Congestion Propagation Based Bottleneck Identification in Urban Road Networks

© 1967-2012 IEEE. 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

Token Bucket Algorithm with Modernization Techniques to Avoid Congestion in DEC Protocol of Wsn

A wireless sensor system is an essential aspect in many fields. It consists of a great deal of sensor nodes. These sensor networks carry out a number of tasks, including interaction, distribution, recognition, and power supply. Data is transmitted from source to destination and plays an important role. Congestion may occur during data transmission from one node to another and also at cluster head locations. Congestion will arise as a result of either traffic division or resource allocation. Energy will be wasted due to traffic division congestion, which causes packet loss and retransmission of removed packets. As a result, it must be simplified; hence there are a few Wireless sensor networks with various protocols that will handle Congestion Control. The Deterministic Energy Efficient Clustering (DEC) protocol, which is fully based on residual energy and the token bucket method, is being investigated as a way to increase the energy efficiency. In the event of congestion, our proposal provides a way to cope with it and solves it using this method to improve lifespan of the sensor networks. Experiments in simulation show that the proposed strategy can significantly enhance lifetime, energy, throughput, and packet loss

Primera aproximación al modelado y control de tráfico

[Resumen] España posee 17.021 km de vías de alta capacidad, autovías y autopistas, y en torno al 95% del transporte por mercancías se realiza por carretera, gran parte por este tipo de vías. Estos vehículos pesados son a menudo más lentos y menos dinámicos que los turismos, y su presencia puede modificar el discurrir del flujo del tráfico, sobre todo ante escenarios con intensidades altas y en situaciones en las que dichos vehículos se desplacen lateralmente. Esto puede producir que se resienta el nivel de servicio de la vía. La motivación del presente trabajo es estudiar la formación de colas causadas por interferencias en el tráfico en vías de alta capacidad causadas por un cambio en la sección transversal de la vía y/o por vehículos pesados y lentos, para después poder aplicar acciones de control, mitigación y prevención para evitarlas o minimizarlas. Para ello, se modelará un tramo de autopista con un ramal de incorporación y una reducción del número de carriles y se estudiará comparativamente la efectividad de dos sistemas de control del tráfico.[Abstract] Spain has 17,021 km of high-capacity roads, dual carriageways and highways, and around 95% of freight transport is carried out by road, much of it on this type of road. These heavy goods vehicles are often slower and less dynamic than passenger cars, and their presence can modify the flow of traffic, especially in scenarios with high intensity and in situations in which these vehicles move laterally. This can cause the service level of the road to suffer. The motivation of this work is to study the formation of queues caused by traffic interference on high-capacity roads, caused by a change in the cross section of the road and/or by heavy and slow vehicles, to apply control actions, mitigation, and prevention to avoid or minimize them. To do this, a highway section will be modelled with an incorporation branch and a reduction in the number of lanes and the effectiveness of two traffic control systems will be studied comparatively