Calibration of discretionary lane changing model based on close-range photogrammetry

Behavior of Lane changing often occurs in process of vehicle aggregating, evanescing, overtaking, blocking, etc. Contrast to other driving behaviors, lane changing will produce conflict points, and increase probability of collision, which impacts on traffic safety seriously. Discretionary lane changing (DLC) behavior is result of the driver's satisfactory extent when the driver goes into different lanes, and its course producing demand can be described with the Logit theory. DLC model is set up with utility selection by introducing Logit theory, and also it is calibrated by surveying data and the close-range photogrammetry principle. Finally, its validity is verified by software based on Open GL under the environment of VC. net. Simulating result shows that the model is rational.