contributor author | Zhou Wang | |
contributor author | Duanfeng Chu | |
contributor author | Bolin Gao | |
contributor author | Liang Wang | |
contributor author | Xiaobo Qu | |
contributor author | Keqiang Li | |
date accessioned | 2024-04-27T22:32:24Z | |
date available | 2024-04-27T22:32:24Z | |
date issued | 2024/03/01 | |
identifier other | 10.1061-JTEPBS.TEENG-7920.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4296892 | |
description abstract | This work investigates commercial vehicle platoon predictive cruise control for highways. We propose a cloud-based platoon predictive cruise control method (CPPCC). A two-layered control architecture of the CPPCC is proposed as a platoon predictive cruise speed planning layer in the cloud and a platoon stabilization control layer. The CPPCC communication topology is proposed to achieve coupled control of the hierarchical architecture. The speed planning layer is a dynamic planning (DP) algorithm based on road slope in the rolling distance domain. The lower layer is a stability control algorithm to meet the stability requirements of vehicle platoon driving; the vehicle side is distributed model predictive control (DMPC). The CPPCC is validated by real road and vehicle data models, and comparative experiments with the traditional predecessor-leader following–cruise control (PLF-CC) platoon and predecessor following–cruise control (PF-CC) platoon. The speed error of the vehicle platoon was maintained at [−0.25, 0.30] (m/s) and the space error at [−0.13, 0.66] (m) in platoon stability. Against the comparison method, the CPPCC saved fuel by over 5.13% and achieved an overall operational efficiency improvement of 5.71%. This research contributes to solving the problem of energy-efficient driving in vehicle platoons. Based on the cloud control system (CCS), cloud-based platoon predictive cruise control (CPPCC) is proposed, which is a layered structure. The upper layer is the platoon speed planning layer in the cloud and the lower layer is the platoon stability control layer. By adding cloud nodes and changing the structure of the existing platoon predictive cruise control (PPCC) and communication topology, CPPCC is able to achieve the goals of platoon economy and stability. Compared with PF-CC and PLF-CC, it is able to achieve fuel savings of more than 5.13% and efficiency improvements of 5.71% while ensuring stable platoon operation. Deploying the vehicle-side platoon stabilization controller in a commercial vehicle platoon can provide a solution to existing PPCC for energy saving and stability control. Combined with cloud-based speed planning, this enables commercial vehicle platoon PCC. Solving the problem of energy consumption of existing commercial vehicles and thus reducing environmental pollution from logistics transport. | |
publisher | ASCE | |
title | Cloud-Based Platoon Predictive Cruise Control Considering Fuel-Efficient and Platoon Stability | |
type | Journal Article | |
journal volume | 150 | |
journal issue | 3 | |
journal title | Journal of Transportation Engineering, Part A: Systems | |
identifier doi | 10.1061/JTEPBS.TEENG-7920 | |
journal fristpage | 04023146-1 | |
journal lastpage | 04023146-15 | |
page | 15 | |
tree | Journal of Transportation Engineering, Part A: Systems:;2024:;Volume ( 150 ):;issue: 003 | |
contenttype | Fulltext | |