基于移动源数据的城市快速交通事件检测W-CUSUM算法与评价
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摘要
交通事件是引发城市路网中各种偶发性拥挤的关键因素,在造成交通延误、交通设施服务效率下降、交通使用者利益损失的同时,也对交通安全、交通环境等产生重要的影响。城市快速路是城市快速交通发展的趋向和城市路网主骨架,对城市快速路的交通事件进行快速、有效的检测和响应,既是快速路交通管理与控制的重要组成部分,同时也是降低事件损失、减少路网交通拥堵的有效方法。同时,移动检测技术的日益发展和成熟也为交通事件自动检测(Automatic Incident Detection,简称AID)提供了新的实时、动态、准确的交通流信息。
本文的研究目的在于提出基于移动源数据的城市快速路交通事件自动检测算法,同时对算法的性能进行评价与验证,并提出算法的实施方法,从而为交通管理者进行城市快速路网的事件检测、管理和响应以及事件检测算法的评价提供新的方法和思路。
本文的主要研究成果及结论包括：
1、现有AID算法主要基于固定源数据开发,存在误报率高、实际应用效果不佳等缺陷,鉴于此,本文提出了基于移动源数据的W-CUSUM交通事件自动检测算法。该算法充分考虑了移动源数据的采集特点及事件条件下快速路交通流的时空特性,并采用具有时频分析特性的小波分析方法与基于似然比的CUSUM算法相结合的思想,使得所开发的W-CUSUM算法在改善所用数据源质量的同时,也大大提高了事件检测的准确性和可靠度。
2、现有的误报率指标未能直观、有效的反映事件检测算法的误报情况,同时传统的算法性能包络曲线只能定性、粗略的描述算法的检测性能,缺乏对事件检测算法的综合、量化评价。鉴于此,本文首先提出了基于时间和空间指数的误报率指标,使得该指标与传统的误报率指标相比更具有直观性和实用性；在此基础上,进一步引入期望成本的概念,将检测率和误报率指标相结合,建立了基于期望成本的事件检测综合评价指标。该综合指标不仅能够实现不同AID算法性能的综合、量化评价及比选,还可以用于确定不同AID算法的最优检测阈值及最优检测性能点,从而为交通管理者进行算法的比选以及算法参数的标定提供了有效的技术支持。
3、分别利用仿真数据和实际数据对W-CUSUM算法进行了评价和比较。分析了不同影响因素下W-CUSUM算法性能的差异,并将所提出的W-CUSUM算法与现有的SND算法、CUSUM算法、UCB算法进行了性能对比。结果表明：(1)不同阻塞车道数条件下W-CUSUM算法性能的差异最为明显,影响最不明显的是事件的持续时间；(2)相对于SND算法、CUSUM算法和UCB算法而言,W-CUSUM算法的检测性能更优,优化程度分别提高了33.7%、19.5%和38.3%。
4、基于实验交通工程法(ETEM),提出了面向事件检测的移动源数据样本量确定模型,弥补了现有方法难以针对事件检测进行移动源数据样本量研究的不足,并通过仿真实例研究得出了满足事件检测一定精度水平所需要的路网浮动车比例以及较优的事件检测间隔,从而为确定面向事件检测的浮动车合理发展规模和检测间隔提供了有效的建议。
5、建立了基于分层结构的事件检测多源数据融合模型。在所建的融合模型中,充分考虑到了各种可用数据源所包含的事件信息特性,并将W-CUSUM算法与神经网络模型以及交通决策者的经验有效的结合起来,一方面既增强了W-CUSUM算法在实际应用中的灵活性和可拓展性,同时也为进一步提高事件检测算法的准确性和可靠性奠定了坚实的方法与理论基础。
6、从系统的角度,提出了W-CUSUM事件检测算法的实施框架与流程,对事件检测系统开发、安装及运行的整个过程进行了具体的阐述和建议,从而对W-CUSUM事件检测算法从理论研究到实际应用建立了相应的方法和流程。
Traffic incidents are a primary contributor to various unexpected congestions, resulting in traffic delays, declining of traffic infrastructure service efficiency, and loss of traffic users' benefits, and having a considerable impact to the traffic safety and environment as well. A prompt and reliable detection of and a quick response to the traffic incident on urban expressways, which represent the trend of the rapid urban infrastrure development and the backbone of the urban transportation network, is not only an important component of traffic management and control of urban expressways, but an effective way to decrease the losses resulted from the incident and reduce the traffic congestion as well. Meanwhile, the continuing development and maturity of mobile traffic detection techniques are now able to provide new real-time, dynamic and accurate traffic information for incident detection.
The purpose of this dissertation is to develop, evaluate, validate and implement an automatic incident detection (AID) algorithm for urban expressways based on mobile source traffic data, which provides a new approach for the detection and management of, and response to the traffic incidents on urban expressways as well as an evaluation method of AID algorithms. The research in this dissertation consists of the following accomplishments and contributions:
1. Existing AID algorithms are mainly developed based on fixed detectors, which have such shortcomings as high false alarm rate, and poor application performance. In this context, this research proposes an AID algorithm, called W-CUSUM algorithm, for urban expressways based on mobile source data. In the proposed algorithm, the feature of the mobile source data and the temporal-spatial characteristics of the traffic flow on urban expressways under incidents are fully considered by combining the wavelet analysis method and CUSUM approach, which improve the quality of the data, thus greatly increase the accuracy and reliability of the incident detection.
2. The existing false alarm rate index could hardly reflect the false alarm situation directly and effectively, and the traditional performance envelop curve can only give a qualitative and rough description of the performance, which result in a lack of comprehensive and quantitative evaluation of the AID algorithms. Therefore, this research first proposes a new false alarm rate based on temporal and spatial index, and then establishes a comprehensive index based on expected cost by integrating the indices of detection rate and false alarm rate. The proposed index based on expected cost can not only provide the comprehensive and quantitative evaluation and comparison for various AID algorithms, but be used for determinating the optimal detection threshold and performance point of an algorithm as well. Thus, it gives traffic managers an effective technical approach to compare, select and calibrate the AID algorithms.
3. The proposed W-CUSUM algorithm is evaluated and compared by using both simulation data and real-world data. By analyzing the performance of W-CUSUM algorithm under different influential factors and comparing W-CUSUM algorithm with SND, CUSUM and UCB algorithms, it is found that:(1) the number of blocked lanes has the largest effect on the performance of W-CUSUM algorithm, while the incident duration has little effect on the performance of W-CUSUM algorithm; (2) W-CUSUM algorithm performs better than SND, CUSUM, and UCB algorithms with an improvement of 33.7%,19.5% and 38.3% respectively.
4. A model for determining the mobile source data sample size for incident detection is developed based on the Experimental Traffic Engineering Methodology (ETEM), which overcomes the shortcomings of existing methods. According to the simulation case study, the reasonable percentage of floating cars in road networks and the optimal detection interval under certain accuracy of incident detection are obtained.
5. A multi-source data fusion model for incident detection based on hierarchical structure is developed by fully considering the characteristics of the incident information contained in various available data sources and integrating W-CUSUM algorithm, neural network model and the experiences of traffic decision-makers. The proposed model not only enhances the flexibility and expandability of W-CUSUM algorithm for application, but also provides a pratical methodology for improving the accuracy and reliability of the W-CUSUM algorithm.
6. A framework for implementing the W-CUSUM algorithm is established using a systematic and integrated approach, in which the development, installation, and operation of the AID system are presented in details in order to provide an overall methodological system for the W-CUSUM algorithm to transition from a theoretical study to practical applications.
本文的研究目的在于提出基于移动源数据的城市快速路交通事件自动检测算法,同时对算法的性能进行评价与验证,并提出算法的实施方法,从而为交通管理者进行城市快速路网的事件检测、管理和响应以及事件检测算法的评价提供新的方法和思路。
本文的主要研究成果及结论包括：
1、现有AID算法主要基于固定源数据开发,存在误报率高、实际应用效果不佳等缺陷,鉴于此,本文提出了基于移动源数据的W-CUSUM交通事件自动检测算法。该算法充分考虑了移动源数据的采集特点及事件条件下快速路交通流的时空特性,并采用具有时频分析特性的小波分析方法与基于似然比的CUSUM算法相结合的思想,使得所开发的W-CUSUM算法在改善所用数据源质量的同时,也大大提高了事件检测的准确性和可靠度。
2、现有的误报率指标未能直观、有效的反映事件检测算法的误报情况,同时传统的算法性能包络曲线只能定性、粗略的描述算法的检测性能,缺乏对事件检测算法的综合、量化评价。鉴于此,本文首先提出了基于时间和空间指数的误报率指标,使得该指标与传统的误报率指标相比更具有直观性和实用性；在此基础上,进一步引入期望成本的概念,将检测率和误报率指标相结合,建立了基于期望成本的事件检测综合评价指标。该综合指标不仅能够实现不同AID算法性能的综合、量化评价及比选,还可以用于确定不同AID算法的最优检测阈值及最优检测性能点,从而为交通管理者进行算法的比选以及算法参数的标定提供了有效的技术支持。
3、分别利用仿真数据和实际数据对W-CUSUM算法进行了评价和比较。分析了不同影响因素下W-CUSUM算法性能的差异,并将所提出的W-CUSUM算法与现有的SND算法、CUSUM算法、UCB算法进行了性能对比。结果表明：(1)不同阻塞车道数条件下W-CUSUM算法性能的差异最为明显,影响最不明显的是事件的持续时间；(2)相对于SND算法、CUSUM算法和UCB算法而言,W-CUSUM算法的检测性能更优,优化程度分别提高了33.7%、19.5%和38.3%。
4、基于实验交通工程法(ETEM),提出了面向事件检测的移动源数据样本量确定模型,弥补了现有方法难以针对事件检测进行移动源数据样本量研究的不足,并通过仿真实例研究得出了满足事件检测一定精度水平所需要的路网浮动车比例以及较优的事件检测间隔,从而为确定面向事件检测的浮动车合理发展规模和检测间隔提供了有效的建议。
5、建立了基于分层结构的事件检测多源数据融合模型。在所建的融合模型中,充分考虑到了各种可用数据源所包含的事件信息特性,并将W-CUSUM算法与神经网络模型以及交通决策者的经验有效的结合起来,一方面既增强了W-CUSUM算法在实际应用中的灵活性和可拓展性,同时也为进一步提高事件检测算法的准确性和可靠性奠定了坚实的方法与理论基础。
6、从系统的角度,提出了W-CUSUM事件检测算法的实施框架与流程,对事件检测系统开发、安装及运行的整个过程进行了具体的阐述和建议,从而对W-CUSUM事件检测算法从理论研究到实际应用建立了相应的方法和流程。
Traffic incidents are a primary contributor to various unexpected congestions, resulting in traffic delays, declining of traffic infrastructure service efficiency, and loss of traffic users' benefits, and having a considerable impact to the traffic safety and environment as well. A prompt and reliable detection of and a quick response to the traffic incident on urban expressways, which represent the trend of the rapid urban infrastrure development and the backbone of the urban transportation network, is not only an important component of traffic management and control of urban expressways, but an effective way to decrease the losses resulted from the incident and reduce the traffic congestion as well. Meanwhile, the continuing development and maturity of mobile traffic detection techniques are now able to provide new real-time, dynamic and accurate traffic information for incident detection.
The purpose of this dissertation is to develop, evaluate, validate and implement an automatic incident detection (AID) algorithm for urban expressways based on mobile source traffic data, which provides a new approach for the detection and management of, and response to the traffic incidents on urban expressways as well as an evaluation method of AID algorithms. The research in this dissertation consists of the following accomplishments and contributions:
1. Existing AID algorithms are mainly developed based on fixed detectors, which have such shortcomings as high false alarm rate, and poor application performance. In this context, this research proposes an AID algorithm, called W-CUSUM algorithm, for urban expressways based on mobile source data. In the proposed algorithm, the feature of the mobile source data and the temporal-spatial characteristics of the traffic flow on urban expressways under incidents are fully considered by combining the wavelet analysis method and CUSUM approach, which improve the quality of the data, thus greatly increase the accuracy and reliability of the incident detection.
2. The existing false alarm rate index could hardly reflect the false alarm situation directly and effectively, and the traditional performance envelop curve can only give a qualitative and rough description of the performance, which result in a lack of comprehensive and quantitative evaluation of the AID algorithms. Therefore, this research first proposes a new false alarm rate based on temporal and spatial index, and then establishes a comprehensive index based on expected cost by integrating the indices of detection rate and false alarm rate. The proposed index based on expected cost can not only provide the comprehensive and quantitative evaluation and comparison for various AID algorithms, but be used for determinating the optimal detection threshold and performance point of an algorithm as well. Thus, it gives traffic managers an effective technical approach to compare, select and calibrate the AID algorithms.
3. The proposed W-CUSUM algorithm is evaluated and compared by using both simulation data and real-world data. By analyzing the performance of W-CUSUM algorithm under different influential factors and comparing W-CUSUM algorithm with SND, CUSUM and UCB algorithms, it is found that:(1) the number of blocked lanes has the largest effect on the performance of W-CUSUM algorithm, while the incident duration has little effect on the performance of W-CUSUM algorithm; (2) W-CUSUM algorithm performs better than SND, CUSUM, and UCB algorithms with an improvement of 33.7%,19.5% and 38.3% respectively.
4. A model for determining the mobile source data sample size for incident detection is developed based on the Experimental Traffic Engineering Methodology (ETEM), which overcomes the shortcomings of existing methods. According to the simulation case study, the reasonable percentage of floating cars in road networks and the optimal detection interval under certain accuracy of incident detection are obtained.
5. A multi-source data fusion model for incident detection based on hierarchical structure is developed by fully considering the characteristics of the incident information contained in various available data sources and integrating W-CUSUM algorithm, neural network model and the experiences of traffic decision-makers. The proposed model not only enhances the flexibility and expandability of W-CUSUM algorithm for application, but also provides a pratical methodology for improving the accuracy and reliability of the W-CUSUM algorithm.
6. A framework for implementing the W-CUSUM algorithm is established using a systematic and integrated approach, in which the development, installation, and operation of the AID system are presented in details in order to provide an overall methodological system for the W-CUSUM algorithm to transition from a theoretical study to practical applications.
引文
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