This page has only limited features, please log in for full access.

Unclaimed
Ming Cai
School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou 510006, China

Basic Info

Basic Info is private.

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 02 August 2021 in IEEE Transactions on Intelligent Transportation Systems
Reads 0
Downloads 0

Cellular signaling data (CSD) have attracted unprecedented attention due to their large size, long observation period, and high followability. Before applying CSD, a series of data processing steps are indispensable; among those steps, staying point recognition is the basis for recognizing individual travel states and thus the influence of further application of CSD. Previous work indicates that the existing staying point recognition algorithms have two common aspects. One is the requirement of a fixed spatiotemporal threshold to analyze the user's travel characteristics. The other is the insufficiency of accuracy assessment, which indicates that further studies are expected owing to the lack of ground truth data in CSD. In this work, a ``spatiotemporal window''-based algorithm is proposed to recognize individual staying and moving states. First, an iterative-learning-based model is designed to cluster individual trajectory points without predefined spatiotemporal thresholds. Then, rules to distinguish the staying or moving cluster are made from individual travel characteristics. Moreover, verification work is carried out by collecting volunteers' ground truth data using our developed smartphone application, which achieves an accuracy of 91.3%. Finally, the results demonstrate the effectiveness and robustness of the algorithm through the performance of comparison and sensitivity analyses.

ACS Style

Ming Cai; Zixuan Zhang; Chen Xiong; Chao Gou. An Adaptive Staying Point Recognition Algorithm Based on Spatiotemporal Characteristics Using Cellular Signaling Data. IEEE Transactions on Intelligent Transportation Systems 2021, PP, 1 -11.

AMA Style

Ming Cai, Zixuan Zhang, Chen Xiong, Chao Gou. An Adaptive Staying Point Recognition Algorithm Based on Spatiotemporal Characteristics Using Cellular Signaling Data. IEEE Transactions on Intelligent Transportation Systems. 2021; PP (99):1-11.

Chicago/Turabian Style

Ming Cai; Zixuan Zhang; Chen Xiong; Chao Gou. 2021. "An Adaptive Staying Point Recognition Algorithm Based on Spatiotemporal Characteristics Using Cellular Signaling Data." IEEE Transactions on Intelligent Transportation Systems PP, no. 99: 1-11.

Journal article
Published: 19 June 2021 in Biomedical Signal Processing and Control
Reads 0
Downloads 0

The development of a real-time monitoring and warning platform for driver fatigue detection is of great importance to avoid traffic accidents and fatalities. Due to the explosive growth of biosignal data, especially electroencephalogram (EEG) signals, generated in the wearable-IoT age, the practical application and recognition stability of these signals should be considered and further studied. The application of EEG signals, especially prefrontal EEG, is a potential key method for effectively determining when a driver is experiencing fatigue, which would promote the development of wearable devices for fatigue warning. In this work, we reported a rapid and effective forehead EEG-based multientropy feature-driven fatigue identification framework using a robust hybrid model. This method investigated and utilized several common entropies to enhance the characteristic quality of EEG signal, and yielded a better expected outcome than those of several classical algorithms due to the hybrid model. The experimental results using prefrontal EEG for assessing driver fatigue showed that the proposed method is convenient and effective, as validated by 32 healthy participants through double-layer nested cross validation. In addition, multi-entropy measures were evaluated for single-channel EEG fatigue detection, and the results showed that wavelet log-energy entropy (WLE) outperformed the other entropy indices with a better recognition rate and higher computational efficiency. We demonstrated that multientropy fusion was able to significantly increase detection quality. This study provided a new strategy of using prefrontal EEG signals to construct a high-efficiency method for detecting driver fatigue, which could possess great potential for real-time single-channel signal analysis.

ACS Style

Jianliang Min; Chen Xiong; Yonggang Zhang; Ming Cai. Driver fatigue detection based on prefrontal EEG using multi-entropy measures and hybrid model. Biomedical Signal Processing and Control 2021, 69, 102857 .

AMA Style

Jianliang Min, Chen Xiong, Yonggang Zhang, Ming Cai. Driver fatigue detection based on prefrontal EEG using multi-entropy measures and hybrid model. Biomedical Signal Processing and Control. 2021; 69 ():102857.

Chicago/Turabian Style

Jianliang Min; Chen Xiong; Yonggang Zhang; Ming Cai. 2021. "Driver fatigue detection based on prefrontal EEG using multi-entropy measures and hybrid model." Biomedical Signal Processing and Control 69, no. : 102857.

Journal article
Published: 21 March 2021 in Transportation Research Part D: Transport and Environment
Reads 0
Downloads 0

Unlike the current methods for dynamic traffic noise maps by using traffic flow as the non-acoustic road-related parameter to predict the noise emission of the whole road network, this study proposes a new method for dynamic updates of traffic noise maps in large regions based on noise monitoring and traffic speed data. The proposed method consists of two main parts. First, since the traffic speed is one of the factors affecting the traffic noise, a model of the noise level and traffic speed is proposed to update dynamically the noise source intensity of the whole road network with the real-time noise monitoring data. Second, to avoid redundant computations, the acoustic attenuation terms are calculated in advance and combined with the updated noise source intensity to generate new noise maps. Compared with two other methods, the proposed method has higher accuracy with a 1.65-dB overall error.

ACS Style

Ziqin Lan; Ming Cai. Dynamic traffic noise maps based on noise monitoring and traffic speed data. Transportation Research Part D: Transport and Environment 2021, 94, 102796 .

AMA Style

Ziqin Lan, Ming Cai. Dynamic traffic noise maps based on noise monitoring and traffic speed data. Transportation Research Part D: Transport and Environment. 2021; 94 ():102796.

Chicago/Turabian Style

Ziqin Lan; Ming Cai. 2021. "Dynamic traffic noise maps based on noise monitoring and traffic speed data." Transportation Research Part D: Transport and Environment 94, no. : 102796.

Research article
Published: 11 March 2021 in Mobile Information Systems
Reads 0
Downloads 0

Obtaining the distribution of home and work locations is essential for city planning, as it defines the structure and mobility pattern of a city. With the development of telecommunication networks, mobile network data, having the advantages of large coverage and strong followability, have produced large amounts of information about human activities. Thus, it has become a popular research subject for human position detection. In this study, we proposed a new method to detect home and work locations based on the extraction of focal points in traces, identifying an individual’s working and resting hours, and analyzing the characteristics of city grids using mobile phone cellular signaling data (CSD). At the individual level, we validated the algorithm on ground-truth volunteer data and achieved a small deviation of under 500 and 565 m for home and work location detection 85% of the time. At the aggregate level, we tested it on a city-wide anonymized CSD set and found a high Pearson correlation between our result and the census data of 0.93. Compared to existing studies, this study improved the granularity and location accuracy of home and work location detection, as well as validated the method using both individually labeled ground-truth data and aggregate data for the first time. Applying the algorithm in a city, we captured the population distribution, commuting patterns, and job-housing balance of the city and demonstrated the potential in using mobile network data for urban planning and policy formulation.

ACS Style

Yingkun Yang; Chen Xiong; Junfan Zhuo; Ming Cai. Detecting Home and Work Locations from Mobile Phone Cellular Signaling Data. Mobile Information Systems 2021, 2021, 1 -13.

AMA Style

Yingkun Yang, Chen Xiong, Junfan Zhuo, Ming Cai. Detecting Home and Work Locations from Mobile Phone Cellular Signaling Data. Mobile Information Systems. 2021; 2021 ():1-13.

Chicago/Turabian Style

Yingkun Yang; Chen Xiong; Junfan Zhuo; Ming Cai. 2021. "Detecting Home and Work Locations from Mobile Phone Cellular Signaling Data." Mobile Information Systems 2021, no. : 1-13.

Journal article
Published: 30 December 2020 in Sensors
Reads 0
Downloads 0

With the rapid development of positioning techniques, a large amount of human travel trajectory data is collected. These datasets have become an effective data resource for obtaining urban traffic patterns. However, many traffic analyses are only based on a single dataset. It is difficult to determine whether a single-dataset-based result can meet the requirement of urban transport planning. In response to this problem, we attempted to obtain traffic patterns and population distributions from the perspective of multisource traffic data using license plate recognition (LPR) data and cellular signaling (CS) data. Based on the two kinds of datasets, identification methods of residents’ travel stay point are proposed. For LPR data, it was identified based on different vehicle speed thresholds at different times. For CS data, a spatiotemporal clustering algorithm based on time allocation was proposed to recognize it. We then used the correlation coefficient r and the significance test p-values to analyze the correlations between the CS and LPR data in terms of the population distribution and traffic patterns. We studied two real-world datasets from five working days of human mobility data and found that they were significantly correlated for the stay and move population distributions. Then, the analysis scale was refined to hour level. We also found that they still maintain a significant correlation. Finally, the origin–destination (OD) matrices between traffic analysis zones (TAZs) were obtained. Except for a few TAZs with poor correlations due to the fewer LPR records, the correlations of the other TAZs remained high. It showed that the population distribution and traffic patterns computed by the two datasets were fairly similar. Our research provides a method to improve the analysis of complex travel patterns and behaviors and provides opportunities for travel demand modeling and urban transport planning. The findings can also help decision-makers understand urban human mobility and can serve as a guide for urban management and transport planning.

ACS Style

Hua Chen; Ming Cai; Chen Xiong. Research on Human Travel Correlation for Urban Transport Planning Based on Multisource Data. Sensors 2020, 21, 195 .

AMA Style

Hua Chen, Ming Cai, Chen Xiong. Research on Human Travel Correlation for Urban Transport Planning Based on Multisource Data. Sensors. 2020; 21 (1):195.

Chicago/Turabian Style

Hua Chen; Ming Cai; Chen Xiong. 2020. "Research on Human Travel Correlation for Urban Transport Planning Based on Multisource Data." Sensors 21, no. 1: 195.

Journal article
Published: 13 December 2020 in Applied Acoustics
Reads 0
Downloads 0

Traffic noise maps are an important instrument for environmental education and research; these maps directly show the traffic noise distribution in a determining area and period. Traffic conditions and the sound pressure of a road stretch changes over time, meanings that the initial map might conflict with the perception of traffic noise by city dwellers; hence, it is necessary to constantly update these maps. A method to obtain an updated traffic noise based on a speed cluster is proposed in this study. The updated method comprises three steps: First, road stretches of the initial map were classified based on the road design guide and each category was clustered according to the speed of the road stretches that was considered to draw the initial traffic noise map. Then, the sound pressure level of all road stretches was updated using data from two steps. The first step contained few noise measurements and the speed data of all road stretches, including the current data. The second step included the predicted sound pressure level of all road stretches and speed data from the initial traffic noise map. Finally, the equivalent noise levels of all receiving points were updated using the law of sound propagation to complete the process of updating the initial traffic noise map. The accuracy of this method was validated in a case study in the Chan Chen district of Foshan, China. In this case study, the mean hourly error between the sound pressure level of all the road stretches calculated by the updated method and extracted from traffic data was 0.16 dB. The updated method can rapidly revise the sound pressure level of road stretches, making it useful in developing traffic noise maps.

ACS Style

Wangxing Xue; Zhaofeng Huang; Bangtao Zhao; Weijun Yang; Ziqin Lan; Ming Cai. Updated traffic noise map method based on speed cluster. Applied Acoustics 2020, 175, 107818 .

AMA Style

Wangxing Xue, Zhaofeng Huang, Bangtao Zhao, Weijun Yang, Ziqin Lan, Ming Cai. Updated traffic noise map method based on speed cluster. Applied Acoustics. 2020; 175 ():107818.

Chicago/Turabian Style

Wangxing Xue; Zhaofeng Huang; Bangtao Zhao; Weijun Yang; Ziqin Lan; Ming Cai. 2020. "Updated traffic noise map method based on speed cluster." Applied Acoustics 175, no. : 107818.

Original research paper
Published: 25 November 2020 in IET Intelligent Transport Systems
Reads 0
Downloads 0

With the advancement of positioning techniques, a large amount of trajectory data has been produced. Matching vehicles with mobile phones using different trajectories can benefit many applications, such as driving behaviour analysis and travel mode split. Moreover, as a privacy attack method, it can provide theoretical inspiration for privacy protection theory. To address this problem, a new trajectory matching framework for processing massive Automatic License Plate Recognition (ALPR) and cellular signalling data is proposed. Information entropy was adopted to address the movement frequency of trajectories and then the infrequent vehicles and phones that did not meet the threshold were pruned. Next, an effective matching algorithm was devised to match the trajectories of vehicles and mobile phones. Moreover, to solve the problem of obtaining a small number of matching results, a data augmentation algorithm was proposed to add new, matching records. Last, a classification model was constructed with LightGBM to determine whether the vehicle matches the phone. Experimental results on real datasets show that the framework outperforms typical techniques in terms of effectiveness and efficiency. The data obtained by data augmentation have distribution characteristics similar to those of the original data. The proposed classification model achieves an accuracy of 93.6%.

ACS Style

Wei Wan; Ming Cai. Phone‐vehicle trajectory matching framework based on ALPR and cellular signalling data. IET Intelligent Transport Systems 2020, 15, 107 -118.

AMA Style

Wei Wan, Ming Cai. Phone‐vehicle trajectory matching framework based on ALPR and cellular signalling data. IET Intelligent Transport Systems. 2020; 15 (1):107-118.

Chicago/Turabian Style

Wei Wan; Ming Cai. 2020. "Phone‐vehicle trajectory matching framework based on ALPR and cellular signalling data." IET Intelligent Transport Systems 15, no. 1: 107-118.

Journal article
Published: 19 August 2020 in Transportation Research Part D: Transport and Environment
Reads 0
Downloads 0

Traffic noise pollution has become a major environmental issue that plagues urban residents. The purpose of this study is to evaluate the traffic noise pollution based on noise maps. Twenty-four-hour noise maps of the Chancheng District in Foshan, China were developed for this study, and the results analyzed. The study area is divided into four types, based on the land use requirements for the acoustic environment, and the calculated noise value is compared to the noise limits of each class of the area. The average equivalent sound pressure level of the entire study area indicates the noise pollution is modest, but further analysis of the noise data in various types of areas shows a high magnitude of noise and long-lasting noise pollution near street-front buildings as well as the areas where quietness is required. It was also found that the noise level of the city is higher during off-peak hours than during rush hours, probably due to the faster speed and larger traffic volume during the off-peak hours. It is urgent to develop effective noise reduction measures to mitigate traffic noise pollution at night, based on the evaluation results.

ACS Style

Weijun Yang; Jinying He; CanMing He; Ming Cai. Evaluation of urban traffic noise pollution based on noise maps. Transportation Research Part D: Transport and Environment 2020, 87, 102516 .

AMA Style

Weijun Yang, Jinying He, CanMing He, Ming Cai. Evaluation of urban traffic noise pollution based on noise maps. Transportation Research Part D: Transport and Environment. 2020; 87 ():102516.

Chicago/Turabian Style

Weijun Yang; Jinying He; CanMing He; Ming Cai. 2020. "Evaluation of urban traffic noise pollution based on noise maps." Transportation Research Part D: Transport and Environment 87, no. : 102516.

Journal article
Published: 23 June 2020 in Journal of Advanced Transportation
Reads 0
Downloads 0

With the rapid development of data acquisition technology, data acquisition departments can collect increasingly more data. Various data from government agencies are gradually becoming available to the public, including license plate recognition (VLPR) data. As a result, privacy protection is becoming increasingly significant. In this paper, an adversary model based on passing time, color, type, and brand of VLPR data is proposed. Through experimental analysis, the tracking probability of a vehicle’s trajectory can be more than 94% if utilizing the original data. To decrease the tracking probability, a novel approach called the (m, n)-bucket model based on time series is proposed since previous works, such as those using generalization and bucketization models, cannot deal with data with multiple sensitive attributes (SAs) or data with time correlations. Meanwhile, a mathematical model is established to expound the privacy protection principle of the (m, n)-bucket model. By comparing the average calculated linking probability of all individuals and the actual linking probability, it is shown that the mathematical model that is proposed can well expound the privacy protection principle of the (m, n)-bucket model. Extensive experiments confirm that our technique can effectively prevent trajectory privacy disclosures.

ACS Style

Hua Chen; Chen Xiong; Jia-Meng Xie; Ming Cai; Hua Chen. Privacy Protection Method for Vehicle Trajectory Based on VLPR Data. Journal of Advanced Transportation 2020, 2020, 1 -16.

AMA Style

Hua Chen, Chen Xiong, Jia-Meng Xie, Ming Cai, Hua Chen. Privacy Protection Method for Vehicle Trajectory Based on VLPR Data. Journal of Advanced Transportation. 2020; 2020 ():1-16.

Chicago/Turabian Style

Hua Chen; Chen Xiong; Jia-Meng Xie; Ming Cai; Hua Chen. 2020. "Privacy Protection Method for Vehicle Trajectory Based on VLPR Data." Journal of Advanced Transportation 2020, no. : 1-16.

Journal article
Published: 25 March 2020 in Transportation Research Part D: Transport and Environment
Reads 0
Downloads 0

Many residents are disturbed by road traffic noise which needs to be controlled and managed. The noise map is a helpful and important tool for noise management and acoustical planning in urban areas. However, the static noise map is not sufficient for evaluating noise annoyance at different temporal periods. It is necessary to develop the dynamic noise map or the noise spatiotemporal distribution. In this study, a method about urban road traffic noise spatiotemporal distribution mapping is proposed to obtain the representative road traffic noise maps of different periods. This method relies on the proposed noise spatiotemporal distribution model with two time-dependent variables - traffic density and traffic speed, and the spatiotemporal characteristics derived from multisource data. There are three steps in the method. First, the urban road traffic noise spatiotemporal distribution model is derived from the law of sound propagation. Then, the temporal characteristics are extracted from traffic flow detecting data and E-map road segment speed data by the outlier detection analysis. Finally, the noise distributions corresponding to different periods are calculated by an efficient algorithm which can save 90% above of the computing time. Moreover, a validation experiment was conducted to evaluate the accuracy of the proposed method. There is only 2.26-dB[A] mean absolute error that is within an acceptable range, which shows that the method is effective.

ACS Style

Ziqin Lan; CanMing He; Ming Cai. Urban road traffic noise spatiotemporal distribution mapping using multisource data. Transportation Research Part D: Transport and Environment 2020, 82, 102323 .

AMA Style

Ziqin Lan, CanMing He, Ming Cai. Urban road traffic noise spatiotemporal distribution mapping using multisource data. Transportation Research Part D: Transport and Environment. 2020; 82 ():102323.

Chicago/Turabian Style

Ziqin Lan; CanMing He; Ming Cai. 2020. "Urban road traffic noise spatiotemporal distribution mapping using multisource data." Transportation Research Part D: Transport and Environment 82, no. : 102323.

Journal article
Published: 05 March 2020 in Results in Physics
Reads 0
Downloads 0

Measurement systems with high precision, fast speeds, and large ranges are required in current technological and industrial fields. In this work, a system was constructed based on the Michelson interferometer and a “soft tracking” measurement scheme. First, an algorithm based on the Radon transform and grayscale projection was proposed to detect the inclination angle of the interference fringe. Next, a raw interference image was rotated to be vertical and projected to a one-dimensional form so that the fringe pitch could be calculated using the algorithm based on Fourier spectrum analysis. Finally, a spatial similarity matching method was developed to obtain the amount of fringe shifting. Each component of the algorithm is discussed, and experimental results are presented. The results showed the effectiveness of the measurement system. The system could measure a displacement of 40 μm within 100 ms, which was 35 times improvement in the system efficiency compared to our previous work. Finally, discussions of the measurement errors and the analysis of the influence factors are presented to comprehensively introduce the properties of the measurement system.

ACS Style

Chen Xiong; Wei Wan; Jiatao Chen; Delong Zeng; Ming Cai. Fast high-precision displacement measurement system based on fringe image analysis techniques. Results in Physics 2020, 17, 103048 .

AMA Style

Chen Xiong, Wei Wan, Jiatao Chen, Delong Zeng, Ming Cai. Fast high-precision displacement measurement system based on fringe image analysis techniques. Results in Physics. 2020; 17 ():103048.

Chicago/Turabian Style

Chen Xiong; Wei Wan; Jiatao Chen; Delong Zeng; Ming Cai. 2020. "Fast high-precision displacement measurement system based on fringe image analysis techniques." Results in Physics 17, no. : 103048.

Journal article
Published: 05 December 2019 in Optical Engineering
Reads 0
Downloads 0

Due to its incomparable advantages, such as low environment requirement and easy data processing, digital image correlation (DIC)1,2 has been applied in many noncontact measurement areas.3–6 Now with the development of high-speed cameras and computer performance, improving the computation efficiency of the DIC method has become a major problem. Continuous improvements have been made to the DIC algorithm.

ACS Style

Chen Xiong; Jiatao Chen; Feng Li; Ming Cai. Fast digital image correlation using parallel temporal sequence correlation method. Optical Engineering 2019, 58, 124101 .

AMA Style

Chen Xiong, Jiatao Chen, Feng Li, Ming Cai. Fast digital image correlation using parallel temporal sequence correlation method. Optical Engineering. 2019; 58 (12):124101.

Chicago/Turabian Style

Chen Xiong; Jiatao Chen; Feng Li; Ming Cai. 2019. "Fast digital image correlation using parallel temporal sequence correlation method." Optical Engineering 58, no. 12: 124101.

Journal article
Published: 13 November 2019 in Applied Acoustics
Reads 0
Downloads 0

Vehicle type and driving speed are important factors affecting the vehicle noise spectrum. Therefore, according to the noise spectrum characteristics of single vehicles, the types of vehicles commonly found on Chinese urban roads are classified and the speed interval is divided. Then, by collecting the noise data of a large number of single vehicles, the noise spectrum characteristics of different types of vehicles at different speed intervals are analyzed. Combined with the vehicle noise emission calculation model, the sound pressure level of the vehicle is calculated, and the noise spectrum of the single vehicle is calculated by the sound pressure level and the noise spectral characteristics of the corresponding vehicle type and speed. The speed distribution of each type of vehicle is estimated, and the noise spectrum of small-size traffic flow consisting of the same type of vehicle driving at the same speed interval is calculated. Finally, the noise spectra of all small-size traffic flow on the road section are superimposed to calculate the road traffic noise spectrum. This calculation method is applied to the five cases, the range standard deviation of the spectral sound pressure level between the calculated result and the measured value is [2.24,3.14], and the range of Euclidean Distance between the spectral energy contribution rate is [0.1,0.16].

ACS Style

Weijun Yang; Ming Cai; Peng Luo. The calculation of road traffic noise spectrum based on the noise spectral characteristics of single vehicles. Applied Acoustics 2019, 160, 107128 .

AMA Style

Weijun Yang, Ming Cai, Peng Luo. The calculation of road traffic noise spectrum based on the noise spectral characteristics of single vehicles. Applied Acoustics. 2019; 160 ():107128.

Chicago/Turabian Style

Weijun Yang; Ming Cai; Peng Luo. 2019. "The calculation of road traffic noise spectrum based on the noise spectral characteristics of single vehicles." Applied Acoustics 160, no. : 107128.

Journal article
Published: 12 July 2019 in International Journal of Environmental Research and Public Health
Reads 0
Downloads 0

In order to realize the simulation and evaluation of road traffic noise among urban buildings, a spatial subdivision-based beam-tracing method is proposed in this study. First, the road traffic source is divided into sets of point sources and described with the help of vehicle emission model. Next, for each pair of source and receiver, spatial subdivision-based beam-tracing method is used in noise paths generation. At last, noise distribution can be got by noise calculation of all receivers considering the complex transmission among urban buildings. A measurement experiment with a point source is carried out to validate the accuracy of the method; the 0.8 m height and 2.5-m height average errors are about 0.9 dB and 1.2 dB, respectively. Moreover, traffic noise analysis under different building layouts and heights are presented by case applications and conclusions can be reached: (1) Different patterns result in different noise distributions and patterns designed as self-protective can lead to an obvious noise abatement for rear buildings. Noise differences between the front and rear buildings are about 7-12 dB with different patterns. (2) Noise value might not show a linear variation along with the height as shielding of different layers is various in reality.

ACS Style

Haibo Wang; Ming Cai; Hongjun Cui. Simulation and Analysis of Road Traffic Noise among Urban Buildings Using Spatial Subdivision-Based Beam Tracing Method. International Journal of Environmental Research and Public Health 2019, 16, 2491 .

AMA Style

Haibo Wang, Ming Cai, Hongjun Cui. Simulation and Analysis of Road Traffic Noise among Urban Buildings Using Spatial Subdivision-Based Beam Tracing Method. International Journal of Environmental Research and Public Health. 2019; 16 (14):2491.

Chicago/Turabian Style

Haibo Wang; Ming Cai; Hongjun Cui. 2019. "Simulation and Analysis of Road Traffic Noise among Urban Buildings Using Spatial Subdivision-Based Beam Tracing Method." International Journal of Environmental Research and Public Health 16, no. 14: 2491.

Journal article
Published: 07 May 2019 in Transportation Research Part C: Emerging Technologies
Reads 0
Downloads 0

Emerging smart transportation applications are calling for publishing and sharing individual-based mobility trace data sets to researchers and practitioners; in the meanwhile, however, privacy issues have become a major concern given that true identities of individuals can be easily revealed from these data sets. Data synthesis In this paper, we quantitatively measure the risk of privacy disclosure in mobility trace data set caused by re-identification attacks based on the concept of k-anonymity. Using a one-month license plate recognition (LPR) data set collected in Guangzhou, China, we examine a variety of factors determining the degree of anonymity of an individual, including the temporal granularity and the size of the published data, local v.s. non-local vehicles, and continuous v.s. non-continuous observations. We find that five spatiotemporal records are enough to uniquely identify about 90% of individuals, even when the temporal granularity is set to be half a day. To publish LPR data without compromising privacy, we propose a suppression solution and a generalization solution and quantify the privacy-and-utility trade-off of them. Our results show that the suppression solution, which removes sensitive records, have a notable performance on privacy protection. The average individual anonymity identified by three spatiotemporal records increases by more than 20% at the cost of losing less than 8% of the data. We also propose a bintree-based adaptive time interval cloaking algorithm as a generalization solution. To meet a specific anonymity constraint, this algorithm adjusts the temporal resolution adaptively based on traffic counts under the principle of minimal information loss. We find that the generalization algorithm performs extremely well in satisfying different user-specified anonymity constraints and it is more flexible and reliable than the traditional uniform time interval cloaking method. We also find a strong correlation between the resulting temporal accuracy of data anonymized by the algorithm and the traffic condition. This study serves as a reminder to relevant agencies and data owners about the privacy vulnerability in individual-based mobility trace data sets and provides methodological guidance when publishing and sharing such sensitive data set.

ACS Style

Jing Gao; Lijun Sun; Ming Cai. Quantifying privacy vulnerability of individual mobility traces: A case study of license plate recognition data. Transportation Research Part C: Emerging Technologies 2019, 104, 78 -94.

AMA Style

Jing Gao, Lijun Sun, Ming Cai. Quantifying privacy vulnerability of individual mobility traces: A case study of license plate recognition data. Transportation Research Part C: Emerging Technologies. 2019; 104 ():78-94.

Chicago/Turabian Style

Jing Gao; Lijun Sun; Ming Cai. 2019. "Quantifying privacy vulnerability of individual mobility traces: A case study of license plate recognition data." Transportation Research Part C: Emerging Technologies 104, no. : 78-94.

Journal article
Published: 31 August 2018 in Forensic Science International
Reads 0
Downloads 0

There is always more than one method can be employed to reconstruct a traffic accident and then more than one result can be obtained. How to describe these different results becomes an issue. Two solutions were given, the first is to fuse different results to one result, while the other is to rank different results according to their credibility. Methods based on the Ordered Weighted Averaging (OWA) operator and Uncertain Ordered Weighted Averaging (UOWA) operator were proposed to fuse different certain results and different interval results to one result, respectively. And methods based on the Combination Weight Arithmetic Average (CWAA) and OWA operators were proposed to rank different certain or interval results. Finally, a true vehicle-motorcycle accident was given to demonstrate these proposed methods, results showed that all methods work well in practice. If the calculation uncertainty was not considered, the fused result 64.56 km/h and a ranked vector can be obtained; if the calculation uncertainty was considered, the fused result [62.13, 68.13]km/h and a ranked interval number set can be obtained. Because that all final results were obtained by employing widely used mature operators, they deserve to be trusted. The research provides more reliable choices to describe different results obtained from different methods in accident reconstruction.

ACS Style

Tiefang Zou; Fenglin He; Ming Cai; Yuelin Li. Methods for describing different results obtained from different methods in accident reconstruction. Forensic Science International 2018, 291, 253 -259.

AMA Style

Tiefang Zou, Fenglin He, Ming Cai, Yuelin Li. Methods for describing different results obtained from different methods in accident reconstruction. Forensic Science International. 2018; 291 ():253-259.

Chicago/Turabian Style

Tiefang Zou; Fenglin He; Ming Cai; Yuelin Li. 2018. "Methods for describing different results obtained from different methods in accident reconstruction." Forensic Science International 291, no. : 253-259.

Journal article
Published: 01 August 2018 in Environmental Pollution
Reads 0
Downloads 0

The primary objective of this study was to develop an evaluation method for assessing an urban traffic noise–exposed population and apply it in the main urban area of Guangzhou. The method based on points of interest (POIs) and noise map is realized in several steps. First, after regionalizing based on road networks and executing a cluster analysis for regions according to the properties of POIs, the environmental noise functional regions (NFRs) of the urban area are presented. Then, surrounding POIs are used to infer the type of buildings, and according to the attraction of different building types and the whole population of the region, the population distribution at the building level is calculated. Finally, with the help of a noise map, an evaluation method for assessing an urban traffic noise–exposed population is proposed. The method is applied in the main urban area of Guangzhou, and the results reveal the followings. 1) At daytime and nighttime, 23.63% and 30.53% of the population, respectively, experience noise levels that exceed the noise standards. The per capita noise exposure value at daytime and nighttime is 0.9 dB and 2.0 dB, respectively. 2) The percentages of the exposed population of Yuexiu District were 28.89% at daytime and 35.65% at nighttime, which are the largest, followed by the exposed population percentages of Liwan, Haizhu, and Tianhe Districts. 3) From the view of different classes of NFRs, the percentages of the exposed population of Class 1 and Class 4 are larger than the percentages of the exposed population from the other classes, especially at nighttime (48.24% of Class 1 and 40.79% of Class 4). 4) Although there are masses of people affected by traffic noise, a large percentage of them (85%) experience not more than 5 dB of traffic noise superscale.

ACS Style

Haibo Wang; Hanjie Chen; Ming Cai. Evaluation of an urban traffic Noise–Exposed population based on points of interest and noise maps: The case of Guangzhou. Environmental Pollution 2018, 239, 741 -750.

AMA Style

Haibo Wang, Hanjie Chen, Ming Cai. Evaluation of an urban traffic Noise–Exposed population based on points of interest and noise maps: The case of Guangzhou. Environmental Pollution. 2018; 239 ():741-750.

Chicago/Turabian Style

Haibo Wang; Hanjie Chen; Ming Cai. 2018. "Evaluation of an urban traffic Noise–Exposed population based on points of interest and noise maps: The case of Guangzhou." Environmental Pollution 239, no. : 741-750.

Journal article
Published: 01 August 2018 in Transportation Research Part B: Methodological
Reads 0
Downloads 0

Synthetic population is a key input to agent-based urban/transportation microsimulation models. The objective of population synthesis is to reproduce the underlying statistical properties of real population based on available microsamples and marginal distributions. However, characterizing the joint associations among a large set of attributes is challenging because of the curse of dimensionality, in particular when attributes are organized in a hierarchical household-individual structure. In this paper, we use a hierarchical mixture model to characterize the joint distribution of both household and individual attributes. Based on this model, we propose a framework of generating representative household structures in population synthesis. The framework integrates three models: (1) probabilistic tensor factorization, (2) multilevel latent class model, and (3) rejection sampling. With this framework, one can generalize not only the associations of within- and cross-level attributes, but also reproduce structural relationships among household members (e.g., husband-wife). As a case study, we implement this framework based on the household interview travel survey (HITS) data of Singapore, and then use the inferred model to generate a synthetic population pool. This model demonstrates great potential in reproducing the underlying statistical distribution of real population. The generated synthetic population can serve as a replacement for census in developing agent-based models, with privacy and confidentiality being protected and preserved.

ACS Style

Lijun Sun; Alexander Erath; Ming Cai. A hierarchical mixture modeling framework for population synthesis. Transportation Research Part B: Methodological 2018, 114, 199 -212.

AMA Style

Lijun Sun, Alexander Erath, Ming Cai. A hierarchical mixture modeling framework for population synthesis. Transportation Research Part B: Methodological. 2018; 114 ():199-212.

Chicago/Turabian Style

Lijun Sun; Alexander Erath; Ming Cai. 2018. "A hierarchical mixture modeling framework for population synthesis." Transportation Research Part B: Methodological 114, no. : 199-212.

Research article
Published: 09 July 2018 in Journal of Advanced Transportation
Reads 0
Downloads 0

The complexity of the 3D buildings and road networks gives the simulation of urban noise difficulty and significance. To solve the problem of computing complexity, a systematic methodology for computing urban traffic noise maps under 3D complex building environments is presented on a supercomputer. A parallel algorithm focused on controlling the compute nodes of the supercomputer is designed. Moreover, a rendering method is provided to visualize the noise map. In addition, a strategy for obtaining a real-time dynamic noise map is elaborated. Two efficiency experiments are implemented. One experiment involves comparing the expansibility of the parallel algorithm with various numbers of compute nodes and various computing scales to determine the expansibility. With an increase in the number of compute nodes, the computing time increases linearly, and an increased computing scale leads to computing efficiency increases. The other experiment is a comparison of the computing speed between a supercomputer and a normal computer; the computing node of Tianhe-2 is found to be six times faster than that of a normal computer. Finally, the traffic noise suppression effect of buildings is analyzed. It is found that the building groups have obvious shielding effect on traffic noise.

ACS Style

Ming Cai; Yifan Yao; Haibo Wang. Urban Traffic Noise Maps under 3D Complex Building Environments on a Supercomputer. Journal of Advanced Transportation 2018, 2018, 1 -10.

AMA Style

Ming Cai, Yifan Yao, Haibo Wang. Urban Traffic Noise Maps under 3D Complex Building Environments on a Supercomputer. Journal of Advanced Transportation. 2018; 2018 ():1-10.

Chicago/Turabian Style

Ming Cai; Yifan Yao; Haibo Wang. 2018. "Urban Traffic Noise Maps under 3D Complex Building Environments on a Supercomputer." Journal of Advanced Transportation 2018, no. : 1-10.

Journal article
Published: 05 May 2018 in Building and Environment
Reads 0
Downloads 0

Road intersections have the potential to pose an additional exposure risk to surrounding dwellers or commuters; however, knowledge of fine-scale variations of traffic pollutants especially PM2.5 and black carbon (BC) remains limited. To investigate them, we conducted a three-point synchronous observation at an intersection in Shanghai in winter and spring. Real-time monitors with one-minute intervals were used to obtain the pollutant and meteorological data while gasoline and diesel vehicle volumes were manually collected every five minutes. Observational results showed that the average PM2.5 on the downwind roadside increased by approximately 9% in both seasons and that the average BC increased by 70% in winter and 97% in spring compared to those of the local background site. PM2.5 displayed a similar diurnal variation among the three sites at the intersection, but in contrast to PM2.5, the BC variation was more strongly correlated to the diurnal traffic cycle. Generalized additive models further identified the background variation as the major contributor to the variations in both pollutants at the intersection, explaining 77–99% and 33–43% of the variance in ln(PM2.5) and ln(BC), respectively. Air pressure and solar radiation were the next top determinants of pollutant variations. Relative humidity combined with air temperature in winter and with dew-point temperature in spring also had a significant impact. Roadside BC was sensitive to traffic from the windward direction, while PM2.5 was mostly influenced by the external pollution driven by westerly winds. In contrast to gasoline vehicles, diesel vehicles were verified to provide an appreciable contribution of approximately 9% to roadside BC variations in spring.

ACS Style

Zhanyong Wang; Shuqi Zhong; Hong-Di He; Zhong-Ren Peng; Ming Cai. Fine-scale variations in PM2.5 and black carbon concentrations and corresponding influential factors at an urban road intersection. Building and Environment 2018, 141, 215 -225.

AMA Style

Zhanyong Wang, Shuqi Zhong, Hong-Di He, Zhong-Ren Peng, Ming Cai. Fine-scale variations in PM2.5 and black carbon concentrations and corresponding influential factors at an urban road intersection. Building and Environment. 2018; 141 ():215-225.

Chicago/Turabian Style

Zhanyong Wang; Shuqi Zhong; Hong-Di He; Zhong-Ren Peng; Ming Cai. 2018. "Fine-scale variations in PM2.5 and black carbon concentrations and corresponding influential factors at an urban road intersection." Building and Environment 141, no. : 215-225.