conference Dinner (18:30 – 20:30) |
| Venue | Conference Dinner venue: Motoyu Jinya (Tsurumaki Onsen) Transfer from Kanagawa Institute of Technology by charter bus |
The detailed schedule of the Conference Dinner is currently being finalized.
Our Focus at ROAD 2026
ARC develops tools and solutions that make the development and operation of next-generation vehicle software safer and more efficient — from scenario-based validation of autonomous driving systems to explainable AI development and AI-powered testing.
Scenario-based development platform
"ZIPC GARDEN"
A suite of software services that transforms the development and operation processes of next-generation automotive systems, enabling the assurance and argumentation of autonomous driving system safety.
AI development platform that visualizes AI weaknesses
"ZIPC SEAS"
Advanced AI such as autonomous driving AI must be not only high-performing but also explainably safe. SEAS visualizes the weaknesses of AI models and rapidly reinforces them with virtual data, realizing an explainable AI improvement loop.
AI testing tools for efficient, high-quality software development
"ZIPC MLTEST"
The ZIPC MLTEST series uses AI analysis to automate test design, test execution, and code defect extraction, enabling faster testing processes and higher quality.
CONTACT
Meet ARC at ROAD 2026. If you have any questions or inquiries about our tools and solutions, please feel free to contact us.