Abstract
Here, we aim to investigate the relationship between characteristics of railway stations and errors in train stop positions. Hence, two kinds of logistic regression analysis were conducted with two different objective variables: train stations with or without the occurrence of delays in braking manipulations and stations with or without the occurrence of misrecognition of stop positions. The explanatory variables included velocities near stations, braking manipulations, and features of the stations. Logistic regression analysis revealed that the delay in braking manipulations was significantly associated with the ratio of the maximum brake notch and the mean of velocities at 200 m before train stops. The delay in braking manipulations occurred frequently at stations where the train velocities when approaching the stations were high and the maximum brake notch was frequently used. Logistic regression analysis further revealed that the misrecognition of stop positions was significantly associated with the existence of a stop sign for four or six vehicles and where there were many stopping velocity patterns. A stop sign before a stop position and decreasing train velocity for a caution signal caused the misrecognition of stop positions.
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Suzuki, D., Suzuki, A., Shimano, K., Kiyota, K., Kakizaki, Y. (2020). Analysis of Driving Performance Data Considering the Characteristics of Railway Stations. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1212. Springer, Cham. https://doi.org/10.1007/978-3-030-50943-9_45
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DOI: https://doi.org/10.1007/978-3-030-50943-9_45
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