Abstract
Due to the rapid development of vehicular transportation and urbanization, traffic congestion has been increasing and becomes a serious problem in almost all major cities worldwide. Many instances of traffic congestion can be traced to their root causes, the so-called traffic bottlenecks, where relief of traffic congestion at bottlenecks can bring network-wide improvement. Therefore, it is important to identify the locations of bottlenecks and very often the most effective way to improve traffic flow and relieve traffic congestion is to improve traffic situations at bottlenecks. In this article, we first propose a novel definition of traffic bottleneck taking into account both the congestion level cost of a road segment itself and the contagion cost that the congestion may propagate to other road segments. Then, an algorithm is presented to identify congested road segments and construct congestion propagation graphs to model congestion propagation in urban road networks. Using the graphs, maximal spanning trees are constructed that allow an easy identification of the causal relationship between congestion at different road segments. Moreover, using Markov analysis to determine the probabilities of congestion propagation from one road segment to another road segment, we can calculate the aforementioned congestion cost and identify bottlenecks in the road network. Finally, simulation studies using SUMO confirm that traffic relief at the bottlenecks identified using the proposed technique can bring more effective network-wide improvement. Furthermore, when considering the impact of congestion propagation, the most congested road segments are not necessarily bottlenecks in the road network. The proposed approach can better capture the features of urban bottlenecks and lead to a more effective way to identify bottlenecks for traffic improvement. Experiments are further conducted using data collected from inductive loop detectors in Taipei road network and some road segments are identified as bottlenecks using the proposed method.
Highlights
T RAFFIC congestion has become a serious problem in almost all modern metropolitan cities due to increased use of vehicular transportation, urbanization and population increases
In order to identify bottlenecks in urban traffic network, we proposed a novel urban bottleneck definition, which calculates congestion costs of road segments to identify bottlenecks in urban areas taking into account both road congestion level cost and congestion contagion cost
We presented an algorithm to build maximal spanning trees in the congestion propagation graphs
Summary
T RAFFIC congestion has become a serious problem in almost all modern metropolitan cities due to increased use of vehicular transportation, urbanization and population increases. The proposed metric provides a more rigorous r way to identify traffic bottlenecks; A novel technique is proposed, based on a combined use of graphical models, maximal spanning trees and Markov analysis, to model and analyze congestion propagation in urban road networks, which presents an effective approach to quantify congestion propagation processes and congesr tion costs of all road segments in road networks; Simulations are conducted using SUMO which demonstrates that compared with those techniques in the literature only considering congestion on road segments themselves for bottleneck identification, the proposed method can capture the features of urban bottlenecks and is more effective r in identifying bottlenecks; Using the inductive loop detector data, the proposed technique is applied to identify bottlenecks in urban areas of Taipei and shows that the most congested road segments are not necessarily bottlenecks.
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