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Further compelling evidence for safety-in-numbers: It is more than meets the eye

Further compelling evidence for safety-in-numbers: It is more than meets the eye
Further compelling evidence for safety-in-numbers: It is more than meets the eye

In the extant road safety literature, estimating safety-in-numbers is dominated by conventional cross-sectional methods in which active mode (pedestrian or cyclist) volume together with motorised traffic volume are present in regression models explaining active mode safety directly. There is “direct” evidence for safety-in-numbers when the coefficient associated with active mode volume is negative (safety improves as volume increases) or when it is smaller than one (safety decreases at a lower rate compared to the rate of increase in active mode volume). In this article we extend the concept of safety-in-numbers in the traffic safety field, introducing “indirect” safety-in-numbers, which constitutes a new form of evidence for this phenomenon. We provide empirical evidence to support this, discussing that using an approach based on heterogeneity in mean modelling–a form of random parameters (slopes) models–it is possible to reveal “indirect” safety-in-numbers effects. Therefore, such models can reveal further compelling evidence for safety-in-numbers. Accurate knowledge of safety-in-numbers effects (both direct and indirect) and their underlying mechanisms can help provide robust motives for promoting active travel and will have valuable implications for the design of road safety interventions.

Cross-sectional models, Cyclist, Endogeneity models, Heterogeneity in mean models, Pedestrian, Safety-in-numbers
0001-4575
Heydari, Shahram
0d12a583-a4e8-4888-9e51-a50d312be1e9
Elvik, Rune
25638473-5379-4b79-a6ec-79cb86a6cb58
Heydari, Shahram
0d12a583-a4e8-4888-9e51-a50d312be1e9
Elvik, Rune
25638473-5379-4b79-a6ec-79cb86a6cb58

Heydari, Shahram and Elvik, Rune (2023) Further compelling evidence for safety-in-numbers: It is more than meets the eye. Accident Analysis & Prevention, 179, [106902]. (doi:10.1016/j.aap.2022.106902).

Record type: Article

Abstract

In the extant road safety literature, estimating safety-in-numbers is dominated by conventional cross-sectional methods in which active mode (pedestrian or cyclist) volume together with motorised traffic volume are present in regression models explaining active mode safety directly. There is “direct” evidence for safety-in-numbers when the coefficient associated with active mode volume is negative (safety improves as volume increases) or when it is smaller than one (safety decreases at a lower rate compared to the rate of increase in active mode volume). In this article we extend the concept of safety-in-numbers in the traffic safety field, introducing “indirect” safety-in-numbers, which constitutes a new form of evidence for this phenomenon. We provide empirical evidence to support this, discussing that using an approach based on heterogeneity in mean modelling–a form of random parameters (slopes) models–it is possible to reveal “indirect” safety-in-numbers effects. Therefore, such models can reveal further compelling evidence for safety-in-numbers. Accurate knowledge of safety-in-numbers effects (both direct and indirect) and their underlying mechanisms can help provide robust motives for promoting active travel and will have valuable implications for the design of road safety interventions.

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Safety in numbers - AAP R1 to Melanie - Accepted Manuscript
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Accepted/In Press date: 15 November 2022
e-pub ahead of print date: 21 November 2022
Published date: 1 January 2023
Additional Information: Publisher Copyright: © 2022 The Authors
Keywords: Cross-sectional models, Cyclist, Endogeneity models, Heterogeneity in mean models, Pedestrian, Safety-in-numbers

Identifiers

Local EPrints ID: 472932
URI: http://eprints.soton.ac.uk/id/eprint/472932
ISSN: 0001-4575
PURE UUID: 705b43e8-3418-47f5-9b3d-ccb0ada091ba

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Date deposited: 06 Jan 2023 12:48
Last modified: 16 Mar 2024 23:22

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Contributors

Author: Shahram Heydari
Author: Rune Elvik

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