Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/39926
Title: The Effectiveness of an Intelligent Speed Assistance System with Real-Time Speeding Interventions for Truck Drivers: A Belgian Simulator Study
Authors: DE VOS, Bart 
CUENEN, Ariane 
ROSS, Veerle 
DIRIX, Hélène 
BRIJS, Kris 
BRIJS, Tom 
Issue Date: 2023
Publisher: MDPI
Source: Sustainability, 15 (6) (Art N° 5226)
Abstract: Speeding is one of the leading risk factors in road safety. Not only is it one of the leading causes of accidents, but it also has an extensive effect on the impact and consequences of accidents. This is especially the case for trucks, where the enforced speed limit is often dependent on local legislation and context rather than speed limit traffic signs. This study is part of the greater i-DREAMS project and aims to explore the effectiveness of an intelligent speed assistance system for truck drivers on different road types. To achieve this, a simulator experiment was performed with 34 professional truck drivers in Belgium. Participants first made a baseline drive, followed by two more drives, where they received visual information about the enforced speed limit but also visual and auditory warnings when exceeding the speed limit. The drives included different road environments with different speed limits. The results reveal a significant reduction in relevant parameters (i.e., average speed, minimum speed, maximum speed, and percentage of distance above the speed limit) when drivers received information and warnings about speeding while driving on a rural 1 × 1 road with a speed limit of 70 km/h (60 km/h for trucks). Further research is needed to validate this effect on other road types and under more-challenging conditions.
Keywords: truck simulator;speeding;intelligent speed assistance;interventions;driving behavior
Document URI: http://hdl.handle.net/1942/39926
e-ISSN: 2071-1050
DOI: 10.3390/su15065226
ISI #: 000968608400001
Rights: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution
Category: A1
Type: Journal Contribution
Appears in Collections:Research publications

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