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http://hdl.handle.net/1942/29759
Title: | Can Automated Vehicles Improve Cyclist Safety in Urban Areas? | Authors: | TAFIDIS, Pavlos PIRDAVANI, Ali BRIJS, Tom Farah, Haneen |
Issue Date: | 2019 | Source: | Safety (Basel), 5(3) (Art N° 57) | Abstract: | Automated vehicles (AVs) are expected to assist in decreasing road traffic fatalities, particularly among passenger cars. However, until now limited research has been conducted on how they will impact the safety of vulnerable road users (VRUs) (i.e., cyclists and pedestrians). Therefore, there is a clear need to start taking into account the interactions between AVs and VRUs as an integrated element of the transport network, especially in urban areas where they are dominant. The objective of this study is to verify whether the anticipated implementation of AVs can actually improve cyclists’ safety. For this purpose, the microscopic traffic flow simulation software PTV Vissim combined with the surrogate safety assessment model (SSAM) were utilized. The road network used for this analysis was generated based on a real study case in a medium-sized city in Belgium, where narrow streets in the city center are shared on many occasions between vehicles and cyclists. The findings of the analysis show a notable reduction in the total number of conflicts between cars, but also between cars and cyclists, compared to the current situation, assuming a 100% market penetration scenario for AVs. Moreover, the severity level of conflicts also decreased as a result of the lack of human-driven vehicles in the traffic streams. | Keywords: | road safety; cyclists; automated vehicles | Document URI: | http://hdl.handle.net/1942/29759 | Link to publication/dataset: | https://www.mdpi.com/2313-576X/5/3/57/htm | e-ISSN: | 2313-576X | DOI: | 10.3390/safety5030057 | Rights: | 2019 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 (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | Category: | A1 | Type: | Journal Contribution | Validations: | vabb 2021 |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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safety-05-00057.pdf | Published version | 4.54 MB | Adobe PDF | View/Open |
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