{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T00:17:23Z","timestamp":1776903443522,"version":"3.51.2"},"reference-count":36,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,6,8]],"date-time":"2020-06-08T00:00:00Z","timestamp":1591574400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The objective of this paper is to study the effect of travel time information on day-to-day driver route choice behavior. A real-world experimental study is designed to have participants repeatedly choose between two alternative routes for five origin-destination pairs over multiple days after providing them with dynamically updated travel time information (average travel time and travel time variability). The results demonstrate that historical travel time information enhances behavioral rationality by 10% on average and reduces inertial tendencies to increase risk seeking in the gain domain. Furthermore, expected travel time information is demonstrated to be more effective than travel time variability information in enhancing rational behavior when drivers have limited experiences. After drivers gain sufficient knowledge of routes, however, the difference in behavior associated with the two information types becomes insignificant. The results also demonstrate that, when drivers lack experience, the faster less reliable route is more attractive than the slower more reliable route. However, with cumulative experiences, drivers become more willing to take the more reliable route given that they are reluctant to become risk seekers once experience is gained. Furthermore, the effect of information on driver behavior differs significantly by participant and trip, which is, to a large extent, dependent on personal traits and trip characteristics.<\/jats:p>","DOI":"10.3390\/s20113257","type":"journal-article","created":{"date-parts":[[2020,6,9]],"date-time":"2020-06-09T06:34:16Z","timestamp":1591684456000},"page":"3257","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Empirical Study of Effect of Dynamic Travel Time Information on Driver Route Choice Behavior"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8993-3813","authenticated-orcid":false,"given":"Jinghui","family":"Wang","sequence":"first","affiliation":[{"name":"Center for Sustainable Mobility, Virginia Tech Transportation Institute, 3500 Transportation Research Drive, Blacksburg, VA 24061, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5845-2929","authenticated-orcid":false,"given":"Hesham","family":"Rakha","sequence":"additional","affiliation":[{"name":"Center for Sustainable Mobility, Virginia Tech Transportation Institute, 3500 Transportation Research Drive, Blacksburg, VA 24061, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1287\/trsc.11.3.253","article-title":"On stochastic models of traffic assignment","volume":"11","author":"Daganzo","year":"1977","journal-title":"Transp. 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