With the improvement of the national economic level,the number of vehicles is still increasing year by year.According to the statistics of National Bureau of Statics,the number is approximately up to 327 million in Ch...With the improvement of the national economic level,the number of vehicles is still increasing year by year.According to the statistics of National Bureau of Statics,the number is approximately up to 327 million in China by the end of 2018,which makes urban traffic pressure continues to rise so that the negative impact of urban traffic order is growing.Illegal parking-the common problem in the field of transportation security is urgent to be solved and traditional methods to address it are mainly based on ground loop and manual supervision,which may miss detection and cost much manpower.Due to the rapidly developing deep learning sweeping the world in recent years,object detection methods relying on background segmentation cannot meet the requirements of complex and various scenes on speed and precision.Thus,an improved Single Shot MultiBox Detector(SSD)based on deep learning is proposed in our study,we introduce attention mechanism by spatial transformer module which gives neural networks the ability to actively spatially transform feature maps and add contextual information transmission in specified layer.Finally,we found out the best connection layer in the detection model by repeated experiments especially for small objects and increased the precision by 1.5%than the baseline SSD without extra training cost.Meanwhile,we designed an illegal parking vehicle detection method by the improved SSD,reaching a high precision up to 97.3%and achieving a speed of 40FPS,superior to most of vehicle detection methods,will make contributions to relieving the negative impact of illegal parking.展开更多
Searching for available parking spaces can be a painful experience for drivers due to driving around until finding a vacant space.This study proposes a new method to automatically detect available parking spaces.The p...Searching for available parking spaces can be a painful experience for drivers due to driving around until finding a vacant space.This study proposes a new method to automatically detect available parking spaces.The proposed system identifies empty parking spaces using grayscale images obtained from any type of video camera.The method was found to successfully identify parking availability under different conditions and scenarios.The method was tested using real-life data and achieved a detection rate of 99.7%.This method can be applied in real-time to monitor parking availability and guide drivers to empty spaces.The method has several advantages,including simple algorithms,the use of low-quality black and white images,and simple configuration.Therefore,the system can provide enormous cost savings for locations with existing black and white surveillance cameras instead of replacing existing cameras with new high-quality cameras.展开更多
Purpose–Magnetic sensors have recently been proposed for parking occupancy detection.However,there has adjacent interference problem,i.e.the magnetic signal is easy to be interfered by the vehicles which are parking ...Purpose–Magnetic sensors have recently been proposed for parking occupancy detection.However,there has adjacent interference problem,i.e.the magnetic signal is easy to be interfered by the vehicles which are parking on adjacent spaces.The purpose of this paper is to propose a sensing algorithm to eliminate the adjacent interference.Design/methodology/approach–The magnetic signals are converted to the pattern representation sequences,and the similarity is calculated using the pattern distance.The detection algorithm includes two levels:local decision and data fusion.In the local decision level,the sampled signals can be divided into three classes:vacant,occupied and uncertain.Then a collaborative decision is used to fusion the signals which belong to the uncertain class for the second level.Findings–An experiment system included 60 sensor nodes that were deployed on bay parking spaces.Experiment results show that the proposed algorithm has better detection accuracy than existing algorithms.Originality/value–This paper proposes a data fusion algorithm to eliminate adjacent interference.To balance the energy consumption and detection accuracy,the algorithm includes two levels:local decision and data fusion.In most of cases,the local decision can obtain the accurate detection result.Only the signals that cannot be correctly detected at the local level need data fusion operation.展开更多
基金This research has been supported by NSFC(61672495)Scientific Research Fund of Hunan Provincial Education Department(16A208)+1 种基金Project of Hunan Provincial Science and Technology Department(2017SK2405)in part by the construct program of the key discipline in Hunan Province and the CERNET Innovation Project(NGII20170715).
文摘With the improvement of the national economic level,the number of vehicles is still increasing year by year.According to the statistics of National Bureau of Statics,the number is approximately up to 327 million in China by the end of 2018,which makes urban traffic pressure continues to rise so that the negative impact of urban traffic order is growing.Illegal parking-the common problem in the field of transportation security is urgent to be solved and traditional methods to address it are mainly based on ground loop and manual supervision,which may miss detection and cost much manpower.Due to the rapidly developing deep learning sweeping the world in recent years,object detection methods relying on background segmentation cannot meet the requirements of complex and various scenes on speed and precision.Thus,an improved Single Shot MultiBox Detector(SSD)based on deep learning is proposed in our study,we introduce attention mechanism by spatial transformer module which gives neural networks the ability to actively spatially transform feature maps and add contextual information transmission in specified layer.Finally,we found out the best connection layer in the detection model by repeated experiments especially for small objects and increased the precision by 1.5%than the baseline SSD without extra training cost.Meanwhile,we designed an illegal parking vehicle detection method by the improved SSD,reaching a high precision up to 97.3%and achieving a speed of 40FPS,superior to most of vehicle detection methods,will make contributions to relieving the negative impact of illegal parking.
文摘Searching for available parking spaces can be a painful experience for drivers due to driving around until finding a vacant space.This study proposes a new method to automatically detect available parking spaces.The proposed system identifies empty parking spaces using grayscale images obtained from any type of video camera.The method was found to successfully identify parking availability under different conditions and scenarios.The method was tested using real-life data and achieved a detection rate of 99.7%.This method can be applied in real-time to monitor parking availability and guide drivers to empty spaces.The method has several advantages,including simple algorithms,the use of low-quality black and white images,and simple configuration.Therefore,the system can provide enormous cost savings for locations with existing black and white surveillance cameras instead of replacing existing cameras with new high-quality cameras.
基金supported in part by the National Natural Science Fund,China,under Grant 61872083,in part by the Science and Technology Project of Guang-dong Province under Grant 2016A010101037,Grant 2017A030310659 and Grant 2017KQNCX194,and in part by the Social Science and Technology Development Project of Dongguan City under Grant 20185071401606.
文摘Purpose–Magnetic sensors have recently been proposed for parking occupancy detection.However,there has adjacent interference problem,i.e.the magnetic signal is easy to be interfered by the vehicles which are parking on adjacent spaces.The purpose of this paper is to propose a sensing algorithm to eliminate the adjacent interference.Design/methodology/approach–The magnetic signals are converted to the pattern representation sequences,and the similarity is calculated using the pattern distance.The detection algorithm includes two levels:local decision and data fusion.In the local decision level,the sampled signals can be divided into three classes:vacant,occupied and uncertain.Then a collaborative decision is used to fusion the signals which belong to the uncertain class for the second level.Findings–An experiment system included 60 sensor nodes that were deployed on bay parking spaces.Experiment results show that the proposed algorithm has better detection accuracy than existing algorithms.Originality/value–This paper proposes a data fusion algorithm to eliminate adjacent interference.To balance the energy consumption and detection accuracy,the algorithm includes two levels:local decision and data fusion.In most of cases,the local decision can obtain the accurate detection result.Only the signals that cannot be correctly detected at the local level need data fusion operation.
