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Impact Analysis of Public Transport Fare Adjustment on Travel Mode Choice for Travelers in Beijing

机译：北京公交票价调整对旅行者出行方式选择的影响分析

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The impact of a public transport fare adjustment on the travel mode choice for residents is studied in this thesis. Analyzing the macro temporal and spatial variation of public transport passenger flow characteristics before and after the fare adjustment, it was found that there was a great impact of fare adjustment on the travel of residents. Through a questionnaire survey, the influence level of the fare adjustment, and the characteristics of travel mode transfer for commuters and non-commuters were different. Based on the temporal and spatial feature vectors of smart card data for public transport travelers, the commuters' classification based on machine learning was proposed. Using massive public transit smart card data of about 13 million every day in Beijing, including rail, bus and public bicycles, the accurate classification of commuters and non-commuters was achieved, which proved that the classification accuracy reached 94.24%. Based on the accurate classification and significance analysis on the temporal and spatial trip characteristics of different types of public transport travelers, the effect difference of the public transport fare adjustment for the travel frequency, public transport travel mode choice of commuters or non-commuters was quantitatively analyzed. The results showed that, for public transport commuters, the proportion of travelers whose travel frequency using rail and bus obviously decreased was 14.90% and 25.47%, respectively, while 3.73% of commuters transferred from rail to bus. On the other hand, for non-commuters, the proportion of travelers whose travel frequency using rail and bus obviously decreased was 21.32% and 26.96%, respectively. The decreasing rate of rail travel frequency for non-commuters was greater than that for commuters, while the decreasing rate of bus travel frequency for two types of travelers was basically equal. The research conclusion provides scientific support and useful reference to the public transit network planning, operation management and policy implementation impact assessment.
机译：本文研究了公交票价调整对居民出行方式选择的影响。通过分析票价调整前后公共交通客流特征的宏观时空变化，发现票价调​​整对居民出行产生了很大的影响。通过问卷调查，票价调整的影响程度以及通勤者和非通勤者的出行方式转换特征都不同。基于公共交通旅客智能卡数据的时空特征向量，提出了基于机器学习的通勤者分类方法。使用北京每天约1300万条海量公共交通智能卡数据，包括铁路，公交车和公共自行车，实现了对通勤者和非通勤者的准确分类，证明分类准确率达到94.24％。在对不同类型的公共交通出行者时空旅行特征进行准确分类和显着性分析的基础上，定量分析了公共交通票价调整对出行频率，通勤者或非通勤者出行方式选择的影响差异。分析。结果表明，对于公共交通通勤者，使用铁路和公交车出行频率明显下降的旅行者比例分别为14.90％和25.47％，而通过铁路转乘公交车的通勤者比例为3.73％。另一方面，对于非通勤者，使用铁路和公交车出行频率明显下降的旅行者比例分别为21.32％和26.96％。非通勤者的铁路出行频率下降率大于通勤者，而两种类型的旅客的公共汽车出行频率下降率基本相等。研究结论为公交网络规划，运营管理和政策实施影响评估提供了科学的支持和有益的参考。

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