Review on Vehicular Speed, Density Estimation and Classification Using Acoustic Signal
نویسندگان
چکیده
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.
منابع مشابه
Acoustic Signal based Traffic Density State Estimation using SVM
Based on the information present in cumulative acoustic signal acquired from a roadsideinstalled single microphone, this paper considers the problem of vehicular traffic density state estimation. The occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) are determined by the prevalent traffic density conditions on the road segment. In ...
متن کاملPedestrian and Vehicular Traffic Characteristics for Synthetic-Hybrid Mobility Models
Synthetic mobility models can be used to simulate the movement of a traffic unit or a group of traffic units in a telecommunication network. Characteristics of pedestrian and vehicular traffic, such as speed-flow, speed-density and flow density are often neglected in current synthetic mobility models. The analysis, emulation and simulation of telecommunication networks with mobile users using m...
متن کاملA Comparative Study of Gender and Age Classification in Speech Signals
Accurate gender classification is useful in speech and speaker recognition as well as speech emotion classification, because a better performance has been reported when separate acoustic models are employed for males and females. Gender classification is also apparent in face recognition, video summarization, human-robot interaction, etc. Although gender classification is rather mature in a...
متن کاملThe Development of Maximum Likelihood Estimation Approaches for Adaptive Estimation of Free Speed and Critical Density in Vehicle Freeways
The performance of many traffic control strategies depends on how much the traffic flow models have been accurately calibrated. One of the most applicable traffic flow model in traffic control and management is LWR or METANET model. Practically, key parameters in LWR model, including free flow speed and critical density, are parameterized using flow and speed measurements gathered by inductive ...
متن کاملThree Dimensional Localization of an Unknown Target Using Two Heterogeneous Sensors
Heterogeneous wireless sensor networks consist of some different types of sensor nodes deployed in a particular area. Different sensor types can measure different quantity of a source and using the combination of different measurement techniques, the minimum number of necessary sensors is reduced in localization problems. In this paper, we focus on the single source localization in a heterogene...
متن کامل