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Probe vehicles can be used as an efficient method to collect real-time travel time information. Existing research on travel time estimation directly records the travel time of a probe vehicle and calculates the mean of travel times from a number of probe vehicles. This paper describes a new approach to estimate travel time by using a single probe vehicle based on the analysis of the speed-time profile. According to the features extracted from the speed profile, the driving pattern of a probe vehicle is classified by using fuzzy sets. Differing from the traditional concept in the research of driving behaviour, the driving pattern in this study is only associated with the difference between the travel time of the probe vehicle and mean travel time. A new variable, the maximum continuous acceleration (MCA), is introduced to reflect acceleration characteristics of the driver by combining the continuous acceleration and speed at the acceleration starting point. The MCA and average speed of a probe vehicle are taken as the input variables of fuzzy sets. The membership function values are determined by historical traffic data of the tested road segment. The travel time is calculated by corresponding equations for different driving patterns. A comparison of the estimated travel time and actual mean travel time illustrates the value of the approach.
Li et al. (Wed,) studied this question.