Rajalakshmi P
The choice of transport mode is one of the most important models in transport planning. This is due to the key role played by public transport, walking and cycling in transport policy. Public transport makes more efficient use of road space compared to cars. The issue of mode choice is therefore one of the most important in transport modeling. It impacts on the efficiency to which people travel in urban areas, the amount of space devoted to transport and if a range of transport are available to people. It is important then to develop and use models which are sensitive to the attributes of travel that influence individual choices of modes. The factors that influence mode choice include characteristics of the trip maker, type of journey and characteristics of the transport facility. An individual's intrinsic mode preference and responsiveness to level-of-service variables affects her or his travel mode choice for a trip. The current paper formulates a Artificial Neural Network model of travel mode choice that accommodates variations in mode preferences and responsiveness to level-ofservice due to both observed and unobserved individual characteristics. The model was applied to examine sub urban work travel mode choice from a sample of workers from the Kottayam District