englanti

Artificial intelligence (AI) is a key technology that is utilized in autonomous systems. However, using AI in such systems introduces also several safety challenges, many of which are related to complex human-AI interactions. In general, these challenges relate to the changing roles of the people who interact with the increasingly autonomous systems in various ways. In this paper, we consider a set of practical safety challenges related to applying advanced AI to autonomous machine systems and present solutions from the perspective of human factors.

The NEXT-ITS 2 project contains a number of measures deployed on the NEXT-ITS 2 corridor and in traffic management centres in order to move from local traffic management towards coordinated and cross-border management of the whole corridor. The evaluation performed has covered the services deployed or enhanced by the road authorities involved during the period 2015-2017, also including some measures completed fully in early 2018. The objective has primarily been to evaluate the costs and impacts of the services deployed i.e.

This study was designed to investigate how many Finnish drivers with new cars have ADAS in their vehicles, and how frequently and in which context they use those systems, ACC and Lane Keeping (LKA) in particular. In addition, the impacts of these systems were to be assessed. Moreover, limitations of the current systems, willingness to have the systems in the future, and willingness to pay for such systems or higher automation levels were of interest.

The evaluation performed for NEXT-ITS2 corridor has covered the services deployed or enhanced by the Nordic road authorities during the period 2015-2017. The objective has been to evaluate the costs and impacts of the deployments. The impacts of the NEXT-ITS2 measures cover a quite large road network, about 25 000 km. The evaluation was carried out as an ex-ante evaluation.

The main aim of this study was to investigate the opinions of Finnish car drivers and experts of traffic safety and automated driving on uptake and acceptance of automated vehicles in Finland. The opinions were collected by on line surveys. Altogether 1 154 drivers participated the survey. The sample represented Finnish drivers well. Finnish drivers are quite familiar with the self driving vehicles, at least in some level. The general opinion on self driving vehicles varies quite a lot.

The NEXT-ITS 2 project contains a number of measures deployed on the NEXT-ITS 2 corridor and in traffic management centres in order to move from local traffic management towards coordinated and cross-border management of the whole corridor. The objective has primarily been to evaluate the costs and impacts of the services deployed i.e. how the measures contribute to reduction in travel time, accidents and emissions from road transport.

The goal of the L3Pilot project is to demonstrate and assess the Level 3 ADFs in real or close-to-real use contexts and environments in the pilots. However, the pilot nature of the field tests will bring some practical limitations to the possibilities of how to conduct them as described above. To receive meaningful and valid results on impacts of the ADFs, it is important to carefully consider the principles underlying the approach to collect the evaluation data.

This paper discusses use of open innovation platforms in the public transport context to create more value with shared assets and collaboration. Open innovation platforms allow businesses to develop new, better and more personalized services to citizens. The main result, the Value Ramp, is a new description of value creation of different enabling features of an innovation platform. The result is demonstrated as an added value description of the Living Lab Bus project, but the Value Ramp can be further utilized in other contexts also.

This paper explores a concept of Industrial Internet to collect and utilise data from vehicle-installed sensors for the purpose of enhanced winter road management. Data from vehicle-installed sensors extends the coverage of road condition information from fixed Road Weather Information System (RWIS) network. Vehicle-based sensors observe similar data as fixed RWIS: road surface condition and temperature, friction values, air humidity and temperature. Some vehicles have also cameras installed to produce continuous images on the road.

A carpooling application by Blox Car was piloted in the City of Espoo from Sept 2018 to Jan 2019. This paper presents pilot and survey results for the pilot and experiences of the process. The results find major events and regularly scheduled trips to be the most potential use cases. The biggest barriers for participation include lack of supply (drivers) and demand (riders) as well as the need to commit to pre-determined schedules or those of others. Main challenges for success related to exclusion of financial transactions (i.e.