通过未来I-ADAS的镜头使用自然驾驶数据评估交叉路口碰撞
Andrew J Galloway1, Max Bareiss1, Takashi Hasegawa2
1Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
Traffic injury prevention
|August 3, 2023
概括
交叉路口先进驾驶辅助系统 (I-ADAS) 面临的挑战是现实世界碰撞中的视线障碍. 了解这些障碍对于开发有效的I-ADAS来防止交叉碰撞至关重要.
科学领域:
- 交通安全 交通安全
- 汽车工程 汽车工程
- 驾驶过程中的人类因素
背景情况:
- 交叉路口撞车仍然是一个重大的安全问题,每年导致许多道路死亡和受伤.
- 先进的驾驶辅助系统 (ADAS) 在通过自动检测和制动来缓解十字路口碰撞方面表现有前途.
- 现实世界的驾驶复杂性对十字路口ADAS (I-ADAS) 的可靠运行提出了独特的挑战.
研究的目的:
- 通过使用自然驾驶数据,调查未来I-ADAS在常见交叉路口碰撞场景中的潜在挑战.
- 分析视线障碍,驾驶员的分心,以及在直线交叉路径 (SCP),左转穿过路径/侧面方向 (LTAP/LD) 和左转穿过路径/相反方向 (LTAP/OD) 中的逃避反应.
主要方法:
- 利用了第二个战略公路研究计划 (SHRP 2) 自然驾驶研究的数据,包括多角度视频和车辆动态.
- 审查驾驶数据以识别视线障碍,驾驶员分心和响应启动.
- 从各种碰撞配置的沉事件计算到碰撞的时间 (TTC).
主要成果:
- 撞击速度的中位数在16.1至18.0公里/小时之间,TTC的中位数在1.35至1.44秒之间.
- 关键的视线障碍包括较慢的车辆,邻近车道的车辆和停放的卡车.
- 在LTAP/OD场景中,近距离的车道上的相对车辆经常会阻碍视图.
结论:
- 视线障碍是SCP,LTAP/LD和LTAP/OD崩中的I-ADAS性能的一个重大挑战.
- 自然驾驶数据为I-ADAS开发提供了对驾驶员行为和环境因素的关键见解.
- 对详细的驾驶数据的分析超越了警察报告的撞车数据的局限性,以了解I-ADAS挑战.
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