Related Experiment Videos
Autonomous Driving Open Road Complexity Classification
Hongpan Yue1, Yichun Jia1, Tongfei Li2
1Beijing Connected and Autonomous Vehicles Technology Co., Ltd., Beijing 100176, China.
Abstract:
Autonomous vehicle open-road testing is a crucial component in the development of intelligent and connected vehicle (ICV) industries. The classification of road complexity plays a key role in ensuring the safety and efficiency of such tests. This study, based on the practices of the High-Level Autonomous Driving Demonstration Zone in Beijing, proposes a scientific and systematic framework for classifying road complexity. The framework integrates static road features, dynamic traffic flow indicators, and safety event metrics, employing the Analytic Hierarchy Process (AHP) to quantify road complexity and categorize roads into five distinct levels. The findings provide significant guidance for the phased opening of test roads, optimization of autonomous driving algorithms, construction of accident scenario databases, and deployment of infrastructure. This paper further explores the practical applications and future development directions of road complexity classification, aiming to offer theoretical and practical support for the testing and demonstration of intelligent and connected vehicles.
Related Concept Videos
Hierarchy of Motor Control
Classification of Systems-I
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Classification of Systems-II
Rolling Resistance: Problem Solving
Multi-input and Multi-variable systems
In the absence of...
Controller Configurations
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller aligns...