Engineers Eye Adaptive Cruise Control as Platooning Enabler
According to a new research paper published by the Transportation Research Board, adaptive cruise control has proven to be the best method of maintaining longitudinal vehicle control in platooning applications.
by Staff
July 21, 2017
A new study found that adaptive cruise control systems can help maintian mobility, safety, driver comfort, and fuel consumption in platooning operations. Photo: Peloton
1 min to read
A new study found that adaptive cruise control systems can help maintian mobility, safety, driver comfort, and fuel consumption in platooning operations. Photo: Peloton
Is a new, expanded role for adaptive cruise control systems on the horizon? A recent technical paper by engineers Zijia Zhong, Joyoung Lee and Liuhui Zhao at the Newark College of Engineering, New Jersey Institute of Technology, published by the Transportation Research Board suggests so.
According to the paper, titled "Multiobjective Optimization Framework for Cooperative Adaptive Cruise Control Vehicles in the Automated Vehicle Platooning Environment," cooperative adaptive cruise control has been proven in tests to be an effect means of automated longitudinal control technology with possible vehicle platooning applications in the near future.
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The paper’s authors have proposed an automated longitudinal control framework based on multiobjective optimization (MOOP) for CACC by taking into consideration four vehicle optimization onbjectives: mobility, safety, driver comfort, and fuel consumption.
The paper notes that of the target time headways that have been tested, the proposed CACC platoon control method achieved the best performance with 0.9- and 0.6-s target time headways. Compared with a non-optimization-based CACC, the MOOP CACC achieved 98%, 93%, 42%, and 33% objective value reductions of time headway deviation, unsafe condition, jitter, and instantaneous fuel consumption, respectively.
In comparison with a single-objective-optimization-based approach, which optimized only one of the four proposed objectives, it was shown that the MOOP-based CACC maintained a good balance between all of the objective functions and achieved Pareto optimality for the entire platoon.
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