A New Approach for Urban Resident Trip-Mode Share Rate Forecasting

The urban resident trip-mode share rate is a significant index of urban transportation pattern and its development level. It is one of the important issues in urban transportation study to forecast the urban resident trip-mode share rate effectively so as to determine whether the present urban transportation structure is reasonable. This paper produces an improved Grey-Markov Chain method by combining Grey Model and Markov Chain, and based on this method, establishes the urban resident trip- mode share rate forecasting model exploringly. Firstly, to forecast the urban resident trip-mode share rate by Grey Model, then to revise the prediction by Markov Chain to obtain a more accurate result. This paper takes the private car trip-mode share rate in Nanjing as an example to illuminate the model's application for forecasting the trip-mode share rate. The result proves that the improved Grey-Markov Chain Method is more reliable and effective.