Models for dynamic network loading and algorithms for traffic signal synchronization

The effectiveness of optimization strongly relies on the underlying model of the phenomenon. According to this, a considerable effort has been spent in improving the General Link Transmission Model (Gentile, 2008) to address urban networks, intersection and lane modelling and multimodal simulation. A genetic algorithm with a formulation tailored on the signal coordination problem has been integrated with the simulation engine. So, a practical and effective multi-objective optimization tool for traffic signal coordination is here presented

Models for dynamic network loading and algorithms for traffic signal synchronization

The effectiveness of optimization strongly relies on the underlying model of the phenomenon. According to this, a considerable effort has been spent in improving the General Link Transmission Model (Gentile, 2008) to address urban networks, intersection and lane modelling and multimodal simulation. A genetic algorithm with a formulation tailored on the signal coordination problem has been integrated with the simulation engine. So, a practical and effective multi-objective optimization tool for traffic signal coordination is here presented

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

Fast estimation of point-to-point travel times for real-time vehicle routing

Abstract To provide the optimal allocation of requests to the available fleet vehicles, routing algorithms typically assume the availability of complete and correct information about point-to-point travel times. Actually, in real applications non-recurrent events and traffic conditions make the estimation and the prediction of such travel times a difficult task, further complicated in real-time applications by the dynamicity of the information and the number of needed estimates. In this paper we present a complete methodology to achieve a computation of point-to-point travel times on a large network which proves to be both extremely fast and consistent with dynamically updated traffic information

Clustering methods for the automatic design of traffic zones

1.1. Motivation of this research No transport study can disregard the zoning phase, since land discretization implies a relevant approximation in the demand model and constitutes the earliest assumption in the simulation process: all the activities carried out in a traffic zone ar

TOSCA – Timing Optimization under Spillback Congestion along Arterials

Regolazione e sincronizzazione semaforica di corridoi stradali, per ottimizzare anche in presenza di code il ciclo, gli offset e i verdi lungo una sequenza di intersezioni; implementato come add-in per VISUM (PTV); registrato presso la SIAE in data 14.11.2011 con il n. 821

TRE – Traffic Realtime Equilibrium

Assegnazione dinamica (basata su splitting rates, temporal layers e gradient projection) dove le scelte di percorso e il caricamento della domanda dipendono dai tempi di percorrenza ottenuti attraverso un modello macroscopico per la simulazione del traffico sulla rete stradale; disponibile anche come VISUM Add-In; registrato presso la SIAE in data 19.03.2013 con il n. 876

Automatic Traffic Zones

Disegno automatico delle zone di traffico a partire dalle caratteristiche socioeconomiche di celle elementari (es. censuarie), per modelli trasportistici di simulazione; disponibile anche come VISUM Add-I