Car-following behavior models based on conventional mathematical cannot adequately reproduce traffic phenomena, such as breakdown, capacity drop, and oscillations, require parameter setting. Therefore, this study aims to construct a highly accurate car-following model using deep learning. We evaluated the influence of variables in dataset random forest. Furthermore, we constructed predict accel...

Car-following refers to a control process in which the following vehicle (FV) tries keep safe distance between itself and lead (LV) by adjusting its acceleration response actions of ahead. The corresponding car-following models, describe how one follows another traffic flow, form cornerstone for microscopic simulation intelligent development. One major motivation models is replicate human drive...

The basic assumption in visual angle car following models is that the following distance between successive vehicles is a function of the object (i.e. leading vehicle) width. This paper examines the validity of this assumption using two types of data. Published real traffic data from instrumented vehicles in the USA and Germany have been used to check the ability of these models to replicate re...

This paper reports design details and applications of the developed visual laser radar. It presents experimental results from "inspection of tunnel tubes", modeling of a "car body welding cell" and a "car body gripper" in the automotive industry. The laser radar was developed at Z+F and is designed for high performance measurements with high robustness, suited for deployment in real industrial ...

One of the main problems of car-like robot is robust path following in the presence of sliding effect. To tackle this problem, a robust mix H2/H∞ static state feedback control method is selected. This method is the well-known linear robust controller which is robust against external disturbance as well as model uncertainty. In this paper, the path following problem is formulated as linear matri...