LAND-USES AND ACTWITY-BASED TRAFFIC FORECASTING MODEL

Abstract

Transportation plays a primary role in achieving industrial, sociological and agricultural development of a country. Among the various modes of transport that connect the cities and villages of the country, road transport constitutes the crucial link. In present scenario, as the road traffic is increasing rapidly, the accurate forecasting of traffic volume seems to be an important parameter for traffic control and transportation planning of an area. It seems to be more important in case of rural roads traffic as it contributes significantly into generating higher agricultural incomes and productive employment opportunities. A number of rural development policies, implemented by the Govt. of India, results in increase of traffic day by day from rural areas. In general, the fundamental base for the estimation of the total traffic volume of such areas is the land use pattern within and around it, the living standard or level defined by socio-economic factors pertaining to that area, population demographics, employment patterns, roads connectivity etc. In this work, 30 villages from some district of Uttrakhand and Western Uttar Pradesh were selected as study area.The data related to influencing variables that affect traffic generation was collected through random survey. Out of these 30 villages, data of 25 villages was used for the development of the traffic prediction models and remaining was used for the validation of the developed model. Regression analysis and Artificial Neural Network (ANN) were used to develop the models. Statistical measures were evaluated to examine the stability of the relationships developed and to select the best-fit models. These models can predict the traffic of a village at a given data of the significant influencing parameters and its growth rates. Finally, the models were comapared by predicting the traffic volume of years 2011 and 2015 for the same study locations.