technical Insights
Advanced algorithms and approaches for vehicle telematics Shamil Mirkhanov Navixy
M
odern telematics platforms utilize various advanced algorithms to address common tasks such as vehicle routing, face recognition, driver behavior identification, ecodriving, and vehicle classification. Here we consider only a few such algorithms and describe the cases where they either might or have been used.
Algorithms and cases To begin with, let’s consider some approaches to vehicle routing. The possibility to determine, modify, and optimize possible routes is a crucial feature for any telematics platform. One approach to vehicle routing could be provided by game theory. A potential of game theory in the building and analysis of behavioral models could be successfully utilized to address logistics and fleet management problems.
Assume that node O is connected to the rest of the network through connection points A and B, where A is a little closer than B. However, both connection points get easily congested, therefore sending both streams via the same connection point would result in an extra delay. Favorable outcomes in this game would be for the two players to “coordinate� and send their traffic through different connection points. On practical case one have to deal with a decent amount of fleets and need to optimize the route for each of them. 28 | Telematics Wire | October 2020
It is a really challenging task to deal with and there are various smart algorithms, methods, and programming paradigms being used and developed to provide some practical solutions. Navixy utilize smart algorithms combined with advanced features of constraint programming and multipurpose meta-heuristic techniques to account for everyday fleet management needs and addressing VRP in a highly
efficient and customer-beneficial way. By simply clicking on the route optimization button, a dispatcher will instantly get the optimal sequence of locations to visit on the map. One-click and all the points line up in the most effective route. Another example is face recognition routine in MDVR systems. Facial recognition performs capturing and analysis with further comparison of specific face patterns based on the facial
