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In this work, we introduce a maximum likelihood (ML) method to estimate the smallest accepted gap of a specific driver, the so-called critical gap. Previous methods, like Troutbeck's or Raff's method, are well known and widely used but require a consistently behaving driver, which is usually not met. The methods will be investigated for the personalization of an intersection assistant, which we are...