Since bus inter-stop travel times (BISTTs) are significant components of the route travel time, providing accurate BISTTs can effectively improve the route travel time prediction accuracy. In this paper we propose a novel prediction model for BISTTs, which takes five factors as input variables: stop distance, historical inter-stop travel times, number of intersections, intersection traffic volumes, and intersection signal timing schemes. The Lagrange Multiplier (LM) test is conducted to check autocorrelation in the model residuals. Cases of two bus routes in Harbin have been studied based on field data. Mean average errors for both bus routes are smaller than 8%, indicating the high prediction accuracy in predicting BISTTs. Sensitivity analysis is conducted and results show that excluding any one of those five factors would cause the failure of the model in the LM test, indicating that the presence of all factors is required to maintain the validity of this model.

中文翻译：

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考虑信号交叉口影响的公交站间行程时间预测模型

由于公交站点间旅行时间（BISTTs）是路线旅行时间的重要组成部分，提供准确的BISTTs可以有效提高路线旅行时间预测的准确性。在本文中，我们提出了一种新的 BISTT 预测模型，它以五个因素作为输入变量：停车距离、历史停车间旅行时间、交叉口数量、交叉口交通量和交叉口信号配时方案。进行拉格朗日乘数 (LM) 检验以检查模型残差中的自相关性。基于现场数据对哈尔滨两条公交线路的案例进行了研究。两条公交路线的平均误差均小于 8%，表明预测 BISTT 的预测精度很高。