A bottleneck automatic identification algorithm based on loop detector data is proposed. The proposed algorithm selects the critical flow rate as the trigger variable of the algorithm which is calculated by the road c...A bottleneck automatic identification algorithm based on loop detector data is proposed. The proposed algorithm selects the critical flow rate as the trigger variable of the algorithm which is calculated by the road conditions the level of service and the proportion of trucks.The process of identification includes two parts. One is to identify the upstream of the bottleneck by comparing the distance between the current occupancy rate and the mean value of the occupancy rate and the variance of the occupancy rate.The other process is to identify the downstream of the bottleneck by calculating the difference of the upstream occupancy rate with that of the downstream.In addition the algorithm evaluation standards which are based on the time interval of the data the detection rate and the false alarm rate are discussed.The proposed algorithm is applied to detect the bottleneck locations in the Shanghai Inner Ring Viaduct Dabaishu-Guangzhong road section.The proposed method has a good performance in improving the accuracy and efficiency of bottleneck identification.展开更多
To improve the performance of composite pseudo-noise （PN） code clock recovery in a regenerative PN ranging system at a low symbol signal-to-noise ratio （SNR）, a novel chip tracking loop （CTL） used for regenerati...To improve the performance of composite pseudo-noise （PN） code clock recovery in a regenerative PN ranging system at a low symbol signal-to-noise ratio （SNR）, a novel chip tracking loop （CTL） used for regenerative PN ranging clock recovery is adopted. The CTL is a modified data transition tracking loop （DTTL）. The difference between them is that the Q channel output of the CTL is directly multiplied by a clock component, while that of the DTTL is multiplied by the Ⅰ channel transition detector output. Under the condition of a quasi-squareware PN ranging code, the tracking （ mean square timing jitter） performance of the CTL is analyzed. The tracking performances of the CTL and the DTTL, are compared over a wide range of symbol SNRs. The result shows that the CTL and the DTTL have the same performance at a large symbol SNR, while at a low symbol SNR, the former offers a noticeable enhancement.展开更多
The burden distribution real-time estimation problem of multi-loop charging based on the real multi-radar data is resolved.Firstly , an iterative algorithm is introduced to calculate the radial coordinate of the pile-...The burden distribution real-time estimation problem of multi-loop charging based on the real multi-radar data is resolved.Firstly , an iterative algorithm is introduced to calculate the radial coordinate of the pile-top.Then , based on the multi-radar data , the burden profile is estimated by a cubic-curve equation at the end of the multi-loop charging.Furthermore , the burden profile before the next multi-loop charging is calculated based on multi-radar data by considering the impact of burden descent.On the basis of these burden profiles , a more accurate thickness ratio of ore to coke （ RO/C ） at the radial direction of blast furnace can be obtained.Finally , an example is given to calculate the burden profiles and RO/C by using the real multi-radar data sampled from Baosteel , which shows the effectiveness of the method introduced.展开更多
Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with...Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with traffic data collected by discrete loop detectors as well as the web-crawl weather data. Matched case-control method and support vector machines （SVMs） technique were employed to identify the risk status. The adaptive synthetic over-sampling technique was applied to solve the imbalanced dataset issues. Random forest technique was applied to select the contributing factors and avoid the over-fitting issues. The results indicate that the SVMs classifier could successfully classify 76.32% of the crashes on the test dataset and 87.52% of the crashes on the overall dataset, which were relatively satisfactory compared with the results of the previous studies. Compared with the SVMs classifier without the data, the SVMs classifier with the web-crawl weather data increased the crash prediction accuracy by 1.32% and decreased the false alarm rate by 1.72%, showing the potential value of the massive web weather data. Mean impact value method was employed to evaluate the variable effects, and the results are identical with the results of most of previous studies. The emerging technique based on the discrete traffic data and web weather data proves to be more applicable on real- time safety management on freeways.展开更多
文摘A bottleneck automatic identification algorithm based on loop detector data is proposed. The proposed algorithm selects the critical flow rate as the trigger variable of the algorithm which is calculated by the road conditions the level of service and the proportion of trucks.The process of identification includes two parts. One is to identify the upstream of the bottleneck by comparing the distance between the current occupancy rate and the mean value of the occupancy rate and the variance of the occupancy rate.The other process is to identify the downstream of the bottleneck by calculating the difference of the upstream occupancy rate with that of the downstream.In addition the algorithm evaluation standards which are based on the time interval of the data the detection rate and the false alarm rate are discussed.The proposed algorithm is applied to detect the bottleneck locations in the Shanghai Inner Ring Viaduct Dabaishu-Guangzhong road section.The proposed method has a good performance in improving the accuracy and efficiency of bottleneck identification.
文摘To improve the performance of composite pseudo-noise （PN） code clock recovery in a regenerative PN ranging system at a low symbol signal-to-noise ratio （SNR）, a novel chip tracking loop （CTL） used for regenerative PN ranging clock recovery is adopted. The CTL is a modified data transition tracking loop （DTTL）. The difference between them is that the Q channel output of the CTL is directly multiplied by a clock component, while that of the DTTL is multiplied by the Ⅰ channel transition detector output. Under the condition of a quasi-squareware PN ranging code, the tracking （ mean square timing jitter） performance of the CTL is analyzed. The tracking performances of the CTL and the DTTL, are compared over a wide range of symbol SNRs. The result shows that the CTL and the DTTL have the same performance at a large symbol SNR, while at a low symbol SNR, the former offers a noticeable enhancement.
基金Item Sponsored by Fundamental Research Funds for Central Universities of China ( FRF-TP-12-103A , FRF-AS-11-004B , FRF-SD-12-016A )Doctoral Program Foundation of Institutions of Higher Education of China ( 20110006120034 )
文摘The burden distribution real-time estimation problem of multi-loop charging based on the real multi-radar data is resolved.Firstly , an iterative algorithm is introduced to calculate the radial coordinate of the pile-top.Then , based on the multi-radar data , the burden profile is estimated by a cubic-curve equation at the end of the multi-loop charging.Furthermore , the burden profile before the next multi-loop charging is calculated based on multi-radar data by considering the impact of burden descent.On the basis of these burden profiles , a more accurate thickness ratio of ore to coke （ RO/C ） at the radial direction of blast furnace can be obtained.Finally , an example is given to calculate the burden profiles and RO/C by using the real multi-radar data sampled from Baosteel , which shows the effectiveness of the method introduced.
基金supported by the National Natural Science Foundation (71301119)the Shanghai Natural Science Foundation (12ZR1434100)
文摘Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with traffic data collected by discrete loop detectors as well as the web-crawl weather data. Matched case-control method and support vector machines （SVMs） technique were employed to identify the risk status. The adaptive synthetic over-sampling technique was applied to solve the imbalanced dataset issues. Random forest technique was applied to select the contributing factors and avoid the over-fitting issues. The results indicate that the SVMs classifier could successfully classify 76.32% of the crashes on the test dataset and 87.52% of the crashes on the overall dataset, which were relatively satisfactory compared with the results of the previous studies. Compared with the SVMs classifier without the data, the SVMs classifier with the web-crawl weather data increased the crash prediction accuracy by 1.32% and decreased the false alarm rate by 1.72%, showing the potential value of the massive web weather data. Mean impact value method was employed to evaluate the variable effects, and the results are identical with the results of most of previous studies. The emerging technique based on the discrete traffic data and web weather data proves to be more applicable on real- time safety management on freeways.
