ABSTRACT
Nowadays transportation represents an important field for CPS applications due to the rapid development of highly automated or autonomous vehicles, e.g. warehouse vehicles, airport people movers, public transport, etc. These vehicles are usually designed to circulate on fixed routes independently of the actual state of the network in order to fulfil a given criterion, such as traveling on the shortest path or including scheduled stops. This paper introduces a routing approach that allows automated vehicles to travel on different paths between given points, minimising the generalised cost of the route. Between fixed points, which can be either different storage points in a warehouse or simply public transport stops, possible routes are modelled as a continuously updated weighted directed graph. The weights represent relevant parameters of links, collected from surrounding sensors and monitoring systems of the network. Route optimisation is done by Yen’s algorithm depending on the timetable: if the vehicle will reach the next stop on time, the alternative with the lowest generalised cost is chosen; else the fastest route is followed. The method is introduced specifically via the problem of traffic congestion on public transport paths, but can be generalised, e.g. any transport system within factories or warehouses.
Acknowledgements
The research reported in this paper was supported by the Higher Education Excellence Program of the Ministry of Human Capacities in the frame of Artificial Intelligence research area of Budapest University of Technology and Economics (BME FIKPMI/FM), and by the Hungarian Government and co-financed by the European Social Fund through the project ‘Talent management in autonomous vehicle control technologies’ (EFOP-3.6.3-VEKOP-16-2017-00001), as well as by János Bolyai Research Scholarship of the Hungarian Academy of Sciences.
Disclosure statement
No potential conflict of interest was reported by the authors.