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		<title>Li et al 2018m - Revision history</title>
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		<updated>2026-05-06T11:34:13Z</updated>
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		<title>Scipediacontent: Scipediacontent moved page Draft Content 442898387 to Li et al 2018m</title>
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				<updated>2021-02-15T09:50:58Z</updated>
		
		<summary type="html">&lt;p&gt;Scipediacontent moved page &lt;a href=&quot;/public/Draft_Content_442898387&quot; class=&quot;mw-redirect&quot; title=&quot;Draft Content 442898387&quot;&gt;Draft Content 442898387&lt;/a&gt; to &lt;a href=&quot;/public/Li_et_al_2018m&quot; title=&quot;Li et al 2018m&quot;&gt;Li et al 2018m&lt;/a&gt;&lt;/p&gt;
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				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;Revision as of 09:50, 15 February 2021&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan='2' style='text-align: center;' lang='en'&gt;&lt;div class=&quot;mw-diff-empty&quot;&gt;(No difference)&lt;/div&gt;
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		<author><name>Scipediacontent</name></author>	</entry>

	<entry>
		<id>https://www.scipedia.com/wd/index.php?title=Li_et_al_2018m&amp;diff=214195&amp;oldid=prev</id>
		<title>Scipediacontent: Created page with &quot; == Abstract ==  Route choice is one of the most critical passenger behaviors in public transit research. The utility maximization theory is generally used to model passengers...&quot;</title>
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				<updated>2021-02-15T09:50:53Z</updated>
		
		<summary type="html">&lt;p&gt;Created page with &amp;quot; == Abstract ==  Route choice is one of the most critical passenger behaviors in public transit research. The utility maximization theory is generally used to model passengers...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;&lt;br /&gt;
== Abstract ==&lt;br /&gt;
&lt;br /&gt;
Route choice is one of the most critical passenger behaviors in public transit research. The utility maximization theory is generally used to model passengers’ route choice behavior in a public transit network in previous research. However, researchers have found that passenger behavior is far more complicated than a single utility maximization assumption. Some passengers tend to maximize their utility while others would minimize their regrets. In this paper, a schedule-based transit assignment model based on the hybrid of utility maximization and regret minimization is proposed to study the passenger route choice behavior in an urban rail transit network. Firstly, based on the smart card data, the space-time expanded network in an urban rail transit was constructed. Then, it adapts the utility maximization (RUM) and the regret minimization theory (RRM) to analyze and model the passenger route choice behavior independently. The utility values and the regret values are calculated with the utility and the regret functions. A transit assignment model is established based on a hybrid of the random utility maximization and the random regret minimization (RURM) with two kinds of hybrid rules, namely, attribute level hybrid and decision level hybrid. The models are solved by the method of successive algorithm. Finally, the hybrid assignment models are applied to Beijing urban rail transit network for validation. The result shows that RRM and RUM make no significant difference for OD pairs with only two alternative routes. For those with more than two alternative routes, the performance of RRM and RUM is different. RRM is slightly better than RUM in some of the OD pairs, while for the other OD pairs, the results are opposite. Moreover, it shows that the crowd would only influence the regret value of OD pair with more commuters. We conclude that compared with RUM and RRM, the hybrid model RURM is more general.&lt;br /&gt;
&lt;br /&gt;
Document type: Article&lt;br /&gt;
&lt;br /&gt;
== Full document ==&lt;br /&gt;
&amp;lt;pdf&amp;gt;Media:Draft_Content_442898387-beopen809-4914-document.pdf&amp;lt;/pdf&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Original document ==&lt;br /&gt;
&lt;br /&gt;
The different versions of the original document can be found in:&lt;br /&gt;
&lt;br /&gt;
* [http://downloads.hindawi.com/journals/jat/2018/9789316.pdf http://downloads.hindawi.com/journals/jat/2018/9789316.pdf] under the license https://creativecommons.org/licenses/by&lt;br /&gt;
&lt;br /&gt;
* [http://dx.doi.org/10.1155/2018/9789316 http://dx.doi.org/10.1155/2018/9789316] under the license cc-by&lt;br /&gt;
&lt;br /&gt;
* [http://downloads.hindawi.com/journals/jat/2018/9789316.pdf http://downloads.hindawi.com/journals/jat/2018/9789316.pdf],&lt;br /&gt;
: [http://downloads.hindawi.com/journals/jat/2018/9789316.xml http://downloads.hindawi.com/journals/jat/2018/9789316.xml],&lt;br /&gt;
: [http://dx.doi.org/10.1155/2018/9789316 http://dx.doi.org/10.1155/2018/9789316] under the license http://creativecommons.org/licenses/by/4.0&lt;br /&gt;
&lt;br /&gt;
* [http://dx.doi.org/10.1155/2018/9789316 http://dx.doi.org/10.1155/2018/9789316],&lt;br /&gt;
: [https://doaj.org/toc/0197-6729 https://doaj.org/toc/0197-6729],&lt;br /&gt;
: [https://doaj.org/toc/2042-3195 https://doaj.org/toc/2042-3195] under the license http://creativecommons.org/licenses/by/4.0/&lt;br /&gt;
&lt;br /&gt;
* [https://www.hindawi.com/journals/jat/2018/9789316 https://www.hindawi.com/journals/jat/2018/9789316],&lt;br /&gt;
: [http://downloads.hindawi.com/journals/jat/2018/9789316.pdf http://downloads.hindawi.com/journals/jat/2018/9789316.pdf],&lt;br /&gt;
: [https://academic.microsoft.com/#/detail/2904533698 https://academic.microsoft.com/#/detail/2904533698]&lt;/div&gt;</summary>
		<author><name>Scipediacontent</name></author>	</entry>

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