Investigating the effects of mixed driver reaction times in the transport network
Investigating the effects of mixed driver reaction times in the transport network
Given the advances in autonomous vehicle technology, vehicles may soon be able
to drive as well as humans. Here, autonomous vehicles are approximated as drivers with reaction times smaller than those of human drivers, but with the same driving competency. Experiments were performed to simulate the effects of loading the transport network with increasingly high proportions of vehicles with faster than normal reaction times, on four different road models.
intelligent transport systems, Autonomous vehicles, driver characteristics
Rafter, Craig, Benjamin
8f56b72d-8984-47e4-ae2a-f38a68fbad14
Box, Simon
2bc3f3c9-514a-41b8-bd55-a8b34fd11113
Rafter, Craig, Benjamin
8f56b72d-8984-47e4-ae2a-f38a68fbad14
Box, Simon
2bc3f3c9-514a-41b8-bd55-a8b34fd11113
Rafter, Craig, Benjamin and Box, Simon
(2016)
Investigating the effects of mixed driver reaction times in the transport network.
5th Symposium of the European Association for Research in Transportation (hEART), Lijm & Cultuur, Delft, Netherlands.
13 - 16 Sep 2016.
1 pp
.
(doi:10.13140/RG.2.2.25157.35044).
Record type:
Conference or Workshop Item
(Poster)
Abstract
Given the advances in autonomous vehicle technology, vehicles may soon be able
to drive as well as humans. Here, autonomous vehicles are approximated as drivers with reaction times smaller than those of human drivers, but with the same driving competency. Experiments were performed to simulate the effects of loading the transport network with increasingly high proportions of vehicles with faster than normal reaction times, on four different road models.
Text
cbrafter_hEART_poster_final
- Version of Record
More information
e-pub ahead of print date: 1 September 2016
Venue - Dates:
5th Symposium of the European Association for Research in Transportation (hEART), Lijm & Cultuur, Delft, Netherlands, 2016-09-13 - 2016-09-16
Keywords:
intelligent transport systems, Autonomous vehicles, driver characteristics
Identifiers
Local EPrints ID: 414451
URI: http://eprints.soton.ac.uk/id/eprint/414451
PURE UUID: 2ac334f1-be30-4f1f-bc83-f085b905b4f8
Catalogue record
Date deposited: 29 Sep 2017 16:31
Last modified: 15 Mar 2024 16:11
Export record
Altmetrics
Contributors
Author:
Craig, Benjamin Rafter
Author:
Simon Box
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics