控制领域很大牛人写的书，搞控制的必看！Khac Duc Do • Jie Pan这两个人一定得知道的。

现代车辆的网络安全最佳实践

AUV前进动力 6DOF AUV的动态模型 一些准则 在zigzagvert.m和zigzagvert_bp_bs.m中的图下方的“ saveas”行中更改文件夹名称

In this thesis we consider the problem of designing and implementing Model Predictive Controllers (MPC) for stabilizing the dynamics of an autonomous ground vehicle. For such a class of systems, the non-linear dynamics and the fast sampling time limit the real-time implementation of MPC algorithms to local and linear operating regions. This phenomenon becomes more relevant when using the limited computational resources of a standard rapid prototyping system for automotive applications. In this thesis we first study the design and the implementation of a nonlinear MPC controller for an Active Font Steering (AFS) problem. At each time step a trajectory is assumed to be known over a finite horizon, and the nonlinear MPC controller computes the front steering angle in order to follow the trajectory on slippery roads at the highest possible entry speed. We demonstrate that experimental tests can be performed only at low vehicle speed on a dSPACE rapid prototyping system with a frequency of 20 Hz. Then, we propose a low complexity MPC algorithm which is real-time capable for wider operating range of the state and input space (i.e., high vehicle speed and large slip angles). The MPC control algorithm is based on successive on-line linearizations of the nonlinear vehicle model (LTV MPC). We study performance and stability of the proposed MPC scheme. Performance is improved through an ad hoc stabilizing state and input constraints arising from a careful study of the vehicle nonlinearities. The stability of the LTV MPC is enforced by means of an additional convex constraint to the finite time optimization problem. We used the proposed LTV MPC algorithm in order to design AFS controllers and combined steering and braking controllers. We validated the proposed AFS and combined steering and braking MPC algorithms in real-time, on a passenger vehicle equipped with a dSPACE rapid prototyping system. Experiments have been performed in a testing center equipped with snowy and icy tracks. For both controllers we showed that vehicle stabilization can be achieved at high speed (up to 75 Kph) on icy covered roads. This research activity has been supported by Ford Research Laboratories, in Dearborn, MI, USA.

多目标识别，车辆跟踪，实时性好，便于快速跟踪，基于匈牙利算法

完整英文版Wireless Power Transfer for Electric Vehicles and Mobile Device（电动汽车和移动设备的无线电力传输）。 本文档从电动汽车，智能手机和笔记本电脑的移动式，无电缆充电到从太阳能发电场中收集太阳能，无线功率传输（WPT）技术为消费者和社会带来了巨大利益。 该综合资源由该领域的创新者撰写，解释了WPT的基本原理和最新进展，并说明了此新兴技术的关键应用。

Falcone的博士论文，主要介绍了自动驾驶车辆模型预测控制。学习过车辆自动驾驶控制方向的，都知道车辆模型预测控制是他在这个领域的开山之作。 很多资源是假的，这个是真的。

主要是讲他的 Braitenberg 小车，千辛万苦才搞到的，淘宝也没有卖的，感谢舍友。只设置一积分 下载，如果后续变多，那是xxdn系统的问题。

提出了一种基于骨架拐角检测的分离方法，以解决视频监控中合并车辆的问题。 首先，通过“射击法”提取融合区域的骨架，并通过角点检测得到骨架的角点。 其次，利用K-means聚类方法对角点进行聚类，从聚类结果中获取合并车辆的分割线。 来自监视视频的五十幅图像被用作实验数据。 实验结果表明，该算法不仅可以有效缓解合并车辆分离中的过度分割问题，而且可以减少所需的分离时间。

2018O奖论文-How to achieve the full adoption of all-electric vehicles.PDF