Urban traffic state estimation for signal control using
mixed data sources and the extended Kalman filter
Urban traffic state estimation for signal control using
mixed data sources and the extended Kalman filter
This paper describes a methodology for fusing data from multiple sensors, including wireless devices and inductive loops, to make an estimation of the instantaneous state of an urban traffic network. An extended Kalman filter is employed along with a state evolution model to make estimates of the state in a discretized network. The instantaneous state is an estimate of the current distribution of vehicles in the network and their instantaneous speeds. Microsimulation tests were used to evaluate the performance of the state estimation on a small urban networks. These results indicate low error between the estimated state and the known ground truth.
Box, S.
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Snell, I.
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Waterson, B.
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Wilson, R.E.
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January 2013
Box, S.
2bc3f3c9-514a-41b8-bd55-a8b34fd11113
Snell, I.
f84d7acc-0223-4b4b-954a-2c825dbcace7
Waterson, B.
60a59616-54f7-4c31-920d-975583953286
Wilson, R.E.
613f4def-6dfa-4a60-8f89-4006f2059f09
Box, S., Snell, I., Waterson, B. and Wilson, R.E.
(2013)
Urban traffic state estimation for signal control using
mixed data sources and the extended Kalman filter.
92nd Annual Meeting of the Transportation Research Board, , Washington, United States.
13 - 17 Jan 2013.
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper describes a methodology for fusing data from multiple sensors, including wireless devices and inductive loops, to make an estimation of the instantaneous state of an urban traffic network. An extended Kalman filter is employed along with a state evolution model to make estimates of the state in a discretized network. The instantaneous state is an estimate of the current distribution of vehicles in the network and their instantaneous speeds. Microsimulation tests were used to evaluate the performance of the state estimation on a small urban networks. These results indicate low error between the estimated state and the known ground truth.
Text
trbTrafficStateEstimation.pdf
- Author's Original
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Published date: January 2013
Venue - Dates:
92nd Annual Meeting of the Transportation Research Board, , Washington, United States, 2013-01-13 - 2013-01-17
Organisations:
Transportation Group
Identifiers
Local EPrints ID: 350159
URI: http://eprints.soton.ac.uk/id/eprint/350159
PURE UUID: aeb5d7c3-f1e5-4b28-b31e-639e03281e00
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Date deposited: 19 Mar 2013 15:15
Last modified: 15 Mar 2024 02:58
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Contributors
Author:
S. Box
Author:
I. Snell
Author:
R.E. Wilson
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