Sensor Technology in Intelligent Transportation Systems - Lane Departure Warnings

This study offers a thorough analysis of the vital role that mobility plays in economic growth, especially in emerging nations where the proliferation of vehicles and the deterioration of infrastructure coexist. In order to synthesise previous research on the topic and determine if Lane Departure Technology is beneficial in reducing traffic accidents, the study used a scoping review methodology. In order to analyse the significance of the technology adoption in the reduction of detrimental effects that transportation activities have on the environment and society, the study emphasises the necessity of Smart Transportation Systems (STS), sometimes referred to as Intelligent Transportation Systems (ITS). According to the study, a variety of sensors—including infrastructure-, vehicle-, and device-based sensors—are critical to the efficiency of ITS. These sensors gather data in real time for traffic control and safety enhancements. A key component of this system is Lane Departure Warning Systems (LDWS), which use sensors like cameras, Lidar, or radar to track lane locations and issue alarms, greatly enhancing road safety. However, the result points out a number of obstacles to the broad use of ITS and LDWS, including sensor limitations, environmental considerations, high prices, and privacy issues, especially in poor nations. Notwithstanding these difficulties, LDWS has been demonstrated to improve overall vehicle performance and traffic flow by raising driver awareness and lowering accident rates. Promising improvements in lane recognition accuracy and driver behaviour prediction are possible with the incorporation of AI and machine learning into LDWS. In order to create safer and more effective transport systems, this study emphasises the significance of ongoing investment and innovation in ITS and LDWS.

Intelligent Transportation System (ITS), Sensor, Artificial Intelligence (AI)

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