Although many traffic prediction models have been studied, much of the existing research considers traffic congestion primarily caused by construction and incidents. An effort to assess the impact of special events (ballgames, parades, conventions, etc.) in an urban area is needed. In this paper, a prototype model for traffic analysis under special events is proposed and tested. Unlike hydrodynamic modeling or the conventional microscopic approach by vehicle tracking, this model tries to decompose the overall system impact into the spatial effect of the special event network (SE network) and the temporal effect of the eventgenerated traffic. The model formulation is shown to possess a unique, physically meaningful solution to the underlying engineering problem. Using systemwide field data for model calibration, preliminary tests have shown encouraging results in predicting traffic impact on SE networks. Although further testing and improvement is needed, the proposed modeling approach has demonstrated its potential for extending to other applications such as disaster evacuation planning.
Vehicle turning movement data from signalized intersections is utilized for numerous applications in the field of transportation. Such applications include real-time adaptive signal control, dynamic traffic assignment, and traffic demand estimation. However, it is very time consuming and costly to obtain vehicle turning movement information manually. Previous efforts to simplify this process were focused on solving the problem using an O-D matrix, but this method proved to be inaccurate and unreliable with the existing data acquisition system. Another study involved the identification of vehicle turning movements from the detector information, but the presence of shared lanes led to uncertainties in vehicle matching, thus limiting application of the method only to intersections without shared lanes. In light of those unsuccessful attempts, this paper develops and tests a system called the Automatic Turning Movement Identification System (ATMIS), which estimates vehicle turning movements at a signalized intersection in real time, regardless of its geometry. The results from lab experiments as well as a field test show that the algorithm is very promising and may potentially be expanded for field applications.
A 3D traffic environment build platform based on UC-win/Road is developed by discussing the advantages, functional integration of software in the platform, and the construction procedures of 3D environment. The procedures includes determining overall dimensions and textures of the models by close-up photography and remote sensing images, drawing traffic signs and road markings by CorelDRAW, making model maps by Photoshop, modifying models by 3Dmax and 3D Model Conversion Tool, adding models through three approaches in UC-win/Road: configuration of models, construction of road appendages, editing road section. In this paper, the construction procedure of buildings and road signs and the 3 views building method of terrain patch are concluded, and the example of reconstructing the traffic environment of from the Tianningsi Bridge to Fuxingmen Bridge in Beijing is given to demonstrate the reliability and availability of the platform in China.
An adaptive control strategy called Piecewise Optimum Delay Estimation (PODE) was developed and tested. This paper reviews the advantages of the existing adaptive control strategies over the actuated control scheme and uses their limitations as the basis for improvement. By using real-time traffic as input, PODE dynamically searches movement combinations for phasing and timing decisions that minimize piecewise system delay. Preliminary results show that PODE can considerably and consistently reduce delay more than actuated control can. Supported by a self-adjusting procedure, PODE control logic has demonstrated its competitive strength among other adaptive control strategies, especially under congested and oversaturated conditions.
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