Impact on Congestion and Fuel Consumption of a Cooperative Adaptive Cruise Control System with Lane-Level Position Estimation

Edgar Talavera, Alberto Díaz-Álvarez, Felipe Jiménez and José E. Naranjo
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Edgar Talavera: Escuela Técnica Superior de Ingeniería de Sistemas Informáticos (ETSISI), Universidad Politécnica de Madrid (UPM), 28031 Madrid, Spain
Alberto Díaz-Álvarez: University Institute for Automobile Research (INSIA), Universidad Politécnica de Madrid (UPM), 28031 Madrid, Spain
Felipe Jiménez: University Institute for Automobile Research (INSIA), Universidad Politécnica de Madrid (UPM), 28031 Madrid, Spain
José E. Naranjo: University Institute for Automobile Research (INSIA), Universidad Politécnica de Madrid (UPM), 28031 Madrid, Spain

Energies, 2018, vol. 11, issue 1, 1-17

Abstract: In recent years, vehicular communications systems have evolved and allowed for the improvement of adaptive cruise control (ACC) systems to make them cooperative (cooperative adaptive cruise control, CACC). Conventional ACC systems use sensors on the ego-vehicle, such as radar or computer vision, to generate their behavioral decisions. However, by having vehicle-to-X (V2X) onboard communications, the need to incorporate perception in the vehicle is drastically reduced. Thus, in this paper a CACC solution is proposed that only uses communications to make its decisions with the help of previous road mapping. At the same time, a method to develop these maps is presented, combining the information of a computer vision system to correct the positions obtained from the navigation system. In addition, the cut-in and cut-out maneuvers for a CACC platoon are taken into account, showing the tests of these situations in real environments with instrumented vehicles. To show the potential of the system in a larger-scale implementation, simulations of the behavior are provided under dense traffic conditions where the positive impact on the reduction of traffic congestion and fuel consumption is appreciated.

Keywords: cooperative adaptive cruise control; platoon; adaptive cruise control; V2X; computer vision; cut-in; cut-out (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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