Abstract
Reactive and predictive routing algorithms have to work fast and reliably for a large number of traffic participants. Therefore, simple rules and thresholds guide the routing decisions rather than extensive data collection and machine learning. In this paper, we optimise some of the thresholds governing the behaviour of a reactive and predictive routing algorithm by using the microscopic traffic simulator TraffSim. Microscopic traffic simulation is more exact than its macroscopic counterpart and very well suited to test the efficiency of a reactive and predictive routing algorithm. Unfortunately, it is also tremendously more computationally expensive, impairing the applicability of 'conventional' heuristic optimisation techniques like genetic algorithms or evolution strategies. Extensive use of surrogate models in an optimisation procedure is a promising alternative. Several variations of the efficient global optimisation (EGO) algorithm are tested and compared. Furthermore, a new type of surrogate model geared towards the parameter optimisation is presented.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Simulation and Process Modelling
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
