Abstract
Intelligent Transportation Systems rely on understanding, predicting and affecting the interactions between vehicles. The goal of this paper is to choose a small subset from the larger set so that the resulting regression model is simple, yet have good predictive ability for Vehicle agent speed relative to Vehicle intruder. The method of ANFIS (adaptive neuro fuzzy inference system) was applied to the data resulting from these measurements. The ANFIS process for variable selection was implemented in order to detect the predominant variables affecting the prediction of agent speed relative to intruder. This process includes several ways to discover a subset of the total set of recorded parameters, showing good predictive capability. The ANFIS network was used to perform a variable search. Then, it was used to determine how 9 parameters (Intruder Front sensors active (boolean), Intruder Rear sensors active (boolean), Agent Front sensors active (boolean), Agent Rear sensors active (boolean), RSSI signal intensity/strength (integer), Elapsed time (in seconds), Distance between Agent and Intruder (m), Angle of Agent relative to Intruder (angle between vehicles °), Altitude difference between Agent and Intruder (m)) influence prediction of agent speed relative to intruder. The results indicated that distance between Vehicle agent and Vehicle intruder (m) and angle of Vehicle agent relative to Vehicle Intruder (angle between vehicles °) is the most influential parameters to Vehicle agent speed relative to Vehicle intruder.
Highlights
Cyber-Physical Systems (CPS) is emerging as an integrative research field aimed toward a new generation of engineered systems [1]
A comprehensive search was performed from the given inputs in order to choose the set of the ultimate optimal combination inputs, Table 2 which has the most impact and influence on the output parameter, Table 3
An ANFIS model is built by the functions for each combination and they are respectively trained for single epoch
Summary
Cyber-Physical Systems (CPS) is emerging as an integrative research field aimed toward a new generation of engineered systems [1]. CPSs are mostly distributed parameter systems (DPSs) which combine real-time computing, embedded systems, wireless sensor networks, control theory, signal processing and knowledge creation using artificial intelligence [2]. Vehicle Agent Speed Relative to Vehicle Intruder by TUD COST TU 1102 “ARTS – Towards Autonomic Road Transport Support Systems” and FP7 Project 316087 ACOMIN “Advance Computing and Innovation”.
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