{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T06:03:35Z","timestamp":1760853815123,"version":"3.38.0"},"reference-count":41,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Transportation Research Record: Journal of the Transportation Research Board"],"published-print":{"date-parts":[[2014,1]]},"abstract":"<jats:p> Transportation systems are inherently uncertain because of random disruptions; nevertheless, real-time information can help travelers make better route choices under such disruptions. The first revealed-preference study of routing policy choice is presented. A \u201crouting policy\u201d is defined as a decision rule applied at each link that maps possible realized traffic conditions to decisions to be made on the link next. The policy represents a traveler's ability to incorporate real-time information not yet available at the time of decision. Two case studies are conducted in Stockholm, Sweden, and in Singapore. Data for the underlying stochastic time-dependent network are generated from taxi GPS traces through map-matching and nonparametric link travel time estimation. An efficient algorithm to find the optimal routing policy in large-scale networks is first presented, which is a building block of any routing policy choice set generation method. The routing policy choice sets are then generated by link elimination and simulation. The generated choice sets are first evaluated on the basis of whether they include the observed traces on a specific day, or coverage. The sets are then evaluated on the basis of \u201cadaptiveness,\u201d defined as the capability of a routing policy to be realized as different paths over different days. A combination of link elimination and simulation methods yields satisfactory coverage. The comparison with a path choice set benchmark also suggests that a routing policy choice set could potentially provide better coverage and capture the adaptive nature of route choice. <\/jats:p>","DOI":"10.3141\/2466-09","type":"journal-article","created":{"date-parts":[[2015,3,6]],"date-time":"2015-03-06T02:07:44Z","timestamp":1425607664000},"page":"76-86","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":9,"title":["Routing Policy Choice Set Generation in Stochastic Time-Dependent Networks"],"prefix":"10.1177","volume":"2466","author":[{"given":"Jing","family":"Ding","sequence":"first","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Massachusetts, Amherst, 139 Marston Hall, 130 Natural Resources Road, Amherst, MA 01003."}]},{"given":"Song","family":"Gao","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Massachusetts, Amherst, 139 Marston Hall, 130 Natural Resources Road, Amherst, MA 01003."}]},{"given":"Erik","family":"Jenelius","sequence":"additional","affiliation":[{"name":"Department of Transport Science, Division of Traffic and Logistics, KTH Royal Institute of Technology, Teknikringen 72, SE-100 44, Stockholm, Sweden."}]},{"given":"Mahmood","family":"Rahmani","sequence":"additional","affiliation":[{"name":"Department of Transport Science, Division of Traffic and Logistics, KTH Royal Institute of Technology, Teknikringen 72, SE-100 44, Stockholm, Sweden."}]},{"given":"He","family":"Huang","sequence":"additional","affiliation":[{"name":"Singapore\u2013Massachusetts Institute of Technology Alliance for Research and Technology, Future Urban Mobility, 1 Create Way, No. 09-02 Create Tower, Singapore 138602."}]},{"given":"Long","family":"Ma","sequence":"additional","affiliation":[{"name":"Singapore\u2013Massachusetts Institute of Technology Alliance for Research and Techno logy, Future Urban Mobility, No. 04\u201336, 54 Choa Chu Kang North 7, Singapore 689529."}]},{"given":"Francisco","family":"Pereira","sequence":"additional","affiliation":[{"name":"Singapore\u2013Massachusetts Institute of Technology Alliance for Research and Technology, Future Urban Mobility, 1 Create Way, No. 09-02 Create Tower, Singapore 138602."}]},{"given":"Moshe","family":"Ben-Akiva","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, 77 Massachusetts Avenue, 1\u2013181, Cambridge, MA 02134."}]}],"member":"179","published-online":{"date-parts":[[2014,1,1]]},"reference":[{"key":"bibr1-2466-09","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4614-6243-9_8"},{"key":"bibr2-2466-09","doi-asserted-by":"publisher","DOI":"10.3141\/1537-06"},{"key":"bibr3-2466-09","doi-asserted-by":"publisher","DOI":"10.1080\/0144164042000196080"},{"key":"bibr4-2466-09","doi-asserted-by":"publisher","DOI":"10.1049\/ip-its:20055012"},{"key":"bibr5-2466-09","doi-asserted-by":"publisher","DOI":"10.1080\/15472450701293882"},{"key":"bibr6-2466-09","doi-asserted-by":"publisher","DOI":"10.1016\/S0968-090X(99)00014-5"},{"key":"bibr7-2466-09","doi-asserted-by":"publisher","DOI":"10.1016\/S0191-2615(02)00063-2"},{"key":"bibr8-2466-09","doi-asserted-by":"publisher","DOI":"10.1023\/B:PORT.0000025396.32909.dc"},{"key":"bibr9-2466-09","doi-asserted-by":"publisher","DOI":"10.1007\/s11067-005-6660-9"},{"key":"bibr10-2466-09","doi-asserted-by":"publisher","DOI":"10.3141\/1926-22"},{"key":"bibr11-2466-09","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2006.880634"},{"key":"bibr12-2466-09","doi-asserted-by":"publisher","DOI":"10.3141\/2156-04"},{"key":"bibr13-2466-09","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2011.08.009"},{"key":"bibr14-2466-09","unstructured":"TianH., GaoS., FisherD. 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