Abstract
This paper presents the results of a controlled-field experiment designed to evaluate the efficiency of a speed recommendation algorithm developed to reduce vehicle fuel consumption at signalized intersections. The evaluated algorithm received instantaneous speed data from the vehicle and computed real-time fuel-efficient speeds that were promptly communicated by an audio signal to the driver to follow. The controlled-field experiment included two other scenarios for comparison. In the first scenario, participants drove freely through the intersection (no communication between the vehicle and the infrastructure). In the second scenario, the time remaining for the current signal indication was communicated to the driver by an audio signal. The experiment was designed as a split-split-plot design in which the scenarios served as the plots, the grade (downhill or uphill) as the split plot, and the time-to-red indication offset (10, 15, 20, and 25 s) as the split-split plot. In total, 1,536 trips were conducted by 32 participants (16 females and 16 males) between the ages of 18 and 30. The collected data were compared in relation to fuel economy and travel time over a fixed 430-m distance (250 m upstream of the intersection and 180 m downstream). The statistical analysis showed significant differences between the evaluated scenarios. The developed optimal speed advisory algorithm was found to be efficient in reducing fuel consumption, with savings up to 19%, depending on the grade and red indication offset. In addition, the developed speed advisory algorithm was found to reduce travel times by up to 10%.
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