Guiyan Jiang

Automatic traffic congestion identification method of expressway based on gain amplifier theory

This paper proposes a method for application in automatic traffic congestion identification method (ACI) using gain amplifier theory. The road segment dividing method is given in this paper, and the ACI method of road lean, road cross-section and natural road segment are proposed to identify the traffic state of expressway. The performance of ACI method is evaluated using real and simulation data. The experimental results indicate that the proposed ACI method of lean produced satisfactory DR with deemed acceptable FAR using traffic data of three time scales. The ACI method of natural road segment is suit for estimating the traffic state of natural road segment.

Automated incident detection algorithms for urban expressway

In order to improve the efficiency of traffic management system, reduce the losses caused by traffic incidents, an algorithm for application in urban expressway incident detection is proposed based on the change trend of traffic parameters using gain methodology. The traffic data for research were obtained from a real section of urban expressway. It contains volume, speed and occupancy. The time scale of data is 20s, 1min and 5min. The performance of automatic incident detection (AID) algorithms was evaluated based on detection rate, false alarm rate, mean time difference between different algorithms, mean time difference between different times scale, robustness. The detection performance of the proposed algorithm was compared to California algorithm which has been adequately proven in practical applications. The experimental results indicate that the proposed algorithm is competitive with California algorithm using traffic data of three time scales, and the robustness of the proposed algorithm is very satisfactory.

Key nodes and corridors identifying method for large-scale evacuation network based on information centrality

Large-scale natural or man-made disasters have the potential to cause great loss of life, human injury and extreme property damage. Evacuation from areas at risk is often one of the most feasible strategies that can be undertaken in response to these types of disasters. Evacuating a large population in the shortest possible time is an extremely complicated and difficult task, which primarily relies on efficient method of traffic planning for emergency evacuation. This paper puts forward a novel method of identifying key nodes and corridors for emergency evacuation based on information centrality, the characteristic of which integrates a method of identifying the efficient nodes and the critical connectivity nodes for evacuation, and a method of identifying the key evacuation corridors. In addition, the approach of connectivity key nodes has been proposed. The experiment results show that the proposed method has rationality and feasibility.

Traffic organization method for emergency evacuation based on information centrality

Large-scale natural or man-made disasters have the potential to cause great loss of life, human injury and extreme property damage. Evacuation from areas at risk is often one of the most feasible strategies that can be undertaken in response to these types of disasters. Evacuating a large population in the shortest possible time is an extremely complicated and difficult task, which primarily relies on efficient method of traffic organization for emergency evacuation corridors. This paper, on the foundation of efficiency and contingency, puts forward a novel method of emergency evacuation traffic organization using information centrality of complex network theory, the characteristic of which integrates a method of emergency evacuation corridors optimization and traffic organization method of emergency evacuation corridors. In addition, the efficiency function in information centrality has been improved. The experiment results show that the proposed method has rationality and feasibility.

Travel Path Guidance Method for Motor Vehicle

Along with the fast rise in number of motor vehicles, traffic congestions are more and more serious. Traffic congestions cause travel time wasting, traffic accident, environmental pollution, vehicles damage and so on. In order to alleviate traffic congestions deteriorating, a travel path guidance method for motor vehicle based on intelligent materials was designed using traffic simulation technologies, considering two common traffic information release systems, whose names are variable message sign and in vehicle navigation system, which will help doing better to make full use of basic traffic information. Then, the method was verified using VISSIM simulation software. The results show that the traffic congestions of experimental network are relieved obviously by the travel path guidance method in this paper.

Traffic Adaptive Control Framework for Real Time Large-Scale Emergency Evacuation

Large-scale natural or man-made disasters have the potential to cause great loss of life, human injury and extreme property damage. Evacuation from areas at risk is often one of the most feasible strategies that can be undertaken in response to these types of disasters. Evacuating a large population in the shortest possible time is an extremely complicated and difficult task, which urgently needs to look for ways to control the evacuation traffic flow efficiently and effectively in real-time. This paper, on the foundation of adaptive control theory, puts forward a traffic adaptive control framework for real time large-scale emergency evacuation, the characteristic of which integrates a method of prescriptive reference model and the adaptive control system. The prescriptive reference model is applied to specify, in a short-term and rolling-horizon manner, the desired traffic states, which serves as a reference point for the adaptive control. And the adaptive control system combines these desired states and the current prevailing traffic conditions collected by the sensing system to produce real time traffic control schemes. These traffic control schemes are implemented in the field to guide the real world traffic flow to evolve towards the desired states.

Link Average Speed of Traffic Flow Estimation Method Based on Floating Car

In floating car data collection, the link average speed of floating cars is exported as link average speed of traffic flow. This results in low quality traffic information being shared with the public. This paper investigates the quantitative relationship between link average speed of floating cars and link average speed of traffic flow considering the traffic conditions, and verifies the research with simulated data based on a part road network in Changchun. The results show that the link average speed of floating cars can not be used instead of the link average speed of traffic flow, and that the link average speed of traffic flow can be estimated accurately using the method described in this paper. INTRODUCTION Link average speed is regarded as an effective traffic parameter for measuring the degree of traffic congestion. Floating car data collection has become one of the main means for collecting link average speed (Jiang G., 2004). In typical case, a single vehicle type (taxi, bus, logistics vehicle etc.) is selected as the floating car in order to reduce system costs (Turner S.M., 1998). However, the structure of vehicle type in traffic flow is very complex, and the running characteristics of different types on road are distinctive. Therefore, the Link Average Speed of Floating Cars (LASFC) cannot usually be substituted for the Link Average Speed of Traffic Flow (LASTF). Currently, research on floating car-based traffic information collection technology focuses on traffic data estimation methods based on individual floating car, and the average traffic data of floating cars is directly exported to users (Quiroga, C.A., 1997, Young-Ji, B., 2005 and Dong, J., 2006). The relationship between traffic data for floating cars and traffic flow is infrequently discussed. ICCTP 2009: Critical Issues in Transportation Systems Planning, Development, and Management ©2009 ASCE 1631