Review on Cars and Pedestrian Detection - D. Deshmukh, Akshay; Gupta, Sanchit; Donge, Ambalika; Katolkar, Piyush; Tipre, Abhishek; A. Bairagi, Rakesh (International Journal of Recent Advances in Multidisciplinary Topics, 2021)
Electronic systems that can identify pedestrians in front of a vehicle and forecast vehicle-to-pedestrian collisions must be specified, implemented, and evaluated. Vehicle-to-pedestrian collisions were categorised into eleven different scenarios in this study. The key features of vehicle-to-pedestrian collisions have been established. The statistical behaviours of the various systems involved were modelled (vehicle, pedestrian, environment, and advanced driver assistance gadgets). Then, for crucial automobile and pedestrian road conditions, Monte-Carlo simulations were run. The created simulation tool enables the evaluation and validation of possible innovative systems’ performance. Intelligent video surveillance, intelligent transportation, automotive autonomous driving, and driver-assistance systems all use cars and pedestrian detection. For the implementation of automobiles and pedestrian detection in a video segment, we chose OpenCV as the programming tool. This programme will be written in Python and will make use of OpenCV.