Synchronization of traffic signals through a heuristic-modified genetic algorithm with GLTM

Urban signal timing is a non-convex NLP problem. Finding an optimal solution on not very small and simple networks may take long time, wherever possible. The present paper focuses on signal synchronization, thus creating fast-flow corridors on one or more network road arterials. To do this, a genetic-like algorithm is applied, in which new solutions generation follows heuristic conceptions. This can be carried out thanks to the specific formulation adopted, suitable for synchronization problems. The objective function is evaluated by the General Link Transmission Model, a very fast macroscopic dynamic simulator referring to the kinematic waves theory. Through this, queues dynamic evolution, spillback phenomenon and vehicles travel times are explicitly taken into account. Key-words: traffic control, signal setting, synchronization, optimization, genetic algorithm, general link transmission model

Precision packet-based frequency transfer based on oversampling

Frequency synchronization of a distributed measurement system requires the transfer of an accurate frequency reference to all nodes. The use of a general-purpose packet-based network for this aim is analyzed in this paper, where oversampling is considered as a means to counter the effects of packet delay variation on time accuracy. A comprehensive analysis that includes the stability of the local clock is presented and shows that frequency transfer through a packet network of this kind is feasible, with an accuracy level that can be of interest to a number of distributed measurement applications