Cognitive Cost in Route Choice with Real-Time Information: An Exploratory Analysis
Real-time traffic information is increasingly available to support route choice decisions by reducing the travel time uncertainty. However it is likely that a traveler cannot assess all available information on all alternative routes due to time constraints and limited cognitive capacity. This paper...
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Elsevier
2014
|
| Online Access: | http://hdl.handle.net/1721.1/92338 |
| _version_ | 1826194522440204288 |
|---|---|
| author | Gao, Song Frejinger, Emma Ben-Akiva, Moshe E. |
| author2 | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Gao, Song Frejinger, Emma Ben-Akiva, Moshe E. |
| author_sort | Gao, Song |
| collection | MIT |
| description | Real-time traffic information is increasingly available to support route choice decisions by reducing the travel time uncertainty. However it is likely that a traveler cannot assess all available information on all alternative routes due to time constraints and limited cognitive capacity. This paper presents a model that is consistent with a general network topology and can potentially be estimated based on revealed preference data. It explicitly takes into account the information acquisition and the subsequent path choice. The decision to acquire information is assumed to be based on the cognitive cost involved in the search and the expected benefit defined as the expected increase in utility after the search. A latent class model is proposed, where the decision to search or not to search and the depth of the search are latent and only the final path choices are observed. A synthetic data set is used for the purpose of validation and ease of illustration. The data are generated from the postulated cognitive-cost model, and estimation results show that the true values of the parameters can be recovered with enough variability in the data. Two other models with simplifying assumptions of no information and full information are also estimated with the same set of data with significantly biased path choice utility parameters. Prediction results show that a smaller cognitive cost encourages information search on risky and fast routes and thus higher shares on those routes. As a result, the expected average travel time decreases and the variability increases. The no-information and full-information models are extreme cases of the more general cognitive-cost model in some cases, but not generally so, and thus the increasing ease of information acquisition does not necessarily warrant a full-information model. |
| first_indexed | 2024-09-23T09:57:24Z |
| format | Article |
| id | mit-1721.1/92338 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T09:57:24Z |
| publishDate | 2014 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | mit-1721.1/923382022-09-26T14:47:57Z Cognitive Cost in Route Choice with Real-Time Information: An Exploratory Analysis Gao, Song Frejinger, Emma Ben-Akiva, Moshe E. Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Ben-Akiva, Moshe E. Real-time traffic information is increasingly available to support route choice decisions by reducing the travel time uncertainty. However it is likely that a traveler cannot assess all available information on all alternative routes due to time constraints and limited cognitive capacity. This paper presents a model that is consistent with a general network topology and can potentially be estimated based on revealed preference data. It explicitly takes into account the information acquisition and the subsequent path choice. The decision to acquire information is assumed to be based on the cognitive cost involved in the search and the expected benefit defined as the expected increase in utility after the search. A latent class model is proposed, where the decision to search or not to search and the depth of the search are latent and only the final path choices are observed. A synthetic data set is used for the purpose of validation and ease of illustration. The data are generated from the postulated cognitive-cost model, and estimation results show that the true values of the parameters can be recovered with enough variability in the data. Two other models with simplifying assumptions of no information and full information are also estimated with the same set of data with significantly biased path choice utility parameters. Prediction results show that a smaller cognitive cost encourages information search on risky and fast routes and thus higher shares on those routes. As a result, the expected average travel time decreases and the variability increases. The no-information and full-information models are extreme cases of the more general cognitive-cost model in some cases, but not generally so, and thus the increasing ease of information acquisition does not necessarily warrant a full-information model. 2014-12-16T19:04:32Z 2014-12-16T19:04:32Z 2011-05 Article http://purl.org/eprint/type/JournalArticle 18770428 http://hdl.handle.net/1721.1/92338 Gao, Song, Emma Frejinger, and Moshe Ben-Akiva. “Cognitive Cost in Route Choice with Real-Time Information: An Exploratory Analysis.” Procedia - Social and Behavioral Sciences 17 (2011): 136–149. en_US http://dx.doi.org/10.1016/j.sbspro.2011.04.511 Procedia - Social and Behavioral Sciences Creative Commons Attribution http://creativecommons.org/licenses/by-nc-nd/3.0/ application/pdf Elsevier Elsevier |
| spellingShingle | Gao, Song Frejinger, Emma Ben-Akiva, Moshe E. Cognitive Cost in Route Choice with Real-Time Information: An Exploratory Analysis |
| title | Cognitive Cost in Route Choice with Real-Time Information: An Exploratory Analysis |
| title_full | Cognitive Cost in Route Choice with Real-Time Information: An Exploratory Analysis |
| title_fullStr | Cognitive Cost in Route Choice with Real-Time Information: An Exploratory Analysis |
| title_full_unstemmed | Cognitive Cost in Route Choice with Real-Time Information: An Exploratory Analysis |
| title_short | Cognitive Cost in Route Choice with Real-Time Information: An Exploratory Analysis |
| title_sort | cognitive cost in route choice with real time information an exploratory analysis |
| url | http://hdl.handle.net/1721.1/92338 |
| work_keys_str_mv | AT gaosong cognitivecostinroutechoicewithrealtimeinformationanexploratoryanalysis AT frejingeremma cognitivecostinroutechoicewithrealtimeinformationanexploratoryanalysis AT benakivamoshee cognitivecostinroutechoicewithrealtimeinformationanexploratoryanalysis |