
Eve autonomy and Panasonic Production Engineering have built a system combining outdoor autonomous transport vehicles with AI-powered remote operation capabilities. In a demonstration at ENEOS's Negishi refinery, operators were able to control vehicles from the office when obstacles blocked the path, eliminating the need to travel to the site—reducing travel time and improving working conditions.
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eve autonomyとパナソニック プロダクションエンジニアリングが、屋外自動搬送システム「eve auto」と遠隔監視・操作システム「X-Area Remote」を連携させるシステムを構築しました。ENEOS根岸製油所での実証で、搬送中に障害物で停止した際にオフィスから安全に回避操作を行える実用性が確認されました。
なぜ重要か
従来、製油所内で無人搬送車が障害物で停止するたびに担当者が現場へ駆け付け手動運転で対応していたため、広大な敷地での往復時間が業務効率に影響していました。遠隔操作により、現場への移動が不要になり、ヘルメット着用も不要で、オフィス業務の合間に対応できるようになり、作業環境が改善される見通しがあります。
注目点
「eve auto」は全国約60拠点・100台が稼働しており、日本国内の構内屋外搬送分野をリードしています。実証は、2023年からeve autoを活用しているENEOS根岸製油所の実際の運用環境で実施されました。
Eve autonomy's eve auto service operates at approximately 60 locations nationwide with around 100 vehicles and leads Japan's outdoor transport sector within factory and plant grounds. The system uses advanced autonomous driving technology (SAE Level 4) combined with reliable EV carts to enable 24-hour unmanned operation even in rain and at night. However, real-world factory and plant environments present frequent unplanned situations—such as equipment construction work—that can stop autonomous vehicles.
Panasonic's X-Area Remote system brings AI-powered remote monitoring and operation capabilities across airports, factories, and logistics facilities. By integrating eve auto with X-Area Remote, the companies created a unified solution that allows human operators to monitor and intervene when needed, without requiring specialized driving skill or on-site presence. The Negishi refinery case study demonstrates the practical value: staff can now handle obstacle avoidance from the office during normal work hours, eliminating both travel burden and the need for protective equipment. This integration represents a step toward fully unmanned transport operations by adding a reliable human-in-the-loop capability for edge cases that pure autonomous systems cannot yet handle independently.
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