基于行车大数据的路面性能及其行车舒适性评价理论和方法研究

A large-scale network of highways and urban roads have been built in China. Under such situation, the real-time monitoring, inspection and evaluation, and timely maintenance of road facilities will have great social and economic significance. Although existing inspection and evaluation methods of pavement performance are basically fast and unified, they have some shortcomings such as narrow coverage and low frequency due to the lack of intelligence and informatization. Thus, existing methods cannot be applied to achieve intelligent, dynamic and real-time monitoring and evaluation of pavement conditions and driving comfort. In another word, existing pavement performance inspection and evaluation methods cannot meet the requirements of modern traffic development...This research project was aimed at introducing emerging technologies to improve intelligence and informatization level of pavement maintenance & management; conducting theoretical, technical and methodological studies of intelligent sensing-based pavement damage identification; and carrying out study of the relationship between comprehensive pavement performance and driving comfort based on subjective and objective evaluation. Based on above studies, the study of evaluation theories, indicators and methods of pavement maintenance and driving comfort based on big data of driving, mobile communication technologies and internet technologies was completed. In this project, new theories and technologies of intelligent sensing-based pavement driving state monitoring and evaluation as well as theories and methods of pavement performance and driving comfort evaluation based on big data of driving were developed. At last, real-time intelligent monitoring and evaluation of pavement performance and driving comfort were realized to improve the modernization level of pavement management & maintenance.

我国已经建成了庞大的公路和城市道路网络，对道路设施的实时监测、检测评价和养护维修具有重要的社会和经济意义。路面性能检测评价基本实现了快速化和统一化，但由于智能化和信息化不足，路面性能的小覆盖面、低频次检测无法对路面状况及其行车舒适性进行智能、动态、实时的监测和评估，不能适应现代交通发展的要求。.本课题立足于应用新兴技术提升路面养护管理的智能化和信息化水平，开展基于智能感知的路面性能识别理论、技术和方法研究，开展基于主客观评价的路面综合性能与路面行车舒适性关系的研究。在此基础上，开展基于行车大数据、移动通信技术、互联网技术的路面性能及其行车舒适性的评价理论、评价指标和评价方法研究。本课题将开发基于智能感知的路面行车状态监测和评价的新理论和新技术、基于行车大数据的路面性能及其行车舒适性的评价理论和方法，实现对路面性能及其行车舒适性的实时、智能监测和评价，提高道路路面管理和养护的现代化水平。

截至2020年底，我国公路里程达到501.23万km，2020年公路养护里程492.63万km，占公路总里程的97.60%，我国道路交通基础设施已经进入建养并重、甚至养护工作更加重要的新时代，道路路面检测评价和养护维修将成为我国交通基础设施建设的首要任务。在道路路面技术状况检测评价方面，我国已经基本实现了从人工检测向自动化检测的转变，但尚存在检测频率低、检测覆盖面小、检测成本高等问题，路面性能的智能化检测评价和监测是今后道路建设面临的一个技术难题。.本课题借鉴和依托新兴智能感知技术、信息传输技术和大数据理论，以道路路面技术状况和行车舒适性评价的智能化以及路面养护管理的科学化为目标，开展了基于行车大数据的路面性能及其行车舒适性评价理论和方法研究。本课题以得到普及应用的智能手机作为智能感知设备，开发了智能手机APP，用于采集行车过程中的GPS位置、速度、三向振动加速度等行车大数据，利用4G网络将APP采集的行车数据上传至课题组开发的“道路路面状况监测分析平台”实验系统。基于开展的大量实际道路路面行车实验，探讨了路面行车舒适性的综合表征方法，研究了基于行车振动的路面平整度和车辙的预测方法。“道路路面状况监测分析平台”实验系统接受手机APP上传的行车数据信息并对原始数据进行处理，利用本课题开发的预测模型分析计算，得到道路路面平整度、车辙和行车舒适性评价结果，并按不同的评价等级显示在地图上。本课题开展了系统的应用工作，初步验证了利用行车大数据进行路面行车舒适性评价和路面技术性能预测的可行性，本课题初步建立了一套基于行车大数据的路面技术状况分析方法和系统。.本课题在采集行车振动等数据的智能手机APP研发、基于手机APP采集行车振动大数据的路面行车舒适性评价指标和方法、基于手机APP采集行车振动大数据的路面RQI、IRI、RD预测模型构建等方面，取得了创新性的成果，为道路路面的养护决策提供了新的辅助手段，在智能交通、智慧城市建设、自动驾驶等领域具有广阔的应用前景。