A Hybrid Approach to Process Planning: The Urban Traffic Controller Example
Jimoh Falilat Olaitan, Simon Parkinson and Thomas Leo McCluskey
DOI : 10.3844/jcssp.2017.257.274
Journal of Computer Science
Volume 13, Issue 8
Automated planning and scheduling are increasingly utilised in solving evsery day planning task. Planning in domains with continuous numeric changes present certain limitations and tremendous challenges to advanced planning algorithms. There are many pertinent examples to the engineering community; however, a case study is provided through the urban traffic controller domain. This paper introduce a novel hybrid approach to state-space planning systems involving a continuous process which can be utilised in several applications. We explore Model Predictive Control (MPC) and explain how it can be introduce into planning with domains containing mixed discrete and continuous state variables. This preserves the numerous benefits of AI Planning approach by the use of explicit reasoning and declarative modelling. It also leverages on the capability of MPC to manage numeric computation and control of continuous processes. The hybrid approach was tested on an urban traffic control network to ascertain it practicability on a continuous domain; the results show its potential to control and optimise heavy volumes of traffic.
© 2017 Jimoh Falilat Olaitan, Simon Parkinson and Thomas Leo McCluskey. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.