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Human perceptions of vehicle turning intention: overall performance and contributory factors

Human perceptions of vehicle turning intention: overall performance and contributory factors
Human perceptions of vehicle turning intention: overall performance and contributory factors
All pedestrians, drivers and cyclists regularly make predictions on where they think an oncoming vehicle is intending to travel, so that they can successfully and safely navigate road systems. Despite the importance of these predictions, the effectiveness of this process is currently poorly understood with all existing research being focused on predictions from in-vehicle technologies. This paper therefore investigates how well observers are able to predict a vehicle’s turning intention as it approaches an intersection and explores the explanatory variables involved in the success of this process through a logistic regression analysis. An interactive touch screen experiment was developed so that people’s predictions about turning intention could be investigated. The data set has been created with over 100 participants attempting to predict a number of vehicles’ turning intention.
The key findings of this study are that people are very good overall at predicting turning intention with approximately 90% median success rate when vehicles are between 0 and 20 meters (0-21.9 yards) away from the intersection, but with a substantial fall to approximately 70% median success rate when the vehicle is between 30 and 50 meters (32.8-54.7 yards) away. Other key explanatory variables include both vehicle specific factors (e.g. use of indicator lights) and crucially the intersection layout, providing valuable information on the relationship between intersection design and road safety
0361-1981
8-15
Hamilton, Andrew
479bec89-827c-4ed3-8569-12501d6d6162
Waterson, Ben
60a59616-54f7-4c31-920d-975583953286
Snell, Ian
d43b7f02-9903-4fac-ba4f-e1b1266d41f1
Hamilton, Andrew
479bec89-827c-4ed3-8569-12501d6d6162
Waterson, Ben
60a59616-54f7-4c31-920d-975583953286
Snell, Ian
d43b7f02-9903-4fac-ba4f-e1b1266d41f1

Hamilton, Andrew, Waterson, Ben and Snell, Ian (2015) Human perceptions of vehicle turning intention: overall performance and contributory factors. Transportation Research Record: Journal of the Transportation Research Board, 2458, 8-15. (doi:10.3141/2458-02).

Record type: Article

Abstract

All pedestrians, drivers and cyclists regularly make predictions on where they think an oncoming vehicle is intending to travel, so that they can successfully and safely navigate road systems. Despite the importance of these predictions, the effectiveness of this process is currently poorly understood with all existing research being focused on predictions from in-vehicle technologies. This paper therefore investigates how well observers are able to predict a vehicle’s turning intention as it approaches an intersection and explores the explanatory variables involved in the success of this process through a logistic regression analysis. An interactive touch screen experiment was developed so that people’s predictions about turning intention could be investigated. The data set has been created with over 100 participants attempting to predict a number of vehicles’ turning intention.
The key findings of this study are that people are very good overall at predicting turning intention with approximately 90% median success rate when vehicles are between 0 and 20 meters (0-21.9 yards) away from the intersection, but with a substantial fall to approximately 70% median success rate when the vehicle is between 30 and 50 meters (32.8-54.7 yards) away. Other key explanatory variables include both vehicle specific factors (e.g. use of indicator lights) and crucially the intersection layout, providing valuable information on the relationship between intersection design and road safety

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2014 [74] Perceptions of Turning TRB.pdf - Author's Original
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Published date: January 2015
Organisations: Transportation Group

Identifiers

Local EPrints ID: 375128
URI: http://eprints.soton.ac.uk/id/eprint/375128
ISSN: 0361-1981
PURE UUID: 7628aecd-4dbc-4cc1-8544-be0359b4327d
ORCID for Ben Waterson: ORCID iD orcid.org/0000-0001-9817-7119

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Date deposited: 13 Mar 2015 10:26
Last modified: 20 Jul 2019 01:12

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