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The evolution of driver route switching behavior in stochastically perturbed networks

The evolution of driver route switching behavior in stochastically perturbed networks
The evolution of driver route switching behavior in stochastically perturbed networks
Traffic assignment, the process of ‘assigning’ expected vehicle origin-destination flows to discrete routes traversing a road network, has traditionally been approached as an optimization problem yielding one fixed set of ‘equilibrium’ road link flows. This approach has been criticized for oversimplifying both traveler behavior representation and the effects of stochastic variations in network conditions. Here the connection is explored between day-to-day driver learning models and correlated perturbations occurring spatially around the network on simulated ‘days’. As elsewhere in the literature, a perturbation is defined as any incident which increases travel time along the perturbed stretch of road for the same level of demand. Equipped with a plausible correlation learning mechanism, drivers are modeled inferring downstream road conditions without the need for signage provision such that strategic en-route path switching can occur with the goal of potentially avoiding delays. It is found that when drivers can undertake strategic behavior the negative impact of perturbations is lessened due to some drivers diverting upstream to avoid them, meaning that potentially delayed routes are seen as relatively more attractive when compared against the outcome when no driver is modeled as being able to switch as is captured by existing assignment techniques. Thus even on days where no perturbations occur, initial driver route choices differ when compared against traditional algorithmic assignment results.
Snowdon, James
48a26581-eba4-41ed-955d-ca84e5aa6908
Waterson, Ben
60a59616-54f7-4c31-920d-975583953286
Fangohr, Hans
9b7cfab9-d5dc-45dc-947c-2eba5c81a160
Snowdon, James
48a26581-eba4-41ed-955d-ca84e5aa6908
Waterson, Ben
60a59616-54f7-4c31-920d-975583953286
Fangohr, Hans
9b7cfab9-d5dc-45dc-947c-2eba5c81a160

Snowdon, James, Waterson, Ben and Fangohr, Hans (2012) The evolution of driver route switching behavior in stochastically perturbed networks. 4th International Symposium on Dynamic Traffic Assignment (DTA2012), Martha's Vinyard, United States. 03 - 05 Jun 2012. 19 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

Traffic assignment, the process of ‘assigning’ expected vehicle origin-destination flows to discrete routes traversing a road network, has traditionally been approached as an optimization problem yielding one fixed set of ‘equilibrium’ road link flows. This approach has been criticized for oversimplifying both traveler behavior representation and the effects of stochastic variations in network conditions. Here the connection is explored between day-to-day driver learning models and correlated perturbations occurring spatially around the network on simulated ‘days’. As elsewhere in the literature, a perturbation is defined as any incident which increases travel time along the perturbed stretch of road for the same level of demand. Equipped with a plausible correlation learning mechanism, drivers are modeled inferring downstream road conditions without the need for signage provision such that strategic en-route path switching can occur with the goal of potentially avoiding delays. It is found that when drivers can undertake strategic behavior the negative impact of perturbations is lessened due to some drivers diverting upstream to avoid them, meaning that potentially delayed routes are seen as relatively more attractive when compared against the outcome when no driver is modeled as being able to switch as is captured by existing assignment techniques. Thus even on days where no perturbations occur, initial driver route choices differ when compared against traditional algorithmic assignment results.

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More information

Published date: June 2012
Venue - Dates: 4th International Symposium on Dynamic Traffic Assignment (DTA2012), Martha's Vinyard, United States, 2012-06-03 - 2012-06-05
Organisations: Transportation Group

Identifiers

Local EPrints ID: 344693
URI: http://eprints.soton.ac.uk/id/eprint/344693
PURE UUID: 95c2f4d5-d5bc-48a9-bad6-e0700fa17a69
ORCID for Ben Waterson: ORCID iD orcid.org/0000-0001-9817-7119
ORCID for Hans Fangohr: ORCID iD orcid.org/0000-0001-5494-7193

Catalogue record

Date deposited: 02 Nov 2012 16:39
Last modified: 11 Dec 2021 03:32

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Contributors

Author: James Snowdon
Author: Ben Waterson ORCID iD
Author: Hans Fangohr ORCID iD

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