In order to make full use of digital data, such as data extracted from electronic police video systems, and optimize intersection signal parameters, the theoretical distribution of the vehicle's road travel time m...In order to make full use of digital data, such as data extracted from electronic police video systems, and optimize intersection signal parameters, the theoretical distribution of the vehicle's road travel time must first be determined. The intersection signal cycle and the green splits were optimized simultaneously, and the system total travel time was selected as the optimization goal. The distribution of the vehicle's link travel time is the combined results of the flow composition, road marking, the form of control, and the driver's driving habits. The method proposed has 15% lower system total stop delay and fewer total stops than the method of TRRL(Transport and Road Research Laboratory) in England and the method of ARRB(Australian Road Research Board) in Australia. This method can save 0.5% total travel time and will be easier to understand and test, which establishes a causal relationship between optimal results and specific forms of road segment management, such as speed limits.展开更多
A new automatic evaluationmethod of subway service quality based onmetro smart card data is proposed suitable for three different levels:station pair,railway line and subway network,which has merits of overcoming the ...A new automatic evaluationmethod of subway service quality based onmetro smart card data is proposed suitable for three different levels:station pair,railway line and subway network,which has merits of overcoming the previous lagging and subjective evaluation in the system of‘questionnaire survey plus evaluationmethod’.First,passengers’travel time distribution for different operating periods in station OD pairs are introduced initially for service evaluation purposes and are classified into different groups in order to infer the station’s operating characteristics at the different periods.Second,the classification is verified by K-means cluster analysis and K-S tests.Third,the service quality weight indicator is proposed to identify the service quality of the entire metro network from the dual perspectives of passengers and companies.Finally,the feasibility and rationality of the proposed method are verified by Shenzhen metro smart card data as an example.The new automated evaluation method of subway service quality is suitable for online and offline application.展开更多
基金Project(14BTJ017)supported by National Social Science Foundation Project of ChinaProject supported by the 2014 Mathematics and Interdisciplinary Science Project of Central South University,China
文摘In order to make full use of digital data, such as data extracted from electronic police video systems, and optimize intersection signal parameters, the theoretical distribution of the vehicle's road travel time must first be determined. The intersection signal cycle and the green splits were optimized simultaneously, and the system total travel time was selected as the optimization goal. The distribution of the vehicle's link travel time is the combined results of the flow composition, road marking, the form of control, and the driver's driving habits. The method proposed has 15% lower system total stop delay and fewer total stops than the method of TRRL(Transport and Road Research Laboratory) in England and the method of ARRB(Australian Road Research Board) in Australia. This method can save 0.5% total travel time and will be easier to understand and test, which establishes a causal relationship between optimal results and specific forms of road segment management, such as speed limits.
文摘A new automatic evaluationmethod of subway service quality based onmetro smart card data is proposed suitable for three different levels:station pair,railway line and subway network,which has merits of overcoming the previous lagging and subjective evaluation in the system of‘questionnaire survey plus evaluationmethod’.First,passengers’travel time distribution for different operating periods in station OD pairs are introduced initially for service evaluation purposes and are classified into different groups in order to infer the station’s operating characteristics at the different periods.Second,the classification is verified by K-means cluster analysis and K-S tests.Third,the service quality weight indicator is proposed to identify the service quality of the entire metro network from the dual perspectives of passengers and companies.Finally,the feasibility and rationality of the proposed method are verified by Shenzhen metro smart card data as an example.The new automated evaluation method of subway service quality is suitable for online and offline application.
