Activity-based travel demand models to evaluate transport policies

Abstract

Transportation planning plays a critical role in shaping the economic health and quality of life of the general public. A good deal of the demand for transport is concentrated on a few hours of a day, at particular section of urban areas where congestion takes place during specific peak periods. Hence, modelling of this travel demand from the transportation point of view is necessary. There are two basic approaches to this travel demand modelling—traditional four-stage travel demand modelling and activity-based travel demand modelling. According to transport department data of Bangalore city collected in 2012, there are 41.86 lakh of two-wheelers, 11.8 lakh of cars and 5.91 lakh of transport vehicles. The share is 69% of two-wheelers, 22% of LMVs, 5% of HTVs and 4% of other vehicles. From the earlier research, it has been found that the activity-based modelling is more efficient to evaluate the transport policies than traditional four-step modelling particularly for the cities like Bangalore having a large amount of vehicle population. Here, an attempt has been made to develop the activity-based travel demand models for the selected zone of Bangalore city. Bangalore city has been divided into three major areas and further into 47 zones. The data has been collected through individual person survey considering certain parameters which are influential to develop person tours. This collected data is then analysed through SPSS software, and models are developed considering the several parameters such as age, gender, monthly income, distance of travel, daily travel cost and vehicle ownership. Simultaneously, the zonal public transport policies have been studied to understand the norms regarding the transport such as quality of transport, pricing, financing and parking facilities. The results obtained in the form of models are compared with the traditional models and are used to evaluate the public transport policies. Also, the factors influencing the trips of each individual have been studied and the effects of those factors are analysed. The results obtained are found satisfactory in terms of R2 value and other testing parameters. Transport policies are selected, and models are linked to the policies to evaluate them. Study concludes with the effective linking of the models to the policies which will help the authorities to bring it into play.