Discrete Choice Analysis: Modelling and Applications in Urban Transportation
Image source: Hindustan Times

Increase in traffic congestion in major metropolitan cities has led to longer travel times with more fuel consumption resulting in motorist frustration. Traffic congestion have also led to indirect impacts like increase in accident rates, deterioration in air quality, increase in freight transportation costs. In recent years, the cities are exploring different traffic congestion management (TCM) policies. Discrete choice models are widely being used to evaluate the TCM policies to counter adverse effects of traffic congestion.
Demand and supply are considered to be the two pillars of TCM policies. Supply can be designed if the demand for a certain alternative is known. Human behaviours and responses to different transportation modes form the basis of these demand models. Such behaviours are discrete and qualitative in nature. Such decision making behaviour of a group of individuals can be modelled using discrete choice analysis. Moreover, discrete choice models also enable an analyst to determine the interrelationship and underlying dynamics of different attributes of alternatives and characteristics of decision makers which influence the choice decisions of the individuals.

Course Faculty