EU-rahoitteisen AiRMOUR-hankkeen tavoitteena on tutkia ja edesauttaa uusien ilmailumuotojen käyttöönottoa kaupunkiolosuhteissa. Tästä uudesta tavasta liikkua halutaan tehdä turvallista, hiljaista ja edullista, jotta ilmakantoisten kulkuneuvojen käyttöönotto olisi mahdollisimman sujuvaa.
Automated driving is expected to improve road safety and traffic efficiency. Host vehicle onboard sensing systems typically sense the environment up to 250 m ahead of the vehicle. Today's LiDARs can see approximately 120 m, and recognition of small objects, such as animals or dropped cargo, however, today reliably drop when range is more than 50m. Connected driving adds an electronic horizon to the onboard sensing system which could extend the sensing range and greatly improves the efficiency.
Light detection and ranging sensors (LiDARS) are the most promising devices for range sensing in automated cars and therefore, have been under intensive development for the last five years. Even though various types of resolutions and scanning principles have been proposed, adverse weather conditions are still challenging for optical sensing principles. This paper investigates proposed methods in the literature and adopts a common validation method to perform both indoor and outdoor tests to examine how fog and snow affect performances of different LiDARs.
5G-DRIVE will trial and validate the interoperability between EU & China 5G networks operating at 3.5 GHz bands for enhanced Mobile Broadband (eMBB) and 3.5 & 5.9 GHz bands for V2X scenarios. The key objectives are to boost 5G harmonisation & R&I cooperation between EU & China through strong connected trials & research activities, with a committed mutual support from the China “5G Product R&D Large-scale Trial” project led by China Mobile.
Enabling of performance, industry and humanity by AI for digitising industry is the key to push the AI revolution in Europe and step into the digital age. Existing services providing state of the art machine learning (ML) and artificial intelligence solutions are currently available in the cloud. In this project, we aim to transfer machine learning and AI from the cloud to the edge in manufacturing, mobility and robotics.
The mission of ARCADE is to coordinate consensus-building across stakeholders for sound and harmonised deployment of Connected, Cooperative and Automated Driving (CAD) in Europe and beyond. ARCADE supports the commitment of the European Commission, the European Member States and the industry to develop a common approach to development, testing, validation and deployment of CAD in Europe and beyond.
The main objective of NordicWay2 is to deploy studies with pilot activities in order to further develop interoperable Day-1 and Day 1.5 C-ITS services utilizing cellular network. It also supports infrastructure readiness for connected and automate driving in Denmark, Finland, Norway and Sweden.
The TransformingTransport project demonstrated, in a realistic, measurable, and replicable way the transformations that Big Data will bring to the mobility and logistics market. To this end, TransformingTransport, validated the technical and economic viability of Big Data to reshape transport processes and services to significantly increase operational efficiency, deliver improved customer experience, and foster new business models.
The European research project L3Pilot tests the viability of automated driving as a safe and efficient means of transportation on public roads. It will focus on large-scale piloting of SAE Level 3 functions, with additional assessment of some Level 4 functions. The functionality of the systems will be exposed to variable conditions with 1,000 drivers and 100 cars across ten European countries, including cross-border routes.
Over the past few years, one person has been killed and close to one seriously injured every day on level crossings in Europe. Therefore, The EU project SAFER-LC (Safer level crossing by integrating and optimizing road-rail infrastructure management and design) aims to improve safety and minimize risk by developing a fully integrated cross-modal set of innovative solutions and tools for the proactive management and design of level-crossing infrastructure.
Main objectives: