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行程时间服从混合高斯分布的车队离散模型
引用本文:姚志洪,蒋阳升,赵斌,朱娟秀,罗孝羚.行程时间服从混合高斯分布的车队离散模型[J].交通运输系统工程与信息,2017,17(2):97-104.
作者姓名:姚志洪  蒋阳升  赵斌  朱娟秀  罗孝羚
作者单位:西南交通大学a. 交通运输与物流学院;b. 综合交通运输智能化国家地方联合工程实验室,成都610031
基金项目:国家自然科学基金/National Natural Science of China (51578465,71402149);重庆市应用开发计划重点项目/ Key Project of Application and Development of Chongqing Municipality (cstc2014yykfB30003, 2015H01373); 西南交通大学拔尖创新人才培育/Outstanding Innovative Talents Fostering Fund of Southwest Jiaotong University (2016-2017).
摘    要:为充分描述异质交通流条件下的车队离散规律,为信号配时优化、公交优先控制提供理论基础.考虑异质交通流条件下车辆行程时间分布特点,采用混合高斯分布拟合车辆行程时间分布.基于此,从流量角度推导了异质交通流条件下车队流量离散模型.通过实际调查数据,分析了下游交叉口到达流率分布与上游交叉口离去流率分布之间的关系,并将本文模型与Robertson模型、实际数据进行比较分析.结果表明,本文模型能够更好地描述异质交通流条件下的车队离散规律,与Robertson模型相比,平均预测均方误差减少了27%.

关 键 词:交通工程  车队离散模型  混合高斯分布  异质交通流  行程时间  信号优化  
收稿时间:2016-07-28

Platoon Dispersion Model Based on Mixed Gaussian Distribution of Travel Time
YAO Zhi-hong,JIANG Yang-sheng,ZHAO Bin,ZHU Juan-xiu,LUO Xiao-ling.Platoon Dispersion Model Based on Mixed Gaussian Distribution of Travel Time[J].Transportation Systems Engineering and Information,2017,17(2):97-104.
Authors:YAO Zhi-hong  JIANG Yang-sheng  ZHAO Bin  ZHU Juan-xiu  LUO Xiao-ling
Institution:a. School of Transportation and Logistics; b. National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 610031, China
Abstract:To describe the law of platoon dispersion under the condition of heterogeneous traffic flow adequately, and provide theoretical support for signal timing optimization and bus priority control. The characteristic of vehicle’s travel time distribution in heterogeneous traffic flow is considered. The mixed Gaussian distribution is used to fit vehicle’s travel time distribution. Based on this, the platoon dispersion model in heterogeneous traffic flow is proposed from the perspective of traffic flow. Later, the relationship of the arrival flow rate of the downstream intersection and the depart flow rate of the upstream intersection is analyzed using the proposed model by field collected data, with comparison to those of Robertson model and the actual data. The results show that, the proposed model can better describe the law of dispersion in heterogeneous traffic flow, and the mean squared error of prediction is reduced by about 27%, compared with Robertson model.
Keywords:traffic engineering  platoon dispersion model  mixed Gaussian distribution  heterogeneous traffic flow  travel time  signal optimization  
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