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An Interactive Car-Following Model (ICFM) for the Harmony-With-Traffic Evaluation of Autonomous Vehicles

计算机科学 模拟 汽车工程 工程类
作者
Haolan Meng,Junyi Chen,Tianyue Feng,Bin Wang,Lu Xiong,Zhuoping Yu,Hong Chen
出处
期刊:SAE technical paper series
标识
DOI:10.4271/2023-01-0822
摘要

<div class="section abstract"><div class="htmlview paragraph">Harmony-with-traffic refers to the ability of autonomous vehicles to maximize the driving benefits such as comfort, efficiency, and energy consumption of themselves and the surrounding traffic during interactive driving under traffic rules. In the test of harmony-with-traffic, one or more background vehicles that can respond to the driving behavior of the vehicle under test are required. For this purpose, the functional requirements of car-following model for harmony-with-traffic evaluation are analyzed from the dimensions of test conditions, constraints, steady state and dynamic response. Based on them, an interactive car-following model (ICFM) is developed. In this model, the concept of equivalent distance is proposed to transfer lateral influence to longitudinal. The calculation methods of expected speed are designed according to the different car-following modes divided by interaction object, reaction distance and equivalent distance. Then the expected acceleration is calculated according to the expected speed, and the corresponding acceleration limit value and reference value are designed under different car-following modes. Through the design and combination of various car-following modes and the customization of model parameters, the ICFM can adjust the recognition range of the forward or side leading vehicle, and calibrate the way and degree of response to the leading vehicle's lane change intention. Through the simulation test, taking the typical ramp merge scene of harmony-with-traffic as an example, the ICFM is verified and compared with the Intelligent Driver Model (IDM). The result shows that the ICFM has the advantage of having interpretable interaction capabilities and is better targeted for evaluation requirements than the IDM, and has the feasibility of being applied to standardized performance evaluation of autonomous vehicles.</div></div>
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