Review on Vehicular Speed, Density Estimation and Classification Using Acoustic Signal

Abstract

Traffic monitoring and parameters estimation from urban to non urban (battlefield environment) traffic is fast-emerging field based on acoustic signals. We present here a comprehensive review of the state-of-the-art acoustic signal for vehicular speed estimation, density estimation and classification, critical analysis and an outlook to future research directions. This field is of increasing relevance for intelligent transport systems (ITSs). In recent years video monitoring and surveillance systems has been widely used in traffic management and hence traffic parameters can be achieved using such systems, but installation, operational and maintenance cost associated with these approaches are relatively high compared to the use of acoustic signal which is having very low installation and maintenance cost. The classification process includes sensing unit, class definition, feature extraction, classifier application and system evaluation. The acoustic classification system is part of a multi sensor real time environment for traffic surveillance and monitoring. Classification accuracy achieved by various studied algorithms shows very good performance for the 'Heavy Weight' class of vehicles as compared to the other category "Light Weight". Also a slight performance degrades as vehicle speed increases. Vehicular speed estimation corresponds to average speed and traffic density measurement, and can be substantially used for traffic signal timings optimization.

Audio Surveillance of Roads: A System for Detecting Anomalous Sounds

“…In the last decades a large number of methods dealing with the analysis of audio streams has been proposed, ranging from speech recognition [12], [13] and scene classification [14], [15] to speaker identification [16], [17]. More recently, a growing interest for audio analysis has been also shown in surveillance applications, in order to detect crimes for public transport security [18]- [20], the maximum speed of vehicles for security reasons [11], [21], [22] or accidents on the roads [2], [3], [23].…”

A Review on Vehicle Classification and Potential Use of Smart Vehicle-Assisted Techniques

“…Table 3 shows a summary of the literature reviews on VC. [97] The presented review of the available literature on VC shows that most of the research to date mainly focuses on vision-based methods. In these review papers, no particular attempts were performed to review the potential impact of smart technologies in vehicular networks and communication to enhance the efficiency and efficacy of VC systems.…”

“…The vulnerabilities of these techniques were evaluated and the potential misuse of the information was discussed. In another research by Borkar and Malik [97] reviewed the application of acoustic signals to estimate vehicular speed, density, and classification. The study only focused on smart methods by utilizing efficient smartphones, cameras, drones, and robotic sensors.…”

Direction of arrival estimation of partial sound sources of vehicles with a two-microphone array

“…The estimations of speed and wheelbase from acoustic signals have been reported in the literature, with larger predominance of the former [13,[15][16][17][18] over the latter [14,15]. In [16], for instance, a maximum likelihood approach is proposed for speed estimation, which resulted in more accurate and robust estimates when compared to the conventional analysis of sequential short-time cross-correlations.…”