面向车路协同的公交车行驶行为研究展望

针对目前相关研究中公交站区公交车行驶行为主要由跟驰、换道及仿真等理论模型进行刻画的局限,为了构建符合车辆实际运行的行为模型,明晰现有公交站相关设计规范是否科学合理,提出了基于无人机视频和图像识别技术。参数化提取公交车进出站过程中的轨迹、速度、加速度等真实行为特征数据的方法,并对其运动变化规律进行详细分析。探讨了基于实测大数据构建车辆运动模型的必要性和可行性,提出了相应技术路线及关键技术。初步研究表明,该方法将能准确描述公交车行驶行为与道路设计、社会车辆运行之间的有机联系,可为公交站几何尺寸设计、公交站区范围内车辆管控以及无人驾驶研究提供技术支撑。

Prospect of Research on the Driving Behavior of Buses for Vehicle-road Cooperation

The bus driving behavior in the bus station area is mainly characterized by theoretical models such as follow-up, lane change, and simulation. In order to build a behavioral model that matches the actual operation of the vehicle and clarify whether the existing bus station related design specifications are scientific and reasonable.This paper presents the method parametrically extracting real-life behavior data including trajectory, velocity, acceleration when the bus enter and exit station based on UAV and image recognition technology, which detailed analyzing the law of movement about vehicles. Furthermore, we discuss the necessity and feasibility of building a vehicle movement model based on measured big data and propose the corresponding technical route and key technologies. The preliminary research demonstrates the method can accurately describe the organic links including bus driving behavior , road design and social vehicle operation, which can provide technical support for geometric design of bus stops, vehicle control and driverless research.