Engin Ozatay

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Driving style, road geometry, and traffic conditions have a significant impact on vehicles' fuel economy. In general, drivers are not aware of the optimal velocity profile for a given route. Indeed, the global optimal velocity trajectory depends on many factors, and its calculation requires intensive computations. In this paper, we discuss the optimization(More)
This paper proposes a speed prediction scheme for multi-vehicle car-following scenarios, which involves vehicle intelligence, human drivers, and vehicle dynamics interacting with one another, under low vehicular communication penetration rates. The algorithm relies on a small number of vehicles equipped with communication capabilities and utilizes(More)
The previous studies have shown that optimizing the driving velocity profiles and route selection based on the availability of the traffic lights' operation information in a traffic network can significantly reduce the individual and cumulative energy consumption of on-road vehicles for the urban driving. In this paper, we propose an accurate and precise(More)
Vehicle speed prediction can benefit a wide range of vehicle control designs, especially for fuel economy applications. This paper shows a computationally light vehicle short term speed predictor designed for on-board implementation, using minimal information of speed measurement only. The predictor generalizes historical speed data's underlying pattern and(More)
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