Distributed Intelligence as Enabler for Smart Transportation
The past few years witness an increased interest within the logistic sector for automated driving. Main drivers are: (i) reducing accidents caused by human errors (ii) increasing transport system efficiency and (iii) setting the users free when automated systems are active. In the cargo world, there are various ways of implementing automated driving. Their common need is an effective control system that takes care of managing the complicated ways in which automated vehicles may interact. Here, control complexity surpasses the level that can be handled by central planning. Inevitably, planning should be organized in a distributed way.
In our presentation we illustrate the benefits of distributed intelligence for planning and controlling automated driving systems. Specifically, we pay attention to the following practical cases: (i) automated docking of trucks at a distribution center (ii) planning and control of automated guided vehicles in a container terminal and (iii) matching trucks into a truck platoon. We are looking forward to discuss and evaluate with you several intriguing choices for system specification, architectural design and detailed design.
Bio of Peter Schuur
Peter C. Schuur is Associate Professor at the School of Management and Governance at the University of Twente, The Netherlands. He received a PhD in Mathematical Physics from the University of Utrecht, The Netherlands. On the theoretical side his research interests are on: packing, covering and cutting problems, game theory, as well as the fundamentals of simulated annealing. On the applied side his research interests are on (closed loop) supply chain management, including vehicle routing, distributed planning, multi-modal networks, dynamic pricing, reverse logistics, layout problems, and warehouse modelling. He has been involved in numerous projects on improving collaboration within supply and demand chains using innovative approaches as Multi-Agent systems where he used serious gaming as a means to exemplify them.