Analysis and design of fuzzy-based manoeuvring model for mid-vehicle collision avoidance system

Abstract

This paper offers a fuzzy-based manoeuvring model labeled as Fuzzy-based Midvehicle Collision Avoidance System (FMCAS) resolving two road crash scenarios. The first scenario covers dual situations (a) Mid vehicle collision avoidance with the rear vehicle under no front vehicle condition and (b) Curvilinear path strategy based on real road conditions. While the suitable curvilinear motion to fit the constrained path for parallel parking is the other scenario. Curvilinear fitting strategy on the left and right sides is achieved by the mid (host) vehicle using fuzzy interpolation techniques modeled by FMCAS. Also, the offset-based curvilinear path determined by FMCAS automatically fits the constraint path to avoid vehicle crashes in highly occupied lanes. In this methodology, path constraint is applicable for both scenarios in forward and reverse directions. The appropriate constraint paths estimated using the developed fuzzy-based polynomial fitting addresses the diverse vehicle kinematic issues. Mean square error values of $$3.9443 \\times {10}^{-28}$$\n m and 0.0148–0.7210\xa0m about the proposed fuzzy respect to crisp and FMCAS are also capable of delivering diverse consequents in highly intact road scenarios. The fuzzy rule base is motivated in this research article to obtain a collision-free environment addressing many collision conditions in the real-time scenario.