Efficient optimization methods for freeway management and control

Abstract

Due to the rapid growth of human population, and jobs being distributed unevenly in different locations, daily commuting is required more than ever, which in its turn is creating a huge socio-economic issue: traffic congestion. In order to prevent, or at least to alleviate this problem, trafficmanagement and control is urgently required. This thesis develops three different management and control methods to improve the performance of traffic networks, with a particular focus on freeway networks, namely • ant colony optimization for dynamic traffic routing; • co-design of network topology and controlmeasures; • path planning of unmanned aerial vehicles for monitoring traffic networks. Usually, solving these problems for a large-scale freeway network will result in an extremely high computational burden. The main contribution of this thesis consists in the development of solution methods for these problems to solve them efficiently with a well-balanced trade-off between performance and computation speed.