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Trip distribution finds prime place after trip generation in sequential modelling of travel demand to cover the spatial dimensions in a geographical area, to reflect on trip length and frequency. It provides the basis for strategic land use and transport infrastructure development both at local and regional levels. Trip distribution problems in the real world are quite complex with association of uncertainty in the decision making and therefore calls for an unorthodox approach to deal with the concerned issue. Soft computing technique - Fuzzy Logic (FL) is believed to be capable of addressing the uncertainty lying in the travellers’ behaviour and has been sought to develop realistic behavioural models in the recent years. FL takes into account linguistic variables and is based on simple and logical “IF-THEN” rules which closely resemble human thought process. Fuzzy Logic based trip distribution models are developed employing Fuzzy C-mean (FCM) clustering, and are compared for their performance with the Genfis based approach, where a Sugeno-type Fuzzy Inference System (FIS) is generated using Subtractive clustering. Surat, a fast growing metropolitan city in India is considered to realize the study. The models developed here, find applications in strategic land-use and transport planning for developing Indian cities.

transportation research procedia

Spatial distribution of urban trips in recently expanded Surat city through Fuzzy Logic with various clustering Techniques: A case study of typical metropolitan city in India