Complexity Measure Of Macroscopical & Microcosmic Transportation Systems And It's Application To Management & Control

The precondition realizing efficient management and control is to get to know the object of management and control, scientifically, correctly. The assumption that the traffic transportation system is a linear, constant system has been overthrown by recent research and the facts that the traffic transport system is complex, nonlinear system are extensively accepted by academe. The quantitative depiction research on complexity, non-linearity of transportation system gradually becomes hotspot research field. Presently, the difficulties in researches are following listed: depicting theory is shortage of systemic basic theory and rounded depicting procedure. Depicting objects need a mass of data. Depicting methods could not realize comparable measurement. The cognition of complexity of traffic transportation system still rests on lower level and how to manage and control traffic transportation system against complexity characteristics is still blank. On basis of these facts, the following researches deepen depicting research of traffic transportation system complexity: choosing and mending comparable measurement under condition of short series, quantitatively researching and analyzing complexity of traffic transportation system, combining complexity measurement with management and control of traffic transportation system. Academic and realistic meaning is obvious for these studies.The key points and main achievements in paper are listed as follows:1.By virtue of analyzing sixteen series (or arrays) of traffic flow in city and six series of traffic flow in highway, the test, choice, improvement of complexity measurement methods and the complexity measurement of traffic flow system are realized. Moreover, the difficulties in short series, compares of traditional depiction methods are solved through reviewing the relations among complexity, chaos, fractal. Finally, some useful conclusions are drawn.2. Based on predicting methods, such as, ARIMA model, RBF neural networks, chaos local prediction of nonparametric estimation, the correlativity between traffic flow complexity and predictability and the complexity applying condition of different prediction methods are discussed. Moreover, the simple applying project of complexity in traffic control are put forward by emulate test to study complexity appliance in traffic control.3. Improved Lempel-Ziv algorithm, which could measure the complexity of super-short series, is put forward. The measures of macro-traffic transportation systems in China and Japan are realized. The conclusions that macro-traffic transportation system approximately is linear system, etc. are drawn.4. The following researches are carried out, i.e. complexity and predictability of macro-traffic transportation system, correlativity between complexity of macro-traffic transportation system and complexity of GDP.5. The construction of theory frame of system complexity measure has been finished. Starting with phenomenology and intentional science, intentional structure model is put forward and it is clear that system complexity measure is a two-step intention explanation process. The mathematics basis and condition of complexity measure are confirmed according to measure theory. General procedure of complexity measure is brought forward.