Autonomous vehicle control systems for safe crossroads

This article presents a cooperative manoeuvre among three dual mode cars – vehicles equipped with sensors and actuators, and that can be driven either manually or autonomously. One vehicle is driven autonomously and the other two are driven manually. The main objective is to test two decision algorithms for priority conflict resolution at intersections so that a vehicle autonomously driven can take their own decision about crossing an intersection mingling with manually driven cars without the need for infrastructure modifications. To do this, the system needs the position, speeds, and turning intentions of the rest of the cars involved in the manoeuvre. This information is acquired via communications, but other methods are also viable, such as artificial vision. The idea of the experiments was to adjust the speed of the manually driven vehicles to force a situation where all three vehicles arrive at an intersection at the same time

Status of the Horizon 2020 EuPRAXIA conceptual design study

The Horizon 2020 project EuPRAXIA (European Plasma Research Accelerator with eXcellence In Applications) is producing a conceptual design report for a highly compact and cost-effective European facility with multi-GeV electron beams accelerated using plasmas. EuPRAXIA will be set up as a distributed Open Innovation platform with two construction sites, one with a focus on beam-driven plasma acceleration (PWFA) and another site with a focus on laser-driven plasma acceleration (LWFA). User areas at both sites will provide access to free-electron laser pilot experiments, positron generation and acceleration, compact radiation sources, and test beams for high-energy physics detector development. Support centres in four different countries will complement the pan-European implementation of this infrastructure

Test exploration and validation using transaction level models

The complexity of the test infrastructure and test strategies in systems-on-chip approaches the complexity of the functional design space. This paper presents test design space exploration and validation of test strategies and schedules using transaction level models (TLMs). Since many aspects of testing involve the transfer of a significant amount of test stimuli and responses, the communication-centric view of TLMs suits this purpose exceptionally wel

Status of the Horizon 2020 EuPRAXIA conceptual design study

The Horizon 2020 project EuPRAXIA (European Plasma Research Accelerator with eXcellence In Applications) is producing a conceptual design report for a highly compact and cost-effective European facility with multi-GeV electron beams accelerated using plasmas. EuPRAXIA will be set up as a distributed Open Innovation platform with two construction sites, one with a focus on beam-driven plasma acceleration (PWFA) and another site with a focus on laser-driven plasma acceleration (LWFA). User areas at both sites will provide access to free-electron laser pilot experiments, positron generation and acceleration, compact radiation sources, and test beams for high-energy physics detector development. Support centres in four different countries will complement the pan-European implementation of this infrastructure

A fourfold typology of living labs: an empirical investigation amongst the ENoLL community

Living Labs can be seen as a means to structure user involvement in innovation processes. However, in this rather young research domain, there is no consensus yet regarding supporting theories and frameworks. This has resulted in a wide variety of projects and approaches being called ‘Living Labs’, which leaves a clear conceptualization and definition a task in progress. Within this research paper we propose a fourfold categorization of Living Labs based on a literature review and validated by an empirical investigation of the characteristics of 64 ICT Living Labs from the European Network of Living Labs (ENoLL). The four types are Living Labs for collaboration and knowledge support activities, original ‘American’ Living Labs, Living Labs as extension to testbeds and Living Labs that support context research and co-creation with users

PuLSE-I: Deriving instances from a product line infrastructure

Reusing assets during application engineering promises to improve the efficiency of systems development. However, in order to benefit from reusable assets, application engineering processes must incorporate when and how to use the reusable assets during single system development. However, when and how to use a reusable asset depends on what types of reusable assets have been created.Product line engineering approaches produce a reusable infrastructure for a set of products. In this paper, we present the application engineering process associated with the PuLSE product line software engineering method - PuLSE-I. PuLSE-I details how single systems can be built efficiently from the reusable product line infrastructure built during the other PuLSE activities

An Agent-based Modelling Framework for Driving Policy Learning in Connected and Autonomous Vehicles

Due to the complexity of the natural world, a programmer cannot foresee all possible situations, a connected and autonomous vehicle (CAV) will face during its operation, and hence, CAVs will need to learn to make decisions autonomously. Due to the sensing of its surroundings and information exchanged with other vehicles and road infrastructure, a CAV will have access to large amounts of useful data. While different control algorithms have been proposed for CAVs, the benefits brought about by connectedness of autonomous vehicles to other vehicles and to the infrastructure, and its implications on policy learning has not been investigated in literature. This paper investigates a data driven driving policy learning framework through an agent-based modelling approaches. The contributions of the paper are two-fold. A dynamic programming framework is proposed for in-vehicle policy learning with and without connectivity to neighboring vehicles. The simulation results indicate that while a CAV can learn to make autonomous decisions, vehicle-to-vehicle (V2V) communication of information improves this capability. Furthermore, to overcome the limitations of sensing in a CAV, the paper proposes a novel concept for infrastructure-led policy learning and communication with autonomous vehicles. In infrastructure-led policy learning, road-side infrastructure senses and captures successful vehicle maneuvers and learns an optimal policy from those temporal sequences, and when a vehicle approaches the road-side unit, the policy is communicated to the CAV. Deep-imitation learning methodology is proposed to develop such an infrastructure-led policy learning framework