构建云控智驾测试平台,真实模拟通信延迟对安全与舒适的影响
A Communication-Latency-Aware Co-Simulation Platform for Safety and Comfort Evaluation of Cloud-Controlled ICVs
- 融合CarMaker与Vissim,引入中匈5G实测延迟数据建模
- 动态冲突模块使场景更危急,延迟主要影响乘坐舒适性
- 适合自动驾驶云控系统测试与评估的研究者使用
测试云控智能网联汽车(ICVs)需模拟车辆行为与真实通信延迟。本文提出一个融合CarMaker与Vissim的延迟感知协同仿真平台,用于评估真实车-云(V2C)延迟下的安全与舒适性。基于中国与匈牙利的5G实测数据,采用伽马分布建模两种通信延迟模型。提出主动冲突模块(PCM),可动态控制背景车辆生成安全关键场景。通过六种测试条件(两种PCM模式×三种延迟条件)验证平台有效性,评估指标包括碰撞率、跟车距离、后侵时间及纵向加速度频谱特征。结果表明,PCM显著提升环境危急性,而V2C延迟主要影响乘坐舒适性。实验验证了该平台在多样测试条件下系统评估云控ICVs的有效性。
原文摘要 · Abstract (English)
Testing cloud-controlled intelligent connected vehicles (ICVs) requires simulation environments that faithfully emulate both vehicle behavior and realistic communication latencies. This paper proposes a latency-aware co-simulation platform integrating CarMaker and Vissim to evaluate safety and comfort under real-world vehicle-to-cloud (V2C) latency conditions. Two communication latency models, derived from empirical 5G measurements in China and Hungary, are incorporated and statistically modeled using Gamma distributions. A proactive conflict module (PCM) is proposed to dynamically control background vehicles and generate safety-critical scenarios. The platform is validated through experiments involving an exemplary system under test (SUT) across six testing conditions combining two PCM modes (enabled/disabled) and three latency conditions (none, China, Hungary). Safety and comfort are assessed using metrics including collision rate, distance headway, post-encroachment time, and the spectral characteristics of longitudinal acceleration. Results show that the PCM effectively increases driving environment criticality, while V2C latency primarily affects ride comfort. These findings confirm the platform's effectiveness in systematically evaluating cloud-controlled ICVs under diverse testing conditions.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。