A novel method for travel system patterns

Due to population growth in urban areas, especially in the capital cities in developing countries, the use of private vehicles are increasing, leading to many problems such as congestion, pollution, noise, long travel time, high travel cost and more side effects. In such circumstances government policy would encourage people to use public transportation. In the meantime, employing the Intelligent Transport System consisting of two parts including private sector and public sector by predicting the dynamic travel time, can help the travelers to be aware of the latest traffic information. To achieve this objective, the calculation of traffic flow, demand of passenger and transport means availability are vital. The double constraint gravity model is a crucial methodology for predicting the origin destination matrix. This paper represents a Travel System Pattern (TSP) based on proposed methodology. TSP tries to let the travellers and authority know about the best travel route with considering the shortest dynamic travel time information. For this purpose the travellers are able to be aware of the travel time and other details of travel route via the internet or SMS system. Hence, a case study based on an actual public and private network in Kuala Lumpur, Malaysia is chosen as a case study area. The result shows that the accuracy of the proposed method indicated reasonable R2 of 0.926 for the evening rush traffic period. This indicates that the TSP developed in the present study is a reliable and suitable tool to guide the travellers and companies.