A socio-economic status-dependent case study on relevance and frequency-enabled trip planning model

Abstract

Planning a trip not only depends on the travelling cost, time and path, but also on the socio-economic status of the traveller. This paper attempts to introduce a new trip-planning model that is able to work on real time data with multiple socio-economic constraints. The proposed trip planning model processes the real time data and it is followed by the extraction of the relevant socio-economic attributes to mine the most frequent and the feasible attribute to plan the trip. Correlation defines the relevance of the socio-economic constraints, whereas the frequent and the feasible attributes are mined using the sequential pattern mining approach. The real-time travel information of about 38,303 trips is acquired from the Indian city of Hyderabad to subject the model for experimentation. The proposed model maintains a substantial trade-off between the multiple performance metrics than the conventional models.