MuCCA aims to develop a next-generation driver aid that will avoid (or reduce the consequences of) multi-car collisions on motorways. It consists of a six-member UK consortium working on a 30-month, £4.6m project, partly funded by Innovate UK. Download Here.
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In late 2019, a technology demonstration which only a few years ago would have been written off as impossible will take place. The MuCCA (Multi-Car Collision Avoidance) project, led by IDIADA UK and with financial support from Innovate UK, is developing a collaborative system that will enable connected and autonomous vehicles to avoid collisions. MuCCA-equipped cars will communicate with each other in the fractions of a second before a potential crash – and agree and act upon the best course of evasive action for each individual vehicle to take. Although connected and autonomous vehicles (CAVs) are expected to become increasingly common on our roads in the next few years, many non-autonomous ‘human driven’ vehicles will remain for the foreseeable future, so the system will also take on the added complexity of anticipating the likely behaviour of any human drivers who are in the vicinity of the potential crash. Given the fractions of a second in which the system will have to decide the optimal trajectories and in which the various vehicles will also have to execute the plan, this may all sound like science fiction. And, indeed, even those of us who are working on the project would be the first to admit that we are absolutely pushing at the limits of what is possible in terms of communication, processing power, and sensor capabilities. This is an R&D project, so we do not expect that at the end of the project we will have a system that is ready to be put into production cars, but we are confident that we will end up with a “proof of concept” – as well as a much better understanding of what is currently possible, and where the biggest challenges lie in truly achieving a safety system with sufficient swarm-like capabilities. Simplifying the scope Making that clear distinction between a system that is ready for “real roads” and a technology that is being trialled in a highly-controlled environment has, in fact, been the main factor in helping to move the proposed MuCCA system from those realms of impossibility and into an area that is ‘merely’ extremely challenging. A key early role played by my own organisation, the Transport Systems Catapult, was to define the exact parameters and scope of the project, using our expertise in Systems Engineering and our position as a not-for-profit “neutral player” in the Intelligent […]
The Multi-Car Collision Avoidance (MuCCA) team began a public trial this month to gather information on sensor systems that will ultimately aid the development of an advanced connected and autonomous safety system that aims to avoid or reduce multi-car, high-speed accidents on motorways. Cameras and LIDAR – housed in a roof box on a standard road vehicle driven by a human – will be used to capture video on a typical stretch of busy motorway. To avoid capture of any personal data, the focus on the video will be adjusted so that any faces captured cannot be recognised and number plates cannot be read or interpreted. Understanding typical traffic conditions on the motorway, and normal driver behaviour, is needed for the building and rigorous testing of the MuCCA system. Eventually the MuCCA system will receive information from other connected cars (while also analysing actions of non-MuCCA cars), before making a collective decision about the best course of action to avoid or reduce any collisions. It will then take control of the cars, navigating around the problem, before returning control to the driver once safe. The aim of these trials is to create a dataset to assess the performance (and limitations) of the LIDAR and object identification system, to understand the range over which vehicles in other lanes can be detected and the level of any false positives or negatives. The trial vehicle will carry out a short series of motorway trials under varying conditions, and will not have any autonomous capabilities linked to the sensor system. It is not a part of the project scope to test the MuCCA vehicles on public roads; all testing of MuCCA vehicles will be done on private testing grounds. MuCCA is a £4.6m, 30-month project supported by Innovate UK, will implement, test and refine solutions to many of the technical challenges that face fully autonomous cars. These challenges include sensor systems, machine learning, vehicle-to-vehicle communications and vehicle control systems. MuCCA is Research & Development project funded by CCAV (Centre for Connected & Autonomous Vehicles) and Innovate UK being delivered by a consortium consisting of AppIus IDIADA, Cosworth, Cranfield University, Westfield Sportscars, Secured By Design and the Connected Places Catapult. Keep up to date with the latest news at http://mucca-project.co.uk/ or follow us on twitter @muccaproject Further information The trials will occur on the M1 motorway and connecting carriageways […]
NEWS AND SOCIAL
- Is MuCCA leading the pack for collaborative, collision avoiding technology?11th April, 2019
By Stuart Rowell, Principal Technologist, Connected Places Catapult The MuCCA (Multi-Car Collision Avoidance) project has a grand aim; using connectivity and autonomy to avoid (or minimise) damage in high speed, multi-vehicle traffic accidents. Our MuCCA-equipped cars will be able to sense danger, communicate that danger amongst themselves, collectively decide on a best course of action, take control of the vehicle, and then safely hand back to the driver at the appropriate time. Best of all, this technology will recognise all vehicles, not just those MuCCA-equipped, and so supporting the gradual roll-out of connected and autonomous vehicles (CAVs). We are developing this next-generation driver aid through collaboration with world-leading industry partners. We are using advanced artificial intelligence, vehicle-to-vehicle (V2V) communications and sensor fusion to take a significant evolutionary step in automated vehicle development. But we’re not alone in looking into advanced driver aid connectivity and autonomy. With Toyota announcing their ‘Guardian’ system at CES 2019, let’s consider where MuCCA sits in the global race to deploy safe, reliable CAVs onto public roads. What makes MuCCA different? Tesla’s Autopilot system and notable German manufacturers (Mercedes’ Driving Assistance Plus, Audi’s Traffic Jam Pilot) are carrying out some exciting work when it comes to developing advanced driver assistance systems (ADAS). Other manufacturers (for example Nissan and Jaguar Land Rover) are developing similar technologies – looking at anticipation, collision-avoidance control and vehicle-to-vehicle communication. But we believe MuCCA is the only collaborative project with the ambition of bringing all of these elements together into one system. So what specific capabilities will MuCCA be developing? Anticipation of the trajectories of other vehicles ahead, alongside and behind the primary vehicle Communication with other MuCCA-equipped vehicles to communicate possible collision hazards and to receive information from other vehicles further ahead Planning of a coordinated swarm-like response for all vehicles to best avoid the hazard Execution of the necessary emergency collision-avoidance control decisions (braking, acceleration and steering) MuCCA is addressing the immediate, close proximity emergency – it will not rely on previous highway or sat nav information to be alerted to potential hazards but will be responding to real-world, high-speed incidents on our fastest roads. And once the best course of action is decided by the MuCCA system, it will brake, accelerate and steer the vehicle to protect the passengers and other road users. Evasive steering systems When it comes to the […]
- Understanding human driver behaviour9th November, 2018
By Ross Walker, Research Fellow in Autonomous Cars, Cranfield University The Multi-Car Collision Avoidance (MuCCA) Project 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). But before the MuCCA vehicles are able to react to these potentially dangerous situations, they have to understand how a human driver would react. And to do so, we need to develop a training algorithm that predicts how drivers behave when avoiding collisions. Accident prevention Drivers avoid accidents by reacting fast enough to a dangerous situation, however for multiple car collisions simply reacting may not be enough. By modelling how human drivers behave on motorways, and how the proximity of surrounding cars influence their behaviour, the movement of the cars that surround the MuCCA vehicle can be predicted over the next few seconds. This can allow any potential accidents to be recognised in advance, and consequently avoided before they have chance to begin developing. Data acquisition To predict potential accidents we first need to learn the driver trajectories that result in them. To safely obtain such trajectory data we use simulation software so that accidents can be created within a virtual (safe) environment. Tailoring scenarios to the MuCCA Project The MuCCA project deals with up to five vehicles moving along a passage of UK motorway; the prediction algorithm adopts the same parameters, and various training scenarios are devised so that meaningful human driving behaviour can be captured in the simulator. To begin, a simple test should always be carried out when initially developing an algorithm – this is to ensure results are as expected and the algorithm is behaving correctly. A simple behaviour was captured from a single vehicle having to pass by a broken down car in their lane. This was primarily to gauge if the driver’s reaction time to the blocked lane replicated a real-life scenario. The introduction of multiple cars allowed us to capture data on how well the drivers maintained motorway lane discipline. It also gave insight into how drivers undertake, lane-hog, or tailgate, which all increase the likelihood of a collision. a) Which lane will the leading HDV move to? b) How will the back HDV cope with the front HDV moving in front? c) What will the right HDV […]
- Using a Systems Engineering approach14th September, 2018
Multi-Car Collision Avoidance Project (MuCCA) is a complex, collaborative R&D project that can benefit greatly from a systems engineering approach, says Thomas Levermore, a Systems Engineer at the Transport Systems Catapult (TSC). The MuCCA project 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). This is a complex project by any definition, and by applying systems engineering methods, we can introduce technological innovation into the planning and development stages. The starting point of the systems engineering process is pulling together the requirements of the stakeholders. The MuCCA project brings together six partners, each contributing to the common goal of reducing the number and severity of multi-car collisions. However, with partners coming from academia, small, medium and large companies, each has a different approach and existing technical systems to incorporate. Before all the partners begin to develop their parts of the MuCCA system, systems engineering ensures everyone takes a step back, looks at the system as a whole in order to understand its purpose and where their elements of the system fit with others. As a systems engineering team at TSC we provide neutral guidance to the system design to balance each partners’ objectives and ensure the system meets the needs of future users. By developing an operational concept for the system, all the assumptions and constraints can be documented and a definition of what the system will (and importantly won’t) do can be agreed upon. Fostering agreement To reach an agreement on the scope of the MuCCA prototype system, use cases were developed along with the operational concept to describe situations in which the system is to intervene. These use cases were described by the approximate relative starting positions and speeds of the cars involved. Examples are two side-by-side cars avoiding a crashed vehicle, and a car avoiding a crash ahead which is partially obscured by the car in front. > From this foundation, requirements were discussed with the consortium to detail what the system is required to do so that it can achieve the objectives of the project. > With an operational concept and an initial set of requirements, the v-model process followed in this project leads to development of the system architecture. Figure 1: V-model Systems Engineering process Defining an architecture A cornerstone of any successful systems engineering process is a well-defined system architecture. At the mention of system architecture, it is common to imagine a diagram of how physical pieces of equipment fit together. Often when existing components are available to be used in a system, there is a tendency to work backwards from what is available to dictate what the functionality of the system can be, resulting in a limited system. Going straight to the physical architecture misses a vital step in the process. Taking a step back and looking at the functionality needed to satisfy the requirements allows a functional architecture to be developed […]
Find out more about our "Motorway Mobility" project, looking at a new way to use our motorways with Connected and Autonomous Technology, in this @IntelTransport article. https://t.co/E6NA53I9F5
CPC are at the @TeenTechevent in Milton Keynes today. Showcasing our Augmented Reality demonstration to 270 year 8 & 9 students. Raising aspirations & awareness of STEM careers! #teentech #STEMcareers
Our latest #MuCCA video was showcased at @AutonomousExpo where our lead partners @ApplusIDIADA had a great stand. If you missed the video check it out here: https://t.co/4XzuNQk5kA #AutonomousVehicles #AV