Bosch Future Mobility Challenge 2022: Our team at UNLV participated in BFMC 2022. We were given a 1/10 car with a raspberry pi 4 processor and PiCamera. The car should navigate through a smart miniature city autonomously. We employed a traffic sign and other road object detection systems by creating a dataset of around 2000 images and trained a lightweight SSD MobileNet model. Since Pi is not suitable for running a deep learning model, we used an additional Intel Neural Computing stick to accelerate the computation. Besides, we implemented an image processing based lane detection model. It removes the noise from the image, then thresholds the birds eye view image to get the binary image of lane markings. Next, recognize the lane markings by calculating the histograms. Finally, We set up the track in our lab room to test the car in real-time. Our car can successfully drive itself on that track and we got selected for the final event as a result.