Ignite, OST drive to solve autonomous vehicle challenges with AI | Computer Weekly

UK applications are opening for operators to run autonomous taxis, buses, and private-hire cars. Ignite by Forvia Hella is collaborating with Oxford Semantic Technologies to build an explainable AI service for autonomous vehicles. The collaboration targets difficulties in proving road safety compliance when vehicles face complex decision-making, including incidents such as driving into flooded roads. Driving performance is improving, but manufacturers lack robust methods to demonstrate safety, compliance, and decision logic at scale. This limits progress from Level 2, where the driver remains legally responsible, to Level 3 and Level 4 autonomy. Knowledge-based AI can act as a rulebook and memory by capturing real-time actions, cross-referencing traffic rules, and ensuring decisions are logical, traceable, and compliant. Engineers receive a white-box view to understand AI decisions, improve safety features, and seek approval with hard evidence.

"The partners noted that their partnership comes as leading autonomous vehicle providers face challenges as their vehicles continue to deal with complex decision-making, resulting in, in some cases, vehicles driving into flooded roads. In addition, the partners say that while driving performance is improving in AVs, manufacturers still lack robust ways to prove safety, compliance and decision logic at scale."

"This, they insist, has created a blocker on progressing to higher levels of autonomy, with manufacturers struggling to move from Level 2 (partial driving automation where the driver is legally responsible) to Level 3 (conditional driving automation where the manufacturer assumes liability) and Level 4 (fully autonomous driving). The collaboration will aim to address the industry's struggle to progress from Level 2 to Level 4 autonomy by providing ways to prove safety, compliance and decision logic at scale."

"It will also look to provide software engineers with a "white box" so they can understand how AI makes decisions, to improve safety features and seek approval with hard evidence. For autonomous vehicles, knowledge-based AI can be used as the vehicle's rulebook and memory - capturing everything the car does in real time, cross-referencing it against traffic rules, and ensuring every decision it makes is logical, traceable and compliant."

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