Determinants of driver response to variable message sign information in Athens
- Author(s): Ioanna Spyropoulou 1 and Constantinos Antoniou 1
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View affiliations
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Affiliations:
1:
School of Rural and Surveying Engineering, National Technical University of Athens, Zografou, Athens, Greece
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Affiliations:
1:
School of Rural and Surveying Engineering, National Technical University of Athens, Zografou, Athens, Greece
- Source:
Volume 9, Issue 4,
May 2015,
p.
453 – 466
DOI: 10.1049/iet-its.2014.0053 , Print ISSN 1751-956X, Online ISSN 1751-9578
Variable message signs – which comprise a type of advanced traveller information systems – can affect driver behaviour, especially considering route choice. Hence, their operation is integrated in traffic management strategies for the mitigation of traffic congestion. This research explores the factors determining driver response to variable message signs (VMSs) in the city of Athens. A stated preference questionnaire survey is undertaken and discrete choice analysis is performed towards this aim. More specifically, a random-effect ordered probit model is estimated that provides insight on the contributory factors that influence driver propensity to divert, when provided with information on incident occurrence via VMSs. Message characteristics, that is, incident type, impact and suggestion for an alternative route, trip characteristics, such as vehicle type, as well as, driver characteristics, such as driver age and income, have been found to affect driver behaviour. Furthermore, appropriate models are also estimated for subsets of the driving population (considering gender and age) and specific similarities and differences between the population behaviours are identified.
Inspec keywords: driver information systems; road traffic control; behavioural sciences computing
Other keywords: driver diversion propensity; trip characteristics; traffic management strategies; traffic congestion mitigation; driver response determinants; driver characteristics; driver gender; incident occurrence information; driving population; VMS; driver behaviour; driver age; message characteristics; Athens city; variable message sign information; vehicle type; random-effect ordered probit model; incident type; route choice; driver income; incident impact; advanced traveller information systems; alternative route suggestion
Subjects: Social and behavioural sciences computing; Traffic engineering computing
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