Speed Profile Definition for GLOSA Implementation on Buses Based on Statistical Analysis of Experimental Data

TL;DR

This paper develops a statistical methodology to define bus speed profiles for GLOSA systems, enhancing traffic flow optimization in urban environments by considering real-world bus behavior and traffic signal synchronization.

Contribution

It introduces a novel data-driven approach to create realistic bus speed profiles tailored for GLOSA implementation, based on extensive experimental data analysis.

Findings

Defined robust statistical bus motion profiles

Incorporated road topology and signal timings into speed profile design

Provided practical insights for urban GLOSA system deployment

Abstract

Intelligent Transportation Systems (ITS) are pushing an increasing interest and development when dealing with eco-driving systems. In this framework, this paper presents a method to define speed profiles specifically designed for Green Light Optimal Speed Advisory (GLOSA) systems on buses. GLOSA aims to optimize traffic flow by providing vehicles with real-time speed recommendations synchronized with traffic signal timings. Leveraging statistical analysis of experimental data collected from an urban bus, the study develops a methodology to extract meaningful insights into bus behaviour and traffic dynamics. The proposed approach considers road topology, scheduled bus stops, and signal timings to define simple although suitable speed profiles considering the peculiarities of the motion of a bus in an urban scenario. Through extensive data collection robust statistical data are defined, allowing the definition of vehicle motion profile for effectively develop and implement GLOSA systems. This research contributes to the advancement of Intelligent Transportation Systems by providing realistic data and practical insights for optimizing bus operations in urban environments.