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With other models, the gap can be more drastic.
Among the rich selection of different models, the gap time model as an extension of the multiplicative Cox proportional hazards model [ 5] and the Lin and Ying's additive model (L-Y model) [ 8, 10] received the greatest attention due to easy interpretation of the covariate effects.
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The model was derived from a forest gap model, reducing the gap models' complexity by model aggregation and includes elements for showing complex behavior: many state variables, non-linear process functions, feedbacks and spatial interactions.
Rossi and Meneguzzer [22] modeled the gap acceptance behavior at priority intersections using neuro-fuzzy system.
Maze [6] modeled the gap acceptance behavior using a logit model which closely approximates the probit model.
The results indicate that the ANFIS can be used to model the gap acceptance behavior at partially controlled intersections.
After careful observation, the following strategies have been adopted for modeling the gap acceptance behavior under mixed traffic condition using a logit model.
The primary focus of this paper is to model the gap acceptance behavior of vehicles at partially controlled intersections in India with the application of ANFIS.
The objective of this study is to analyze and model the gap acceptance behavior of minor street drivers at uncontrolled T-intersections considering their aggressive nature.
Sangole et al. [16] used an adaptive neuro-fuzzy interface system (ANFIS) approach to model the gap acceptance behavior of two-wheelers at uncontrolled intersections.
In the other method on the right column, which is referred to as "Proposed model", the gap was estimated from the gap (capacitance) sensor [18] and the voltage was obtained by using Eqs.
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