当前位置: X-MOL 学术IEEE Trans. Veh. Technol. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
An Efficient Eco-Planner for Autonomous Vehicles With Focus on Passengers Comfort
IEEE Transactions on Vehicular Technology ( IF 6.8 ) Pub Date : 2022-04-19 , DOI: 10.1109/tvt.2022.3168088
Alessandra Duz , Alex Gimondi , Matteo Corno , Sergio Savaresi

Speed planning is one of the tasks that a self-driving vehicle carries out. A complete planner should consider and balance passengers comfort, trip time and energy consumption. This paper proposes a computationally efficient global speed planner for autonomous vehicles that explicitly includes comfort as one of the main objectives. In particular, our approach considers the trip time as a user-specified constraint and optimizes a cost function that accounts for both energy consumption and comfort. Since passenger comfort plays a critical role for self driving vehicle, we propose a comfort model that captures different aspects: planar and vertical accelerations and the contribution of different frequency components. We test the algorithm on a realistic case study and we quantify the trade-off between energy consumption and comfort.

中文翻译:

专注于乘客舒适度的自动驾驶汽车高效生态规划器

速度规划是自动驾驶汽车执行的任务之一。一个完整的计划者应该考虑和平衡乘客的舒适度、旅行时间和能源消耗。本文提出了一种计算高效的自动驾驶汽车全局速度规划器,明确将舒适性作为主要目标之一。特别是,我们的方法将行程时间视为用户指定的约束,并优化了考虑能源消耗和舒适度的成本函数。由于乘客舒适度对自动驾驶汽车起着至关重要的作用,因此我们提出了一种舒适度模型,该模型可以捕捉不同方面:平面和垂直加速度以及不同频率分量的贡献。我们在一个现实的案例研究中测试了算法,我们量化了能源消耗和舒适度之间的权衡。
更新日期:2022-04-19
down
wechat
bug