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Thorsten Neumann 《先进运输杂志》2014,48(8):1087-1106
Probe vehicle data (PVD) are commonly used for area‐wide measurements of travel time in road networks. In this context, travel times usually refer to fixed edges of an underlying (digital) map. That means measured travel times have to be transformed into so‐called link travel times first. This paper analyzes a common method being applied for solving this task (distance‐based travel time decomposition). It is shown that, in general, its inherent imprecision must not be neglected. Instead, it might cause a serious misinterpretation of data if potential errors in the context of travel time decomposition are ignored. For this purpose, systematic as well as maximum deviations between “decomposed” and “true” link travel times are mathematically analyzed. By that, divergent statements in the literature about the accuracy of PVD are harmonized. Moreover, conditions for the applicability of the so‐called distance‐proportion method are derived depending on the permitted error level. Three examples ranging from pure theory to real world confirm the analytical findings and underline the problems resulting from distance‐based travel time decomposition at local level, for example, at individual intersections. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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选用北京培特公司技术开发的HT8002AC井式炉渗碳/碳氮共渗工艺过程计算机控制系统,技术改进2台RJJ-75-9TG井式气体渗碳炉的渗碳控制系统,实现计算机对整个工艺渗碳全过程的模拟控制,并时刻跟踪和修正现场设备参数的动态变化。提升了渗碳件的产品质量,确保汉德公司两到三年之内的自制件,能够达到国际出口标准。 相似文献
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AbstractIn recent years, there has been a growing desire for the use of probe vehicle technology for congestion detection and general infrastructure performance assessment. Unlike costly traditional data collection by loop detectors, wide area detection using probe-based traffic data is significantly different in terms of the nature of data collection, measurement technique, coverage, pricing, and so on. Although many researches have studied probe-based data, there remains critical questions such as data coverage and penetration over time, or the influential factors in the accuracy of probe data. This research studied probe-sourced data from INRIX, to profoundly explore some of these questions. First, to explore coverage and penetration, INRIX real-time data was illustrated temporally over the entire state of Iowa, demonstrating the growth in real-time data over a 4-year timespan. Furthermore, the availability of INRIX real-time and historical data based on type of road and time of day, were explored. Second, a comparison was made with Wavetronix smart sensors, commonly used sensors in traffic management, to explore INRIX’s speed data quality. A statistical analysis on the behavior of INRIX speed bias, identified some of the influential factors in defining the magnitude of speed bias. Finally, the accuracy and reliability of INRIX for congestion detection purposes was investigated based on the road segment characteristics and the congestion type. Overall, this work sheds light onto some of the less explored aspects of INRIX probe-based data to help traffic managers and decision makers in better understanding this source of data and any resultant analyses. 相似文献
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该文结合城市道路旧城改建或道路拓宽所采取的人非共板断面工程案例,在分析人非共板断面优点及存在问题的基础上,提出了科学运用人非共板的观点,并对人非共板的适用范围进行了探讨。 相似文献
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针对构件化软件测试存在的一些问题,提出一种基于遗传算法和探针模型的构件化软件测试模型.该模型通过探针实现测试程序与构件的交互,然后采用遗传算法对构件测试用例进行优化,提高r测试效率和测试覆盖率. 相似文献
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AbstractPath travel time estimation for buses is critical to public transit operation and passenger information system. State-of-the-art methods for estimating path travel time are usually focused on single vehicle with a limited number of road segments, thereby neglecting the interaction among multiple buses, boarding behavior, and traffic flow. This study models path travel time for buses considering link travel time and station dwell time. First, we fit link travel time to shifted lognormal distributions as in previous studies. Then, we propose a probabilistic model to capture interactions among buses in the bus bay as a first-in-first-out queue, with every bus sharing the same set of behaviors: queuing to enter the bus bay, loading/unloading passengers, and merging into traffic flow on the main road. Finally, path travel time distribution is estimated by statistically summarizing link travel time distributions and station dwell time distributions. The path travel time of a bus line in Hangzhou is analyzed to validate the effectiveness of the proposed model. Results show that the model-based estimated path travel time distribution resembles the observed distribution well. Based on the calculation of path travel time, link travel time reliability is identified as the main factor affecting path travel time reliability. 相似文献