In the context of high-speed mixed traffic and intricate multi-vehicle interaction, existing driving intention recognition models for research vehicles inadequately address crucial factors, such as driving style and vehicle-vehicle interaction information. This paper introduces a novel driving intention recognition model based on an enhanced bidirectional long- and short-term memory network (Bi LSTM). The proposed model leverages the driving trajectory sequence of the target vehicle, driving style, and interaction features of surrounding vehicles as inputs for effective training and learning. It facilitates the classification and recognition of the driving intention feature dataset, specifically considering diverse driving styles. Additionally, the whale optimization algorithm is employed to optimize pivotal hyperparameters, encompassing the number of hidden layer nodes and learning rate, effectively mitigating the adverse impacts of manual parameter adjustment. The model's efficacy is validated using the NGSIM dataset, exhibiting an impressive recognition accuracy of 97.5% in precisely identifying vehicle driving intentions.
为了通过车车、车路通信实现车辆和基础设施之间智能协同,达到提高交通安全、缓解交通拥堵的目标,进行了协同式队列控制方法研究.基于车辆间信息流拓扑结构、队列几何构型、控制目标和评价指标在MATLAB/Simulink中搭建了队列速度控制器策略.结合CarSim建立精细车辆动力学模型的优势,在CarSim中搭建队列场景工况,完成了CarSim和Simulink的联合仿真系统搭建,实现了对车辆队列场景的仿真,验证了队列控制算法的可行性,降低了实车试验时的风险,节省时间和成本.
分别用AVL公司生产的直采分析仪和稀采分析仪对船机排放的气态污染物进行测量,用simulink搭建的气态污染物质量流量计算模型对数据进行计算,研究了直采和稀采采样方式下对排放结果的影响.分析表明:在NRSC的C1循环下,直采与稀采相比出现以下情况:NOx的排放量呈现增加的趋势,最大增加了6.5％,但CO的排放量呈现降低的趋势,最大减少了1.1％.随着负荷的增加,直采NOx的采样结果和稀采NOx的采样结果的差值在不断增加,最大差值为66.76 g/h.因稀释空气的温度和湿度的影响,在稀采方式下出现NOx的排放量低和CO的排放量高的情况.
为合理的设计汽车3个蒸发器制冷回路电磁截止阀布置与储液罐大小,文章通过3个蒸发器系统制冷剂充注量的实车配管台架测试,验证了不同管路截止阀布置位置对系统充注量的影响,截止阀应靠近空调箱蒸发器布置.结果显示在充注工况下蒸发器有空气流动换热工作时,蒸发器内部制冷剂平均空泡系数在0.83～0.87,而蒸发器没有空气流动换热工作且没有截止阀截断时,蒸发器内部制冷剂平均空泡系数在0.57左右.
汽车试验场耐久试验是车辆耐久性验证的关键因素,如何制定合理的试验方法仍是亟待深入研究的重要问题.文章通过对用户道路特征的研究,得到用户道路特征的量化评价模型,进而根据评价模型对整车载荷进行分解、雨流分析、雨流叠加及外推,得到反映用户道路特征的目标载荷谱,并制定出了反应用户道路特征的车辆结构耐久试验方法.
