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- W622674018 abstract "Drivers’ car-following behavior, coupled with inaccurate perception of ambient conditions, contributes to oscillations and significant emissions in congested highway traffic. The emergence of intelligent vehicles and communication technologies provide an opportunity to dynamically optimize longitudinal control of car-following vehicles in a platoon and eliminate human factors from car-following laws. This paper proposes a nonlinear model predictive control (MPC) model for emission mitigation via longitudinal control of intelligent vehicles in a congested platoon. To relieve the real-time optimization burden, the authors also propose an instantaneous control model which is essentially a simplified MPC model with short prediction and control horizons. The proposed vehicle control strategies are tested in a series of simulation scenarios, and the results verify that the localized and instantaneous control of a few intelligent vehicles could induce lower emissions of a platoon of vehicles. The proposed models are also applied to field trajectory data, and results show that the instantaneous emission optimization model significantly reduces emissions without increasing travel time. In addition, numerical results show that the effectiveness of the proposed vehicle longitudinal control on emission mitigation and traffic stabilization increase with the percentage (penetration rate) of intelligent vehicles in the congested vehicle platoon." @default.
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- W622674018 date "2015-01-01" @default.
- W622674018 modified "2023-09-26" @default.
- W622674018 title "Emission Mitigation via Longitudinal Control of Intelligent Vehicles in a Congested Platoon: An Exploratory Study" @default.
- W622674018 hasPublicationYear "2015" @default.
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