MuCCA

27/03/2020

    The Multi-Car Collision Avoidance Project (MuCCA) is a £4.6m, 30-month project funded by the Centre for Connected and Autonomous Vehicles (CCAV) via Innovate UK, which will develop a next-generation driver aid that aims to avoid multi-car collisions on motorways. If an accident cannot be avoided, the MuCCA system will attempt to minimise its consequences (both injuries and damage).

    Motorway pile-ups are costly, both in human and  financial terms: This technology aims first and foremost to avoid an accident, but if an accident cannot be  avoided, the MuCCA system will attempt to minimise their consequences. The project will culminate in a trial involving up  to five MuCCA-equipped connected vehicles, and one or more human-controlled vehicles, which will demonstrate how accidents can be avoided at high speed in simulated motorway conditions.

     

     

    Our objective is to avoid or minimise the impact of multi-car collisions, the project will develop:

    • L4 automated, cooperative system
    • Cooperative decision and trajectory control
    • Driver model for unequipped vehicle path prediction
    • Shared sensor-agnostic world view
    • Complex path prediction
    • Graceful degradation of performance
    • Insurance logging capability to support event reconstruction
    • Integrated simulation environment to evaluate complex crash scenarios
    • Cyber-security assessment for common requirements

     

    Our supporters and partners:

    The MuCCA consortium comprises leading experts from industry and academia. MuCCA is a Research & Development project funded by CCAV (Centre for Connected & Autonomous Vehicles) and Innovate UK, being delivered by a world-class consortium consisting of AppIus IDIADA, Cosworth, Cranfield University, Westfield Sportscars, Secure By Design and the Connected Places Catapult.

     

     

    Applus Servicios Tecnológicos, S.L.U. uses first-party and third-party cookies for analytical purposes and to show you personalized advertising based on a profile drawn up based on your browsing habits (eg. visited websites). Click HERE for more information. You can accept all cookies by pressing the "Accept" button or configure or reject their use by clicking here.

    Cookie settings panel