Abstract:
Delhi metro is suffering from serious congestion due to booming travel demand. Differential pricing is an important and effective measure in traffic demand management (TDM). Whether pricing strategies work depends strongly on the responses of travellers to fare changes. Normally, the fare elasticity of demand is used to describe the relationship between demand changes and fare changes at an aggregate level. It is useful to estimate demand changes for system-wide and long-term pricing policies. However,
for regional and short-term (valid time window is short) fare strategies, it is hard to capture the reactions just by the fare elasticity of demand. The retiming elasticity decreases greatly with increasing shifted time, and 30 minutes is almost the maximum acceptable shifted time for passengers. Moreover, the retiming elasticity of passengers in the middle term is approximately twice that in the short term. Applications of fare optimization are also executed, and the results suggest that optimizing the valid time window of the discount fares is a feasible way to improve the congestion relief effect of the policy, while policy makers should be cautious to change fare structures and increase discounts. Passengers’ travel responses to fare changes are very complex and related to various external factors, such as service quality, travel preference, and socioeconomic factors. In
past works on travel responses are usually specific to a certain region or transit system and assume that the external factors remain the same before and after the policy. As we already seen that flexi fare is success full in Beijing suburban railway and it handles booming congestion of suburbs rail. Modelling in departure time choice plays a vital role in caters the congestion in metro and distributes the commuters in different intervals of time. For knowing the modelling departure time choice different we have to know the
willingness to shift to off peak hour or hike in fare of peak hour. So for this new fare strategies must be recommended.
