Fixed unit extension was adopted in the traditional way of actuated control, that is, waiting intervals for following vehicles remain the same. The method did not consider vehicle flow arrival rules and drivers' psychological featrues. Aiming to solve the above problems in the traditional actuated control, the paper establishes the model of changeable unit extension, and use actual data to validate its feasibility and superiority by simulation. The results obtained have the important theoretical significance and practical value for the urban traffic control (UTC).

In China vehicle conversion factors are usually obtained from vehicle type classification. This commonly used method results in problems in traffic control. By studying the different impacts of standard and non-standard vehicles with various lengths on the headways of standard vehicles, a conversion factor measurement model in terms of vehicle length is established. Through traffic surveys at typical intersections during peak periods, the headway of a standard vehicle following a standard vehicle, a standard vehicle following a non-standard vehicle, or a non-standard vehicle following a standard vehicle, as well as the length of a non-standard vehicle, have been calibrated. Therefore, the parameters in the model are calibrated by using the data obtained in the mentioned surveys. As a result, in accordance with the vehicle length, the vehicle conversion factor, which is applicable in traffic control, is determined.

In terms of the similarity between a road network and a circuit network, this paper demonstrates that Kirchhoff's current and voltage laws observed in the circuit can be employed in the traffic assignment of the road network. Inspired by the more consummate circuit theory, we put forward a new idea and method of traffic assignment. A set of models is formularized by means of multiobjective nonlinear planning theory, and the solutions are found using MATLAB. An example is provided to prove the feasibility of the new traffic assignment model.

Car-following models describe how one vehicle follows the preceding vehicles. In order to better model and explain car-following dynamics, this paper categorizes the state of a traveling vehicle into three sub-processes: the starting (acceleration) process, the car-following process, and the stopping (deceleration) process. The starting process primarily involves vehicle acceleration behavior. The stopping process in volves not only car-following behavior but also deceleration behavior. This paper regards both the stopping process and the starting process as spring systems. The car-following dynamics during the starting process and the stopping process is modeled in this paper. The parameters of the proposed models, which are represented in the form of trigonometric functions, possess explicit physical meaning and definitive ranges. We have calibrated the model of the starting process using data from the Traffic Engineering Handbook, and obtained reasonable results. Compared with traditional stimulus-response car-following models, this model can better explain traffic flow phenomena and driver behavior theory.

为了揭示基于收入的居民出行分布规律，本文以模拟电子云居民出行分布模型为基础，将电子能级理论引入到出行分布理论当中，建立了居民出行分布模型。该模型用以描述居民收入与出行分布之间的关系，并通过美国NPTS的调查数据对此模型进行了验证。