The traffic characters and conflicts are analyzed on the basis of including features of various kinds of traffic modes for the technological development zone. The investigation results reflects that travel time concentrated distribution and commuting is the mainly travel purpose. The proportion of slow traffic is more than 50% in the peak hours. The conflicts to the slow traffic mainly caused by public traffic and motor vehicle. Ignoring the slow traffic management, the lack of public participation and citizens do not satisfied the slow traffic environment and are the main problems for the slow system of technological development zone. Additionally, the strategies and contents of planning and design for slow traffic are suggested, which have good practical significance.

According to the traffic conditions in the typical freeway tunnel group in China, an artificial neural network model is constructed for the purpose of predicting the operating speed in freeway tunnel group in this paper. In this model, some input variables are selected from four aspects, including time factors, traffic dynamic factors, road conditions and tunnel environment, and the output variable is the operating speed. Then the sensitivity analysis method is selected to study the effects of input variables on output variable. The results show that this algorithm can avoid the difficulty of constructing traffic flow model comparing to the traditional algorithm, and it is suitable to realize online modeling for speed limit of freeway tunnel group. Results of this research are practical and effective, and it may provide a theoretical foundation for speed limit of freeway tunnel group.