Probabilistic traffic forecast method based on comprehensive transport information platform
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摘要: 以交通综合信息平台为数据支撑, 考虑交通指数发布对交通预测的影响, 应用模式匹配和概率统计方法构建了概率交通预报方法的流程框架, 研究了概率交通预报的2项关键实现技术, 包括3级交通数据融合方法和交通指数发布内容。算例结果表明: 概率交通预报使主路径和替代路径的饱和度差值从40%降低到23%;由于概率交通预报方法在考虑交通指数发布对出行行为影响的基础上对交通预测结果进行了修正, 所以提高了交通预报的可信度, 使路网交通负荷趋于均衡。Abstract: Taking the effects of traffic index release on traffic forecast into consideration, a procedure frame of traffic forecast was established based on comprehensive transport information platform (CTIP), mode matching method and probability statistics method.Two key implementation technologies were studied, including three-level traffic data fusion and traffic index release.Example result shows that probabilistic traffic forecast method reduces the saturation gap of main road and alternative road from 40% to 23%, improves the confidence of traffic forecast by considering the influences of traffic index release on travel behavior, and can balance OD distribution of road network effectively.
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表 1 交通状态评价体系
Table 1. Evaluation system of traffic state
交通状态评价层次 交通预报范围 数据融合层次 交通状态评价指标 微观 重要节点、关键路段 参数级 小时流量、饱和度、行驶速度 中观 主要通道 特征级 小时流量、行程速度、行程时间、拥堵状态 宏观 区域 决策级 OD分布、路网服务水平、区域拥堵范围、交通事件 
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表 2 常态交通预报时交通指数
Table 2. Traffic indices of normal traffic forecast
预报时段 预报范围 交通指数发布内容 长期 微观 高峰及平峰时段的饱和度范围及概率水平 中观 高峰及平峰时段的饱和度范围及概率水平 宏观 高峰及平峰时段拥堵面积百分比范围及概率水平 短期 微观 延误等级及概率水平 中观 行程时间范围及概率水平 宏观 拥堵范围及概率水平
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[1] 关志超, 林群, 文锦添, 等. 深圳"城市交通仿真与公用信息平台"设计与实践[J]. 中山大学学报: 自然科学版, 2005, 44 (S2): 178-183. https://www.cnki.com.cn/Article/CJFDTOTAL-ZSDZ2005S2043.htmGUANZhi-chao, LI N Qun, WENJin-tian, et al. Design anddevelopment of Shenzhen urban traffic si mulation and publictransport information platform[J]. Acta Scientiarum Natur-alium Universitatis Sunyatseni, 2005, 44 (S2): 178-183. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZSDZ2005S2043.htm [2] 郭伟, 姚丹亚, 付毅, 等. 区域交通流特征提取与交通状态评估方法研究[J]. 公路交通科技, 2005, 22 (7): 101-104, 114. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK200507026.htmGUO Wei, YAO Dan-ya, FU Yi, et al. Study onthe methodfor regional traffic flow feature extraction and traffic statusevaluation[J]. Journal of Highway and TransportationResearch and Development, 2005, 22 (7): 101-104, 114. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK200507026.htm [3] 李瑞敏, 史其信. 基于虚拟数据仓库和XML的城际交通综合信息平台[J]. 清华大学学报: 自然科学版, 2005, 45 (6): 745-748. doi: 10.3321/j.issn:1000-0054.2005.06.008LI Rui-min, SHI Qi-xin. Inter-city transport integratedinformation platform based on virtual data warehouse andXML[J]. Journal of Tsinghua University: Science andTechnology, 2005, 45 (6): 745-748. (in Chinese) doi: 10.3321/j.issn:1000-0054.2005.06.008 [4] 姬杨蓓蓓, 杜豫川, 孙立军. 上海市城市道路交通信息平台系统分析与设计[J]. 交通与计算机, 2006, 24 (1): 54-57. https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS200601015.htmJI-YANG Bei-bei, DU Yu-chuan, SUN Li-jun. Analysis anddesign of traffic information platformsystemof urban roadinShanghai City[J]. Computer and Communications, 2006, 24 (1): 54-57. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS200601015.htm [5] 章威, 徐建闽. 广州市ITS共用信息平台软件体系结构研究[J]. 交通运输系统工程与信息, 2006, 6 (4): 119-124. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT200604023.htmZHANG Wei, XU Jian-min. Software system structure ofITS common information platform in Guangzhou City[J]. Journal of Transportation Systems Engineering and Informa-tion Technology, 2006, 6 (4): 119-124. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT200604023.htm [6] 杨兆升, 保丽霞, 朱国华. 深圳市综合交通信息平台系统分析与设计[J]. 公路交通科技, 2005, 22 (2): 100-103. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK200502027.htmYANG Zhao-sheng, BAO Li-xia, ZHU Guo-hua. Analysisand design of integrated traffic information systemin ShenzhenCity[J]. Journal of Highway and Transportation Researchand Development, 2005, 22 (2): 100-103. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK200502027.htm [7] CAREY M, MCCARTNEY M. Behavior of a whole-linktravel ti me model used in dynamic traffic assignment[J]. Transportation Research Part B, 2002, 36 (1): 83-95. doi: 10.1016/S0191-2615(00)00039-4 [8] SOHNS Y, LEE S H. Data fusion, ensemble and clusteringto i mprove the classification accuracy for the severity of roadtraffic accidents in Korea[J]. Safety Science, 2003, 41 (1): 1-14. doi: 10.1016/S0925-7535(01)00032-7 [9] CHOI K. Data fusion methodology for link travel ti me esti-mation for advanced traveler information system[J]. KSCEJournal of Civil Engineering, 1999, 3 (1): 1-14. [10] CHOI K, CHUNG Y. Adata fusion algorithmfor esti matinglink travel ti me[J]. Intelligent Transportation Systems, 2002, 7 (3): 235-260. [11] JOHN NI, VANEET S. Data fusion of fixed detector andprobe vehicle data for incident detection[J]. Computer-AidedCivil and Infrastructure Engineering, 1998, 13 (5): 329-337. -
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