reliablE in-Vehicle pErception and decisioN-making in complex environmenTal conditionS

EVENTS Project

Robust perception and decision-making for automated driving

Driving is a challenging task. In our everyday life as drivers, unexpected situations rise and need to be handled in a safe and efficient way. The same is valid for Connected and Automated Vehicles (CAVs), which also need to respond in these situations, to a certain extent, depending on their automation level. The higher the automation level is, the higher the expectations for the system to cope with these situations are. In the context of EVENTS project, these unexpected situations, where the normal operation of the CAV is close to be disrupted (e.g. ODD limit is reached due to traffic changes, harsh weather/light conditions, imperfect data, sensor/communication failures, etc.), are called “events”. These “events” are creating challenges for CAVs that should be overcome in order to enable safe and reliable automated driving in such cases.

The EVENTS project aims to create a robust and resilient perception and decision-making system, able to tackle the abovementioned challenges. In EVENTS, in case the system or some of the subsystems cannot perform with the expected quality and reliability, an improved minimum risk manoeuvre is triggered.

Use Cases

Interaction with VRUs in Complex Urban Environment

Safe and resilient automated driving in complex urban environment has to cope with cluttered surroundings (occlusions), multiple road users etc. Particular focus is laid on interacting with Vulnerable Road Users (e.g. pedestrians, cyclists).

Non-Standard & Unstructured Road Conditions

Nowadays, automated driving systems feature ODDs which assume benevolent, normative traffic conditions and roads with lane markings. This use case investigates non-standard and unstructured road conditions, for example, road work- or accident-zones and urban park areas with no lane markings.

Low Visibility and Adverse Weather Conditions

The majority of AD functions today is designed for “normal” environmental conditions, i.e. clear weather (no rain/snow/fog/low-standing-blinding sun) and daytime. This use case aims to extend the environmental conditions of AD functions.

Project Information

Start Date:

1st September 2022

End Date:

31st August 2025

Total Cost

€ 6.920.598,00

EU Contribution

€ 5.534.448,00

Latest News

Recent Tweets

🚨 ✨ Fireside Chat on Safe AI
At @MOVE_Event 2024, @gates_sj @wayve_ai & I will hold a fireside chat to talk about 𝗔𝗜 𝗶𝗻 𝘀𝗲𝗹𝗳-𝗱𝗿𝗶𝘃𝗶𝗻𝗴 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆, and how to ensure we use AI safely & responsibly 🔭

🗓️19 June 2024
⏰: 15:10-15:30

Load More

Project Consortium

EVENTS Consortium comprises of 12 partners within 6 EU Member States and UK. The project has followed a multidisciplinary approach, purposefully selecting partners with distinct scientific, technical and operational expertise to secure high-quality contributions in addressing all aspects of the project.