Within each category, technical descriptions of the sensor types, properties and applications are discussed in terms of theoretical formulas and feasible scenarios. The methods are roughly grouped into mechanical, optical and microwave sensor-based methods. Then, this paper reviews various measurement methods carried out for the essential data of traffic loads. General principles of the traffic load cognition are firstly presented by reviewing different statistical analysis techniques for determining the spatial-temporal factors of vehicles. Therefore, we focus on introducing the state-of-the-art approaches most relevant to the traffic load cognition on road bridges, including in-site measurement and data-driven simulation. As a result, for the traffic load measurement, the relevant technologies had great progress in the past decades. A better understanding of traffic loads in different traffic densities has become increasingly important in structure health monitoring. Traffic load is a crucial but complicated factor in determining the in-service performance and deterioration behavior of bridges. Furthermore, a comparison of the developed photonic-radar is also established with conventional microwave-radar to present a comparative analysis. The performance of the demonstrated photonic-radar is assessed through the power spectral density and range-Doppler mapping measurements. Therefore, this work is tested for different multiple-mobile targets in different complicated traffic-scenarios modeled by using MATLABâ„¢ software. Besides it, some complex real-time traffic-scenarios consisting of multiple mobile-targets make the target-detection, data-association, and classification processes more complicated. Therefore, a linear frequency-modulated continuous-wave photonic-radar is developed in this work to carry out a radar cross-section-based tracking of multiple mobile-targets in the presence of fog, cloud, and rain. Unlike the microwave-radar, the photonic-radar comes out as an attractive candidate owing to provide wide-spectra to attain improved and precise radar-resolutions at low-power requirements along with extended target-range even under severe atmospheric fluctuations. As the utmost functions of the advanced driving assistance system-equipped autonomous vehicles governed by the equipped radar, therefore, the radar system should have the ability to track multiple-targets accurately with high radar-resolutions. Recent developments in the state-of-the-art Intelligent Transportation Systems enable autonomous vehicles to offer significant safety services to take appropriate and prompt actions to avoid any probable unfortunate road-hazard. Lastly, the system is replicated for range resolution with four varying operational bandwidths from 600 MHz to 4 GHz. The system is simulated for detecting and ranging over 100 meters by analyzing received echoes and verifying the range frequency with theoretically calculated values while effective operation is measured in terms of received power under varying level of attenuation up to 75 dB/Km under rain and fog conditions. Impact of varying bandwidth is analyzed upon the performance of the proposed system using numerical simulations. For multiple targets detection, wavelength division multiplexing (WDM) scheme is used in conjugation with polarization division multiplexing (PDM) scheme. To achieve that, frequency modulated continuous wave (FMCW) based Photonic Radar is proposed. Futuristic transportation systems would be requiring more effective sensing system that are not only cost effective but also more efficient in sensing multiple targets while acquiring minimal area and utilizing low input power.
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