Machine Sensible Infrastructure under Nordic Conditions

The vehicle industry and software and hardware providers are rapidly developing sensor systems and artificial intelligence (AI) methods for sensing the road environment. Connected and Automated Vehicles (CAVs) are argued to have a large potential for increasing traffic safety and efficiency. There is a strong need for more open scientific studies publishing AI software and results on CAV technology which give valuable insight to road authorities, information which is not available from the vehicle industry today. In addition, in Nordic countries more scientific studies on the limitations of these technologies caused by Nordic conditions is needed, and exploring how these limitations may set other requirements for road design and winter maintenance. In this project we utilize our own research platform for automated driving, and data from instrumented vehicles to gain knowledge on how to establish a machine sensible road environment in the Nordic region and explore how standards for road design and maintenance should be adjusted in this regard. The proprietary nature of vehicle technologies makes a research platform for automated driving particularly important for gaining scientific knowledge on how these systems work on existing infrastructure and in real traffic. MCSINC will use pilot activities as the backbone of the project, and aim at solving technological and non-technological challenges simultaneously. The non-technological challenges include development of governance, regulations, policies, standards and business models. Solving these challenges requires a coupling between the traditional fields of human factors, road planning and design and the field of computer science. Hence, this project will couple data collections from stakeholder interviews and workshops with technical data and analyses from vehicle sensors.

The vehicle industry and software and hardware providers are rapidly developing sensor systems and artificial intelligence (AI) methods for sensing the road environment. Connected and Automated Vehicles (CAVs) are argued to have a large potential for accelerating traffic safety and efficiency. There is a strong need for more open scientific studies publishing AI software and results on CAV technology which give valuable insight to road authorities, information which is not available from the vehicle industry today. In addition, in Nordic countries more scientific studies on the limitations of these technologies caused by Nordic conditions is needed, and exploring how these limitations may set other requirements for road design and winter maintenance We utilize our own research platform for automated driving, i.e. a vehicle with automated driving capabilities, and data from instrumented vehicles to gain knowledge on how to establish a machine sensible road environment in the Nordic region and explore how standards for road design and maintenance should be adjusted in this regard. The proprietary nature of vehicle technologies makes a research platform for automated driving particularly important for gaining scientific knowledge on how these systems work on existing infrastructure and in real traffic. We use pilot activities as the backbone of the project, and aim at solving technological and non-technological challenges simultaneously. The non-technological challenges include development of governance, regulations, policies, standards and business models. Solving these challenges requires a coupling between the traditional fields of human factors, road planning and design and the field of computer science.