Multiobjective optimization framework for cooperative adaptive cruise control vehicles in the automated vehicle platooning environment
Document Type
Article
Publication Date
1-1-2017
Abstract
Automated longitudinal control technology has been tested through cooperative adaptive cruise control (CACC), which is envisioned to improve highway mobility drastically by forming a vehicle platoon with short headway while maintaining stable traffic flow under disturbances. Compared with previous research efforts with the pseudomulti-objective optimization process, this paper proposes an automated longitudinal control framework based on multiobjective optimization (MOOP) for CACC by taking into consideration four optimization objectives: mobility, safety, driver comfort, and fuel consumption. 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.
Identifier
85033712626 (Scopus)
ISBN
[9780309441551]
Publication Title
Transportation Research Record
External Full Text Location
https://doi.org/10.3141/2625-04
e-ISSN
21694052
ISSN
03611981
First Page
32
Last Page
42
Volume
2625
Fund Ref
Federal Highway Administration
Recommended Citation
Zhong, Zijia; Lee, Joyoung; and Zhao, Liuhui, "Multiobjective optimization framework for cooperative adaptive cruise control vehicles in the automated vehicle platooning environment" (2017). Faculty Publications. 9868.
https://digitalcommons.njit.edu/fac_pubs/9868
