摘要:The existing Big Data of transport flows and railway operations can be mined through advanced statistical analysis and machine learning methods in order to describe and predict well the train speed, punctuality, track capacity and energy consumption. The accurate modelling of the real spatial and temporal distribution of line and network transport, traffic and performance stimulates a faster construction and implementation of robust and resilient timetables, as well as the development of efficient decision support tools for real-time rescheduling of train schedules. In combination with advanced train control and safety systems even (semi-.) automatic piloting of trains on main and regional railway lines will become feasible in near future.
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北京交通大學(xué)學(xué)報雜志, 雙月刊,本刊重視學(xué)術(shù)導(dǎo)向,堅持科學(xué)性、學(xué)術(shù)性、先進性、創(chuàng)新性,刊載內(nèi)容涉及的欄目:數(shù)字經(jīng)濟研究_數(shù)字經(jīng)濟發(fā)展、創(chuàng)新與治理、應(yīng)用經(jīng)濟研究、管理研究、物流研究、馬克思主義研究、國家社會治理研究等。于1975年經(jīng)新聞總署批準(zhǔn)的正規(guī)刊物。