Models for Estimation of Drivers’ Impatience on Two-Lane Rural Highways
Sofya Rozenshtein, Abishai Polus, Moshe Cohen
Abstract
Sofya Rozenshtein, Abishai Polus, Moshe Cohen
Abstract
The main objective of the study was to model the decision making process of drivers during passing maneuvers performed on two-lane rural highways, using only traffic characteristics. By limiting the input data in this way, the findings and their implications become applicable to any two-lane road segment. On two-lane highways, when traffic volume increases, drivers may be unwilling to travel in platoons, resulting in an increased willingness to execute risky passing maneuvers. This phenomenon has been called “drivers’ impatience”. The study proposes an empirical method for evaluating drivers’ impatience using the concept of a critical passing gap. It was found that the critical passing gap has a bounded decreasing function determined by the total traffic volume or the volume in the oncoming lane. The critical passing gaps were found to be Log-Normally and Normally-distributed with an average value of 16.5 seconds, and a standard deviation of 5.5 seconds.
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The main objective of the study was to model the decision making process of drivers during passing maneuvers performed on two-lane rural highways, using only traffic characteristics. By limiting the input data in this way, the findings and their implications become applicable to any two-lane road segment. On two-lane highways, when traffic volume increases, drivers may be unwilling to travel in platoons, resulting in an increased willingness to execute risky passing maneuvers. This phenomenon has been called “drivers’ impatience”. The study proposes an empirical method for evaluating drivers’ impatience using the concept of a critical passing gap. It was found that the critical passing gap has a bounded decreasing function determined by the total traffic volume or the volume in the oncoming lane. The critical passing gaps were found to be Log-Normally and Normally-distributed with an average value of 16.5 seconds, and a standard deviation of 5.5 seconds.
Key concepts: Traffic volume, Limiting, Estimation, Transport engineering, Computer science, Bounded function, Volume (thermodynamics), Process (computing)