Pritesh Patil

• Master of Science
• Graduate Research Assistant at Western Michigan University

div class="section abstract"> Traditional autonomous vehicle perception subsystems that use onboard sensors have the drawbacks of high computational load and data duplication. Infrastructure-based sensors, which can provide high quality information without the computational burden and data duplication, are an alternative to traditional autonomous v...

div class="section abstract"> Lane detection plays a critical role in autonomous vehicles for safe and reliable navigation. Lane detection is traditionally accomplished using a camera sensor and computer vision processing. The downside of this traditional technique is that it can be computationally intensive when high quality images at a fast frame...

div class="section abstract"> Evaluating real-world hazards associated with perception subsystems is critical in enhancing the performance of autonomous vehicles. The reliability of autonomous vehicles perception subsystems are paramount for safe and efficient operation. While current studies employ different metrics to evaluate perception subsyste...

Safe autonomous vehicle (AV) operations depend on an accurate perception of the driving environment, which necessitates the use of a variety of sensors. Computational algorithms must then process all of this sensor data, which typically results in a high on-vehicle computational load. For example, existing lane markings are designed for human drive...

Advancements in driving automation systems such as Lane Keeping Assist has shown improvements in safety by reducing traffic accidents. Nonetheless, despite the promise of these technologies, some studies have shown statistical data that such systems have a poor resilient operation. Therefore, there is a need to design more robust and resilient Adva...