‘Connected’, ‘cooperative’, ‘smart’, ‘intelligent’ and ‘autonomous’ are labels that appear these days in numerous scientific publications and in many commercial advertisements in conjunction with up-to-date road vehicles. It comes as no surprise to anyone working in this application field as the road vehicles characterised with one or more of the above features are foci of intensive research and development (R&D) effort throughout the world. In many respect, however, the automotive industry is well beyond the R&D phase: the number of production cars on the market with the above features and the number of such cars in everyday use grows day by day.
It is difficult to judge which the most important aspect of this technological revolution-on-the-road is. It could well be the connectedness, i.e., being part of the dynamic electronic communication network of road vehicles, which is at the same time connected to the quasi-static road infrastructure. It could be the cooperative approach between the otherwise unrelated road vehicles. But it could well be the ubiquitous navigation support, or the crowdsourced real-time traffic data ‒ made available via geographical information systems ‒ that really make the difference.
Foci of the proposed research
In the frame of the project, we will look into three main aspects of the above outlined field.
- Firstly, we will investigate what an unconnected, non-navigated intelligent car can achieve on its own ‒ i.e., in a non-cooperative, standalone fashion ‒ relying solely on its own sensors. What kind of information can it work out from the data originating from its cameras, its range sensors and its more conventional sensors in respect of the road environments, junctions and road users?
- Secondly, we will look into potential uses of the automotive data connectivity.
- Thirdly, building on the above aspects, a Big Data approach is used for the purpose of vehicular complex event detection.