Determination of the critical congestion point in urban traffic networks: A case study

At present, most of the attempts to quantify urban traffic flow have completely ignored its predominant social footprint, while literature concerning the appearance and forecasting of congestion points remains scarce. This paper presents a methodology for determining the critical point leading to congestion in urban traffic, based on analyzing the network topology and flow using an innovative mixture of complex network metrics and state of the art traffic simulation. To validate the concepts and methodology we conducted a case study over the city of Timisoara. At around 0.5 million inhabitants we believe it provides, which provides a suitable benchmark for deriving empirical, results and qualitative interpretations.

I. Introduction and Background

THE urban road networks are growing ever increasingly busy and traffic-jams have become a day-to-day practice for most commuters, while coping with the increasing and dynamic changing of traffic conditions in large cities remains largely an unsolved problem. In Copenhagen alone, traffic values have increased with over 50% since the 1980s; furthermore, in 2012 people were spending over 100,000 hours in queues, corresponding to an economic loss of more than 750 million Euros [1]. It is clear these issues require addressing quickly if the road network is to avoid collapse in the near future. Improving the efficiency over road networks can be done by re-designing the network. However, construction of new roads or expanding existing ones is hampered by restrictive European legislation, that enforces new rules concerning air and noise pollution [1]. A second, preferred approach is to optimize traffic flow.