Human driving data-based design of a vehicle adaptive cruise control algorithm

This paper presents a vehicle adaptive cruise control algorithm design with human factors considerations. Adaptive cruise control (ACC) systems should be acceptable to drivers. In order to be acceptable to drivers, the ACC systems need to be designed based on the analysis of human driver driving behaviour. Manual driving characteristics are investigated using real-world driving test data. The goal of the control algorithm is to achieve naturalistic behaviour of the controlled vehicle that would feel natural to the human driver in normal driving situations and to achieve safe vehicle behaviour in severe braking situations in which large decelerations are necessary. A non-dimensional warning index and inverse time-to-collision are used to evaluate driving situations. A confusion matrix method based on natural driving data sets was used to tune control parameters in the proposed ACC system. Using a simulation and a validated vehicle simulator, vehicle following characteristics of the controlled vehicle are compared with real-world manual driving radar sensor data. It is shown that the proposed control strategy can provide with natural following performance similar to human manual driving in both high speed driving and low speed stop-and-go situations and can prevent the vehicle-to-vehicle distance from dropping to an unsafe level in a variety of driving conditions.     

Findings from subjective evaluations and driver ratings of vehicle dynamics: steering and handling

This paper investigates subjective assessments (SA) of vehicle handling and steering feel tests, both numerical and verbal, to understand drivers’ use of judgement scales, rating tendencies and spread. Two different test methods are compared: a short multi-vehicle first-impression test with predefined-driving vs the standard extensive single-vehicle free-driving tests, both offering very similar results but with the former saving substantial testing time. Rating repeatability is evaluated by means of a blind test. Key SA questions are identified by numerical subjective assessment autocorrelations and by generating word clouds from the most used terms in verbal assessments, with both methods leading to similar key parameters. The results exposed in this paper enable better understanding of SA, allowing improving the overall subjective testing and evaluation process, and improving the data collection and analysis process needed before identifying correlations between SA and objective metrics.     

驾驶辅助技术在事故预防中的应用效果

越来越多的车型都搭载了驾驶辅助系统,部分驾驶人对这类系统的实际效果持怀疑态度。本文通过调研国内外相关研究,对几类主流驾驶辅助系统的事故预防效果进行综述。与相同条件下未安装驾驶辅助系统的车辆对比,研究人员发现多数驾驶辅助系统在事故预防方面发挥了明显的作用,降低了相关的事故率、保险索赔率,其中前向和后向的自动紧急制动系统效果最为显著。此外,驾驶人对驾驶辅助系统的接受度以及响应度均会影响事故预防效果。     

Real time detection of driver attention: Emerging solutions based on robust iconic classifiers and dictionary of poses

Real time monitoring of driver attention by computer vision techniques is a key issue in the development of advanced driver assistance systems. While past work mostly focused on structured feature-based approaches, characterized by high computational requirements, emerging technologies based on iconic classifiers recently proved to be good candidates for the implementation of accurate and real-time solutions, characterized by simplicity and automatic fast training stages.In this work the combined use of binary classifiers and iconic data reduction, based on Sanger neural networks, is proposed, detailing critical aspects related to the application of this approach to the specific problem of driving assistance. In particular it is investigated the possibility of a simplified learning stage, based on a small dictionary of poses, that makes the system almost independent from the actual user.On-board experiments demonstrate the effectiveness of the approach, even in case of noise and adverse light conditions. Moreover the system proved unexpected robustness to various categories of users, including people with beard and eyeglasses. Temporal integration of classification results, together with a partial distinction among visual distraction and fatigue effects, make the proposed technology an excellent candidate for the exploration of adaptive and user-centered applications in the automotive field.     

螺旋匝道和螺旋桥的小客车行驶速度特征

为明确螺旋匝道和螺旋桥处的驾驶行为模式和汽车运行特征，在涪陵长江一桥、乌江二桥、重庆融侨大道和涪陵金凯环形高架4处地点开展螺旋匝道实车试验，用车载仪器采集自然驾驶状态下的汽车连续行驶轨迹、速度以及周围行驶环境等信息。基于自然驾驶数据，研究螺旋匝道范围内的速度变化模式、幅值特性以及影响因素。研究结果表明：单车道螺旋匝道的速度变化模式多样化，双车道螺旋匝道的行驶速度在整体上维持稳定，匝道范围内的连续升坡和降坡并未导致速度出现趋势性衰减和趋势性升高；螺旋匝道并入主线时，驾驶人在合流鼻之前有明显的、共性的减速行为，这与现行设计标准中的设计假定相反；除涪陵长江一桥之外，其余3处都是下行速度低于上行速度；螺旋匝道设计速度越低，实测速度与设计速度之间的偏离越严重，并且速度幅值离散化，因此不建议使用20 km·h^-1的匝道设计速度；螺旋匝道运行速度与匝道半径成正相关。     

基于VC的微视V200图像采集卡驱动及内存中图像截取

在VC环境下开发采集卡的驱动程序,可以方便地应用于其他程序中,避免重复开发,提高了软件开发的效率。在内存中获取采集卡捕获的图像并转换为标准的句柄接口,能够提高实时性、方便更进一步的图像处理。     

重视道路因素对道路交通安全的影响

对道路交通系统的客观分析后发现,在以往事故分析中对人、车、路三因素间的关系分析不足。针对此问题,对道路事故处理中过多偏重驾驶员因素进行了原因分析,然后通过计算分析指出道路因素应占有更大的比例,在未来道路交通安全分析中应该重视道路因素的影响。     

施工振动对房屋结构安全影响分析与鉴定

通过对振动打桩机系统的理论分析和土体振动分析,提出了施工振动对邻近房屋结构安全性影响分析的4种方法。结合民用房屋结构安全性鉴定的要求,提出了施工振动对邻近房屋结构安全性影响的鉴定基本原则。通过一个工程鉴定实例应用,验证了施工振动对邻近房屋建筑结构安全性影响鉴定基本原则的合理性。     

Windows 2000并口EPP模式驱动程序的设计与实现

Windows2000下，用户模式应用程序不能直接访问硬件设备，需要通过内核模式驱动程序实现。本文介绍PC机在Windows2000操作系统下，使用Nm9835芯片，完成并行端口EPP模式的数据和地址读写操作的WDM模型设备驱动程序的设计与实现过程，以及驱动程序与用户模式应用程序的通信机制。