基于浮动车数据的路网交通状态宏微观评价指标研究  

Research on Macro and Micro Evaluation Indexes of Road Network Traffic State Based on Floating Car Data

作　　者：张立立 王心哲 姚迪 于沛 张海波[3] 王力[3] Zhang Lili;Wang Xinzhe;Yao Di;Yu Pei;Zhang Haibo;Wang Li(College of Information Engineering,Beijing Institute of Petrochemical Technology,Beijing 102617,China;China Fire and Rescue Academy,Beijing 102202,China;Beijing Key Laboratory of Urban Intelligent Traffic Control Technology,North China University of Technology,Beijing 100144,China)

机构地区：[1]北京石油化工学院,信息工程学院,北京102617 [2]中国消防救援学院,北京102202 [3]北方工业大学城市交通智能控制技术北京市重点实验室,北京100144

出　　处：《南开大学学报（自然科学版）》2023年第3期27-33,共7页Acta Scientiarum Naturalium Universitatis Nankaiensis

基　　金：国家重点研发计划(2017YFC0821102);北京自然科学基金(4214070);北京市科学技术协会2021-2023年度青年人才托举工程(BJKX2021045);北京石油化工学院交叉科研探索(BIPTCSF-006);北方工业大学北京城市治理研究基地项目(21CSZL34);宁夏自然科学基金(2022AAC03757)。

摘　　要：传统断面检测器存在检测范围有效、完好率不足等实际问题无法有效感知和辨识路网交通状态,以浮动车数据为基础,研究和设计了路网交通宏微观评价指标,并提出基于灰色关联熵的路网宏微观交通状态评价方法,进一步通过引入宏观基本图平移的特性扩展了交通状态评价方法.最后,利用北京市昌平区政府街主干线数据对所提方法进行了验证,结果表明所提方法能够有效判别路网的宏微观交通状态.The traditional cross-section detector has some practical problems,such as an effective detection range and insufficient integrity rate,which can not effectively perceive and identify the traffic status of the road network.Based on the floating car data,the macro and micro evaluation index of road network traffic is studied and designed.A macro and micro traffic state evaluation method of road network based on grey relational entropy are proposed.Furthermore,the traffic condition evaluation method is extended by introducing the characteristics of macroscopic basic graph translation.Finally,the proposed method is verified by the trunk data of government streets in Changping district,Beijing,and the results show that the proposed method can effectively distinguish the macro and micro traffic state of the road network.

关 键 词：智能交通 浮动车 微观评价指标 宏观评价指标 状态熵 

分 类 号：U121[交通运输工程]