Congestion Warning Research Articles

Attribution-related causes of a difficult doctor-patient relationship

Network-wide traffic control strategies (e.g. perimeter control and route guidance) in urban networks have recently been mainly studied to relieve or postpone congestion based on the theory of macroscopic fundamental diagram (MFD). Nevertheless, these studies are mostly applied to the statically partitioned networks or the dynamic networks that fail to fully consider traffic state prediction, conflicting with strongly spatiotemporal variability of traffic congestion or objective of active traffic management (ATM). This paper proposes a methodology to dynamically identify critical congestion warning areas from heterogeneous urban road networks, which aids to design efficient perimeter control approaches. In the methodology, a dynamic directed weighted network is built on the base of the link connectivity and the real-time traffic loads, and a link travel time prediction method based on Kalman filter is developed to calibrate directed weight values and undirected input values for links. With the undirected link input information, a dynamic congestion warning community detection method which consists of three consecutive steps is developed. Firstly, it could capture emergence of new congestion areas based on the definition of congestion seed intersection. Secondly, expansion and regression of each congested area could be achieved with the objectives of spatial compactness and traffic condition homogeneity. Thirdly, a two-level merging algorithm of adjacent different congestion areas is designed utilizing modularity model in community detection of complex networks. The proposed methodology is validated using ground truth data from downtown network of Jinan City in China. The results show that the proposed algorithms can efficiently track congestion evolutionary processes and effectively detect congestion warning areas from the test real network.

Function, equipment, and field testing of a route guidance and information system for drivers (ALI)

Traffic flow has already been improved in the German autobahn network by guidance systems utilizing data collection and calculating forecasts. Some examples of this are the remote-controlled traffic signs in the autobahn network Rhein-Main, the congestion warning system on the Aichelherg, and the lane-controlling system of the Frankfurt-Cologne autobahn. An improvement of the prediction accuracy can be expected if the destinations of the vehicles are known. This is the basic idea of the interactive ALI system (guidance and information system for drivers). After indicating his destination, the driver receives individual information about how to reach the destination in the shortest and easiest way. By knowing the destination, the system can improve its prediction ability. At this time, such a system of approximately 100 km in length is being prepared on an autobahn network in the Ruhr area; it is being financially supported by the Federal Ministry of Research and Technology, the Federal Minister of Transport, and several participating authorities of Northrhein-Westfalia. At 83 cross sections all vehicles will he counted and data will be exchanged with the ALI vehicles. This enables one to receive automatic directional information for 32 autobahn exits. For testing purposes, 400 vehicles will he fitted with ALI units. After considering the current traffic situation, the central computer can arrive at a forecast for this partial stretch of the network. For example, if there is a threat of congestion, the computer can modify its program for directional information in the cross sections, thereby informing ALI vehicles as to traveling time, operating costs of the vehicles, as well as the danger of congestion, and the detour route. Large-scale testing began in mid-1979, accompanied by a series of tests. The effectiveness of the system, an analysis of cost-benefit, and the effect upon driver acceptance will he determined. The evaluation of the large-scale testing will he available by mid-1981. This project is being carried out by Blaupunkt-Werke, the consulting engineers Heusch/Boesefeldt, and the Voikswagenwerke A.G. It is supervised by the Technical Inspection Bureau (TÜV), Rheinland.