The 85th speed of vehicles is one of the traffic engineering parameters used by road safety equipment designers. It is usually used for maintenance activities and designing of warning signs and road equipments. High measuring costs of speed data collection lead decision makers to define a methodology for determining the category of 85th speed using indirect parameters. In this research work, focusing on undivided intercity roads, a hybrid particle-swarm-optimization- (PSO-) fuzzy model has been developed to determine the category of 85th speed. In this model, geometric design parameters including roads' width and length characteristics and roadside land use are considered as input variables whereas the category of the 85th speed is output variable. A set of experimental data is used for evaluating the performance of the proposed model comparing to a well-known model of exponential regression. It is shown that the developed PSO-fuzzy model is capable of determining the category of 85th speed with an accuracy of 96%, while exponential regression can estimate that with up to 84% accuracy. Variable effectiveness procedure shows that the lane width has more direct effect on 85th speed than shoulder width and the number of access points. The percentage of forbidden overtaking is also found to have indirect effect on 85th speed. 1. Introduction The 85th speed is one of the most important traffic engineering parameters. By definition, the 85th speed is the maximum speed that eighty-five percent (%85) of drivers prefer to drive with a speed less than that. The importance of this parameter is that the majority of drivers drive within their safe considered speed, so the 85th speed is the maximum speed considered as safe speed by most of drivers [1]. The 85th speed is being used in some technical applications such as designing of road safety infrastructure, planning road maintenance programs, and setting warning signs, while construction workers are working on the road in order to provide the traffic with safe passage. Many parameters affect on 85th speed including authorized speed, traffic volume, land topography, and roadside land use condensations [1]. Traditionally, 85th speed is calculated using vehicle’s speed on a certain road. Many techniques have been utilized for estimating vehicles’ speed, mainly need for electronic devices and infrastructures. Image processing technique [2], combination of fuzzy logic and image processing [3], traffic counting and occupancy data [4], vehicle tracking [5], optical sensors [6], RF-based vehicle detection [7], the field of
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