Xiaodan Zhang's research while affiliated with Beihang University (BUAA) and other places
What is this page?
This page lists the scientific contributions of an author, who either does not have a ResearchGate profile, or has not yet added these contributions to their profile.
It was automatically created by ResearchGate to create a record of this author's body of work. We create such pages to advance our goal of creating and maintaining the most comprehensive scientific repository possible. In doing so, we process publicly available (personal) data relating to the author as a member of the scientific community.
If you're a ResearchGate member, you can follow this page to keep up with this author's work.
If you are this author, and you don't want us to display this page anymore, please let us know.
It was automatically created by ResearchGate to create a record of this author's body of work. We create such pages to advance our goal of creating and maintaining the most comprehensive scientific repository possible. In doing so, we process publicly available (personal) data relating to the author as a member of the scientific community.
If you're a ResearchGate member, you can follow this page to keep up with this author's work.
If you are this author, and you don't want us to display this page anymore, please let us know.
Publications (6)
Traffic safety has become a severe problem on freeways in China, thus, it is important to establish a real-time crash risk model to identify traffic conditions causing crashes. In this study, we explore the real-time crash risk for urban freeways in China and obtain dynamic crash risk level. Crash and their matching traffic sensor data from a Beiji...
In this paper, we study the traffic event detection from audio signals. Real-life data are collected in a long tunnel, and audio samples are labeled in accordance with traffic events including tire friction sound, vehicle percussion sound and other background sounds. Efficient spectral features are proposed for the fast classification of audio even...
Road traffic monitoring is very important for intelligent transportation. The detection of traffic state based on acoustic information is a new research direction. A vehicles acoustic event classification algorithm based on sparse autoencoder is proposed to analysis the traffic state. Firstly, the multidimensional Mel-cepstrum features and energy f...
With the improvement of automobile automation, auto-driving technology has become one of the research hotspots worldwide. The classification of automobile driving conditions is a key technology for auto-driving. In order to simplify the complexity of automobile driving conditions recognition, it is usually divided into three categories: driving, br...
In the dynamic interaction of a driver-vehicle-environment system, risk perception of drivers changes dynamically, having significant impacts on driving behavior and vehicles movement. In China, because there is less construction of stop signs, as well as limited regulation of driving courtesy, traffic operation and safety issues at unsignalized in...
Citations
... Due to the uncertainty and unforeseen conditions of parameters affecting road safety and the high ability of machine learning algorithms to solve complex problems, recently, the use of these methods in combination with classical methods or, in many studies, alone has been widely used [41][42][43][44][45][46][47][48][49]. Xu et al. (2018) evaluated the effect of road lighting on road safety using an artificial neural network. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/277699055636492-1443220022825_Q64/Miaomiao-Liu-2.jpg)
![[object Object]](https://i1.rgstatic.net/ii/profile.image/277631477010432-1443203910099_Q64/Yongsheng-Chen.jpg)
... Compared to ANN, DNN offers a simpler sequential model with ability of fine-tuning the neural network result. DNN was used for wide range of applications, such as risk assessment [3,4], damage and fault detection [5,6] and forecasting of traffic flow [7,8]. Regardless of wide application of DNN within different fields, the body of literature on house price prediction still needs further attention [9]. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/1096116795916288-1638346017011_Q64/Chengwei-Huang-2.jpg)
... Input data that contains noise or anomalies contain signals that the network has not learned, and so the reconstructed output does not contain these, resulting in a large loss [6]. Applications of auto-encoders for acoustic signals have included the de-noising as a preliminary approach for speech recognition [4], [5], detection of distinct events in acoustic recordings (finger flexion, traffic states) [10], [11], and detecting wear and abnormalities in machine sounds [7], [12]- [15]. ...
... Collect real data in long tunnels and mark audio samples based on traffic incidents, including tire rubbing, vehicle crashing, and other background sounds. An effective spectrum feature is proposed for the rapid classification of audio events [7]. Zhang et al.'s main research is to judge the spectral characteristics by sound, and has no application in the soundscape. ...
... Time-domain features are commonly used in the detection and evaluation applications along with statistical features (Genuit, 2004;Lee et al., 2005;Lee et al., 2015;Nopiah et al., 2015). However, time-frequency domain features, which include wavelet and cepstral features, are more effective in the classification and recognition of acoustic patterns (Mitrović et al., 2010;Niessen et al., 2013;Schr€ oder et al., 2015;Zhang et al., 2019;Pogorilyi et al., 2020a). The cepstral domain features are obtained by taking the fast Fourier transform (FFT) of the logarithm of the amplitude from the spectrum data (Mitrović et al., 2010). ...
... These fuzzy sets can be used to evaluate binary situations such as yes/no, true/false, and those defined as linguistic variables (e.g., safer or riskier). Fuzzy rule-based algorithms have been widely used in transportation safety studies (19)(20)(21)(22). ...
