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Introduction
In the contemporary digitalized world, the application of various technologies has found its positive feedback across multiple spheres. One of the most significant technologies that have yielded numerous opportunities for airline route regulation, autonomous vehicle functioning, weather forecasting, environmental protection, and others is Radio Detecting and Ranging (RADAR). It is a detection system that utilizes radio waves to analyze spatial and temporal data.
It is a valuable tool that enables visualizing the placement of objects and advances the opportunities for autonomous driving. Overall, the application of different frequency waves allows for expanding the range of options for technology implementation. This paper is designed to analyze and explain how RADAR technology is used for operating automated vehicles with particular insight into sustainability and improvement issues as addressed by the technology.
RADAR Technology Overview
In order to analyze the technologys potential to solve some operational and information-related problems, one should clarify how the technology works and what data it produces. According to Taylor (2018), RADAR technology is a complex system that entails the generation of electromagnetic waves, the characteristics of the reflection of which signalizes the distance to objects, their speed, and direction. The specifications of wave reflection provide frequency- and length-related data that can further be interpreted for operational decision-making. RADARs are commonly used in aviation to obtain information about the space in the air for aircraft to find safe routes. According to research, there are 143 operational WSR-88Ds and 44 Federal Aviation Administration (FAA) Terminal Doppler Weather Radars on the territory of the continental USA. (Cho & Kurdzo, 2019, p. 972).
The primary purpose of these RADARS is providing hazardous wind shear alerts for aircraft landing and taking off at airports (Cho & Kurdzo, 2019, p. 972). Nonetheless, these data are available to the general public and weather forecasters, who might benefit from knowing the meteorological details. While RADARs play an essential role in guiding and alerting aircraft, this technology deems applicable to land transportation controlling. In particular, the rapidly evolving sphere of automated vehicles and computerized driving provides a new option for RADAR application.
Analysis of RADAR Technology as Applied to Automated Vehicles
Throughout past several decades, RADAR technologies have penetrated multiple spheres of life, affecting such everyday concerns as weather forecasts or highly digitalized processes like automated cars control. For example, weather radars have emerged as a new measurement technique that is capable of providing areal precipitation information with high spatial and temporal resolution and put precipitation monitoring on a new level (Kreklow, 2020, p. 1). This particularity allows for effective utilization of RADARs for analyzing the space, objects, their velocity, distance, and movement direction when developing automation syst4ems for driverless cars.
Indeed, different types of RADARs with various particular features are applied to regulating the movement of automated vehicles. In the context of the contemporary advancement of driverless vehicles, the relevance of RADAR technologies grows due to the use of several sensors. According to Zhou et al. (2020), sensors, controllers, actuators, and other devices as well as a variety of technologies such as environmental perception, high precision self-localization, decision-making, and motion planning are applied (p. 1). For example, the use of millimeter-wave (MMW) radar data provides multiple benefits since it is low in cost, precise, adaptable to the environment, has a long measuring distance, and has dynamic detection (Zhou et al., 2020).
In combination with another RADAR technology, Long Range Radar (LRR), which can detect targets within the range of 250 m, safe car driving is ensured (Zhou et al., 2020, p. 1). In addition, an important phenomenon that is used in RADAR applications to automated cars is the Doppler effect which deals with the change in wave frequency depending on the direction of two objects movement (Zhou et al., 2020).
The availability of tools and devices that are capable of gathering and processing such data provides multiple opportunities for safer and more machine-controlled driving. However, the implementation of RADAR to automated driving is still a work in progress since there are some inaccuracies in data analysis. Although there are difficulties in detecting non-moving objects such as pedestrians, there are significant improvements in the application of the technology to enhanced road safety (Combs et al., 2019). Thus, the intensification of RADAR technology advancement for automated cars is a beneficial effort that should be addressed by specialists and scholars.
Conclusion
In summary, the presented analysis of the application of RADAR technologies to such a complex and developing area as automated driving showed that the currently used devices deem effective but require improvement. The advancement in the usage of wave frequency interpretation has allowed people to develop several technological tools that enable safe aircraft movement, weather forecasting, and automated vehicle controlling. The implementation of such technological solutions as MMW radars and LRR in combination with other sensors helps ensure safe car driving and fewer road fatalities. Therefore, it is essential to continue working on the refining of RADAR technology use for transportation to ensure better safety outcomes.
References
Cho, J. Y., & Kurdzo, J. M. (2019). Weather radar network benefit model for tornadoes. Journal of Applied Meteorology and Climatology, 58(5), 971-987.
Combs, T. S., Sandt, L. S., Clamann, M. P., & McDonald, N. C. (2019). Automated vehicles and pedestrian safety: Exploring the promise and limits of pedestrian detection. American Journal of Preventive Medicine, 56(1), 1-7.
Kreklow, J. (2020). Improving usability of weather radar data in environmental sciences: Potentials, challenges, uncertainties and applications [Doctoral dissertation, Institutionelles Repositorium der Leibniz Universität Hannover].
Taylor, J. D. (Ed.). (2018). Ultra-wideband radar technology. CRC Press.
Zhou, T., Yang, M., Jiang, K., Wong, H., & Yang, D. (2020). MMW radar-based technologies in autonomous driving: A review. Sensors, 20(24), 7283.
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