摘要
浮动车技术是目前常用的获取道路交通信息技术手段之一,而出租车GPS数据是该技术重要数据来源,但其本身存在诸多不足。为更好地利用出租车GPS数据,文中提出了在定位误差、低频采样、数据量少等因素影响下的行程速度估计方法。首先结合城市复杂路段情况,提出基于车流方向、路段可达性、速度等约束条件下的实时地图匹配算法,引入反向检查机制对不确定点进行修正;然后针对出租车运营特性,建立了有效数据获取模型,并提出低频采样影响下的行程速度估计算法;最后利用北京出租车数据进行计算比较。结果表明了该方法的可用性,能满足道路状态判断的一般需求。
Floating car data technology is one of the techniques currently used to get traffic information, and GPS data of Taxi is an import source of it,but with many deficiencies. In order to availably utilize GPS data of Taxi, a travel speed estimation method under the influ- ence of all kinds of external factors is presented in the paper. First, a map matching algorithm based on direction of traffic,road accessibil- ity, speed and reverse check mechanism is presented to solve the problem of complex sections, introducing reverse check mechanism to modify the point of uncertainty. Second, the effective data acquisition model is established and the travel speed estimation algorithm under influence of low frequency sampling is presented. Finally, make a comparison using the Beijing Taxi data. The results verify the feasibility of this algorithm, which can well meet the requirements of road situation judgment.
出处
《计算机技术与发展》
2015年第7期15-19,共5页
Computer Technology and Development
基金
国家自然科学基金资助项目(91118008)
