In the current literature, little research has been done in the eco-driving of vehicle platoon. To increase the fuel efficiency of vehicle platoon and ensure vehicle safety, this study proposes a switching control strategy for vehicle platoon travelling on a road with varying slopes, where the platooning and eco-driving technologies are used. To improve the fuel efficiency of vehicle platoon, the cooperative look-ahead controller is proposed by formulating a cooperative look-ahead control problem of vehicle platoon based on distributed model predictive control (CLCbDMPC), which is a constrained nonlinear non-convex multi-objective optimisation problem. To solve the CLCbDMPC problem quickly, after the minimum fuel consumption table and its corresponding optimal reduction gear ratio table are constructed and calculated off-line, the improved particle swarm optimisation algorithm with multiple dynamic populations is presented. Furthermore, the safety controller acting as the emergency brake to guarantee vehicle safety is also designed. The switch between the look-ahead controller and the safety controller forms the switching control strategy of vehicle platoon. Simulation results demonstrate, compared with benchmarks, the proposed strategy can significantly save up to 21.88% of fuel for vehicle platoon, and vehicle safety can also be guaranteed.
Cooperative look-ahead control of vehicle platoon travelling on a road with varying slopes
IET Intelligent Transport Systems ; 13 , 2 ; 376-384
2018-11-28
9 pages
Article (Journal)
Electronic Resource
English
safety controller , road vehicles , vehicle safety , concave programming , cooperative look-ahead controller , eco-driving technologies , improved particle swarm optimisation algorithm , constrained nonlinear nonconvex multiobjective optimisation problem , distributed control , fuel efficiency , switching control strategy , road traffic control , distributed model predictive control , cooperative look-ahead control problem , predictive control , CLCbDMPC problem , vehicle platoon , optimal reduction gear ratio table , particle swarm optimisation , minimum fuel consumption table , multiple dynamic populations , switching systems (control)
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