摘要
通过对浮动车定位数据情况的分析,可知大部分速度估计算法仅适用于采样时间间隔不大于行程时间的情况,为在相同浮动车比例以及采样时间间隔的条件下,提高数据利用率,以提高速度估计结果的路网覆盖率,提出两种速度估计算法:车辆跟踪法、速度-距离积分法,并给出路段区间平均速度自适应估计模型。使用真实交通流OD数据进行仿真,结果表明在相同的浮动车定位数据情况下,使用自适应估计模型可比速度-时间积分法获得更高的路网覆盖率,且所得的速度估计结果的误差与速度-时间积分法处于同一水平。
The analysis of probe vehicle data shows that most algorithms of speed estimation are only applied to the condition of sampling interval is less than travel time.For improving the data utilization and the road network coverage of speed estimating results in the same condition of probe vehicle population as well as the sampling interval,two kinds of speed estimation algorithms,i.e.,vehicle tracking algorithm,speed-distance integral algorithm,were presented.Then,an adaptive estimation model for obtaining segment average speed estimation was presented.The simulation result with true OD input shows that the adaptive estimation model can obtain higher road network coverage comparing with the speed-time integral algorithm without increasing the error in the case of the same probe vehicle data.
出处
《公路交通科技》
CAS
CSCD
北大核心
2011年第6期128-135,共8页
Journal of Highway and Transportation Research and Development
基金
广东省科技厅工业攻关计划项目(2007A010100012)
