An Intelligent Multi-Speed Advisory System using Improved Whale Optimisation Algorithm

TL;DR

This paper presents an improved whale optimisation algorithm to develop a multi-speed advisory system that reduces CO2 emissions for vehicles on urban highways by recommending multiple optimal speeds.

Contribution

It introduces a novel optimisation framework capable of handling implicit cost functions and recommending multiple speeds for different vehicle groups in urban settings.

Findings

Reduces CO2 emissions effectively.

Provides multiple speed recommendations for vehicle groups.

Outperforms previous algorithms in urban highway scenarios.

Abstract

An intelligent speed advisory system can be used to recommend speed for vehicles travelling in a given road network in cities. In this paper, we extend our previous work where a distributed speed advisory system has been devised to recommend an optimal consensus speed for a fleet of Internal Combustion Engine Vehicles (ICEVs) in a highway scenario. In particular, we propose a novel optimisation framework where the exact format of each vehicle's cost function can be implicit, and our algorithm can be used to recommend multiple consensus speeds for vehicles travelling on different lanes in an urban highway scenario. Our studies show that the proposed scheme based on an improved whale optimisation algorithm can effectively reduce CO2 emission generated from ICEVs while providing different recommended speed options for groups of vehicles.