Public Funding for Aimsun Limited

In the last 5 years, air quality has become a key consideration for the UK government agenda, as illustrated by the increasing number of Low Emission Zones (LEZ), Ultra Low Emission Zones (ULEZ, including the first ULEZ in a mega-City in London) and even the world’s first Zero Emission Zone (Oxford, starting from 2020) and dedicated funds. This is due to the alarming evidence of local and wider implications of air quality to the health of citizens, and world climate. As transportation contributes to grow a high percentage of the total emissions, traffic management and regulations, such as the emissions-controlled zones, have the potential to significantly contribute towards a solution. Yet, this localised approach to reducing emissions may have other wider implications to near-by areas, a critical example being the SRN. For example, prohibiting or discouraging vehicles from crossing one region (such as a city centre), may disproportionally burden the strategic road network (such as a ring road) around that region with a net negative effect. A linked consideration is that as cities/regions are aiming to incentivise active travel by, for example, prioritising pedestrians over cars at traffic lights, this might have implications on the link roads. A holistic approach is needed where the impact of such local measures can be evaluated alongside their implications on the SRN. Establishing a working and scalable Proof of Concept (PoC) to deliver this vision is challenging as it involves, especially if this system is to be dynamic, responding the live situations. Suppose that an area would like to dynamically change between prioritising walkability (and healthy travel) as a Business As Usual (BaU), yet at times of high congestion would need to switch the traffic management to increase traffic flow (thus reducing congestion and enabling better use of vehicles), our solution to this problem will: • Systematise clear trigger points, based on predictions of the implication of not taking any actions • Creating measurable and actionable KPIs that can be used for the evaluation of the system at traffic control centres • Be based on real time data of both traffic and air quality (AQ data may be from on-vehicle sensors, infrastructure-imbedded sensors or satellite data) • Establish clear tactics that are appropriate to the region (divergence routes, time-to-green etc) that are based on traffic modelling of their implications, which are also evaluated • Be communicated to the drivers over the air via reliable routes, such as highways authority’s social media, broadcast radio etc. • Be communicated to the drivers via edge devices, such as traffic lights and DSRC communication.

"The VeriCAV project is developing an integrated test framework to allow Automated Driving Systems (ADSs) to be validated in simulation, exposing them to large numbers of complex driving situations such that developers and regulators can have real confidence in their reliability and safety when deployed on the roads. The project will go beyond scenario-based testing to a paradigm where optimal test cases are generated from the space of all possible situations. VeriCAV is also aiming to improve the efficiency of testing by minimising human effort necessary to supervise the huge number of tests expected. As part of this approach, a test analyser (also known as test oracle) will automate the evaluation of an ADS's performance during a test run and also aggregate information on the simulation setup in order to automatically create test coverage statistics. The project will also create realistic smart agents, representing other vehicles and pedestrians that interact with the ADS. Finally, the project will verify that the test framework performs correctly, by testing a real ADS as the system-under-test in the simulation framework, and additionally by performing physical tests with a vehicle running the same ADS to correlate performance with the simulation."

"OmniCAV will lay the foundations for the development of a comprehensive, robust and secure simulator, aimed at providing a certification tool for Connected Autonomous Vehicles (CAVs) that can be used by regulatory and accreditation bodies, insurers and manufacturers to accelerate the safe development of CAVs. It brings together a team of eleven internationally renowned organisations, with decades of accumulated knowledge in the area, in order to produce a single-point-of-call simulator to establish when a CAV can safely progress from a testbed to road trial. To achieve this, OmniCAV will use highly detailed road maps, together with a powerful combination of traffic management, accident and CCTV data, to create a high-fidelity dual (traffic and driving) simulation environment, including AI-trained road users to interact with the AV under test. Scenarios for testing will be developed and randomised in a holistic way to avoid CAVs training to specific conditions, whilst maximising coverage, and the integrity of the testing environment will be taken into consideration through creation of a root-of-trust design to secure the test inputs, simulator configuration and resulting test outputs. Critically, the simulator will offer market-leading coverage of a representative element of the UK road network, through encompassing rural roads, peri-urban and urban roads, to help enable autonomy for all. Representatives of the key end-users, including a local authority, an OEM and an insurance provider, will be engaged throughout to understand their needs. The validity of the synthetic test environment compared to the real-world is of particular importance, and OmniCAV will be tested and refined through an iterative approach involving real-world comparisons and working in conjunction with a CAV test-bed. This is an ambitious project aiming to step-change the safe trialing of CAVs in a safe, holistic and challenging manner in order to accelerate their training, deployment and adoption."

"Our vision is for the potential benefits in safety and capacity of highly automated vehicles (CAVs) to be achieved more quickly, by using data on 'real world' behaviour of human driven vehicles to define and rules for new automated ones that improve on human safety and driving capability. It may be feasible to build these from data from existing vehicles, based not just on road laws how humans drive vehicles in specific circumstances. These could be 'tuned' by modelling how CAVS and other vehicles then behave in a mixed fleet. This will help tailor early CAV behaviour to match that of human drivers, improving confidence for early adopters. We want to understand the feasibility of processing existing massive datasets, to understand the parameters needed for modelling human drivers and how to extend them to make vehicle rules, improving current technology and modelling impact to balance comfort, capacity and safety. This could ensure CAV behaviour meets needs of regulators and customers. We focus on innovatively exploring a full end to end data chain and business model in a mixed fleet environment. This integrates vehicle maker and road operator perspectives on CAV behaviour and examines how to develop privacy law compliant datasets for other CAV projects. It brings together those who develop CAV and modelling software with data from massive mixed fleets of anonymised drivers across the UK, rather than small fleets of specialised vehicles in one location. Led by CloudMade, bringing expertise in machine learning and human driver behaviour modelling, the partners include Birmingham City Council as a highway authority with legal powers and duties, TSS from road operations and Trakm8 and the AA who will provide anonymised sample data from many thousands of AA member's vehicles equipped with the innovative Car Genie device. Our key output will be identifying potential product improvements for all partners to make data, modelling and rules generate new sales. The benefits if the idea is feasible would be reduced unforeseen impacts on traffic, patents on rules for CAVS, an improved understanding of early mixed fleet operation of human and automated vehicles and how to make early level self driving vehicles attractive to users. It will help highways authoritiesand vehicle makers alike understand how to deploy CAVs on a variety of real world roads. It is a 1-year feasibility study delivering technology innovation and business change needed for exploiting the idea globally."

City councils and urban housing developers around the world need methods to remove heavy goods vehicles (HGVs) from pedestrianized city center shopping areas ("high streets"). Shops on high streets must regularly (a) receive deliveries and (b) have refuse collected, both by HGVs. Current advisory solutions include scheduling these vehicles at night, which creates nighttime noise and emissions pollution making city centers less attractive for urban living; or where such pollution is critical due to existing urban living, expensive infrastructure solutions such as designing underground tunnels for delivery. Urban living is environmentally efficient, aids regeneration and reduces the UK's housing shortage, and is important to encourage. There is a clear need for alternative urban systems to move goods and refuse to and from high streets. Our alternative is a fleet of small, electric last-mile delivery vehicles, driving on regular routes around high streets and to HGV interchange areas positions around the edges of high streets. The vehicles can be summoned to stop at shops and at parked HGVs by the retailers, to load and unload Deliveroo-sized standard boxes of goods and refuse. Unlike previous projects, they operate in dense pedestrian crowds and translate into commercial implementations newly researched algorithms for pedestrian interactions from a state-of-the-art EU research project. Unlike pure robotics projects our partners study the effects on urban planning systems and credible routes to market through existing international clients at city councils and housing developers.

The CAPRI project will design & deliver a complete, market ready, mobility service deployable in urban scenarios using trusted secure PODs and systems supported with a 'complete package' of viable business cases, legal, regulatory, insurance recommendations to enable quick and easy deployments. A series of trial deployments demonstrate increasingly complex POD-based mobility services. Whilst addresing all CCAVs priority areas, including cyber security of vehicle and data validated real-time controld systems, our focus is on innovative business models based around POD mobility services.

The project will build an autonomous vehicle with human like, natural control / path planning, by 2019, that 1) is able to be fully autonomous on country roads, when overtaking, on roundabouts and/ or motorways 2) mimics the driving behaviour of human beings, to provide an enhanced experiences for the occupants. Nissan and Hitachi will use their global automotive, artificial intelligence/ machine learning and communication technology expertise to build vehicles and AI models that are fit for purpose, and use the expertise of Horiba MIRA, Cranfield University and the University of Leeds to ensure the system is validated and end-user acceptance is evaluated. Atkins and SBD will address protective security, making the vehicle digitally and physically secure. The Transport Systems Catapult will be responsible for project management and development of safety aspects of the project. The impact of L4 vehicles on the Strategic Road Network will be explored through work by Highways England and TSS. Highways England and Milton Keynes Council will provide support to the demonstration route of the vehicle.

Connected and autonomous vehicles will play a significant role in a future transport system and unlock enormous social benefits at the same time. FLOURISH looks to enable the delivery of many of these benefits by helping to ensure that connected and autonomous vehicle are developed with the user in mind and are technically secure, trustworthy and private. Using older people and others with assisted living needs as an exemplar to develop an understanding of the diverse needs of a particular user group, FLOURISH will develop innovative products, processes and services that are directly transferrable to the wider community. FLOURISH will expand existing physical and virtual vehicle test capability and help deliver up to 10,000 jobs through the establishment of the Bristol City-Region as a world class independent test facility for connected and autonomous vehicles.