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A ROBUST OPTIMIZATION APPROACH TO PUBLIC TRANSIT MOBILE REAL-TIME INFORMATION

机译：公共交通移动实时信息的鲁棒优化方法

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近几年大量手机实时公交应用涌入市场，公交乘客可提前査询出行路线以及所乘车辆的到站时间。已有研究表明，精确的公交实时信息可以降低乘客候车时的焦虑感，以及乘客的候车时间。不精确或者错误的公交实时信息不仅会误导乘客出行，还会增加乘客对公交的不良印象。另外，已有关于公交实时信息优化的研究多是侧重公交实时到站时间或者公交运行时间预测，尚未从完善信息内容的角度考虑优化公交实时信息。基于此，论文提出了一种鲁棒优化的方法，针对单条公交线路的实时到站信息进行优化。通过鲁棒线性优化，考虑公交客流的不确定性，如突发客流等，在现有的公交实时到站时间预测中增加运行延误信息，以最大节省乘客的出行时间成本为目标，建立公交到站时间预测优化模型，使实时公交APP提供的公交实时信息更加完善。最后分别运用上海一条市域公交和一条市内公交的运行信息对模型进行验证。验证结果证明了模型的有效性以及模型存在的不足。%In the past few years, numerous mobile applications have made it possible for public transit passengers to find routes and learn about the expected arrival times of their transit vehicles. Previous studies show that provision of accurate real-time bus information is vital to passengers for reducing their anxieties and wait times at bus stops. Inadequate and/or inaccurate real-time information not only confuses passengers but also reinforces the bad image of public transit. However, almost all methods of real-time information optimization are aimed at predicting bus arrival or travel times. In order to make up for the lack of information accuracy, this paper proposes a new approach to optimize mobile real-time information for each transit route based on robust linear optimization. An error estimation is added to current bus arrival time information as a new element of mobile bus applications. The proof process of the robust optimization model is also presented in this paper. In the end, the model is tested on two comparable bus routes in Shanghai. The real-time information for these two routes was obtained from Shanghai Bus, a mobile application used in Shanghai City. The test results reflect the validity, disadvantages, and risk costs of the model.
机译：近几年大量手机实时公交应用涌入市场，公交乘客可提前查询出行路线以及所乘车辆的到站时间。已有研究表明，精确的公交实时信息可以降低乘客候车时的焦虑感，以及乘客的候车时间。不精确或者错误的公交实时信息不仅​​会误导乘客出行，还会增加乘客对公交的不良印象。另外，已有关于公交实时信息优化的研究多是侧重公交实时到站时间或者公交运行时间预测，尚未从完善信息内容的角度考虑优化公交实时信息。基于此，论文提出了一种鲁棒优化的方法，针对单条公交线路的实时到站信息进行优化。通过鲁棒线性优化，考虑公交客流的不确定性，如突发客流等，在现有的公交实时到站时间预测中增加运行延误信息，以最大节省乘客的出行时间成本为目标，建立公交到站时间预测优化模型，使实时公交APP提供的公交实时信息更加完善。最后分别运用上海一条市域公交和一条市内公交的运行信息对模型进行验证。验证结果证明了模型的有效性以及模型存在的不足。 %In the past few years, numerous mobile applications have made it possible for public transit passengers to find routes and learn about the expected arrival times of their transit vehicles. Previous studies show that provision of accurate real-time bus information is vital to passengers for reducing their anxieties and wait times at bus stops. Inadequate and/or inaccurate real-time information not only confuses passengers but also reinforces the bad image of public transit. However, almost all methods of real-time information optimization are aimed at predicting bus arrival or travel times. In order to make up for the lack of information accuracy, this paper proposes a new approach to optimize mobile real-time information for each transit route based on robust linear optimization. An error estimation is added to current bus arrival time information as a new element of mobile bus applications. The proof process of the robust optimization model is also presented in this paper. In the end , the model is tested on two comparable bus routes in Shanghai. The real-time information for these two routes was obtained from Shanghai Bus, a mobile application used in Shanghai City. The test results reflect the validity, disadvantages, and risk costs of the model.

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