{"id":9211,"date":"2026-01-15T17:11:07","date_gmt":"2026-01-15T08:11:07","guid":{"rendered":"https:\/\/www.waseda.jp\/fsss\/gsss\/?p=9211"},"modified":"2026-04-24T17:14:24","modified_gmt":"2026-04-24T08:14:24","slug":"coursework-in-the-streets-walking-around-and-getting-a-sense-of-cultural-gaps-yoichi-sato-2-2-3-2-2-2-3-3-2-3-2-3-2-2-2-3-4","status":"publish","type":"post","link":"https:\/\/www.waseda.jp\/fsss\/gsss\/news-en\/2026\/01\/15\/9211\/","title":{"rendered":"Evaluating Autonomous Truck Adoption: An Elasticity-Based Model of Demand, Modal Shift, and Emissions &#8211; Tomoo Noguchi"},"content":{"rendered":"<dl>\n<dt><strong>Evaluating Autonomous Truck Adoption: An Elasticity-Based Model of Demand, Modal Shift, and Emissions &#8211; Tomoo Noguchi<\/strong><\/dt>\n<dt><code><\/code><\/dt>\n<dt><\/dt>\n<dt><\/dt>\n<dt><\/dt>\n<dt><\/dt>\n<dt><\/dt>\n<dt><\/dt>\n<dt><\/dt>\n<dt><span style=\"text-decoration: underline;\"><em>Abstract<\/em><\/span><\/dt>\n<dt><\/dt>\n<dt><\/dt>\n<dt><\/dt>\n<dt>This study develops a compact elasticity-based framework for assessing how autonomous truck adoption influences corridor-level performance, freight demand, modal competition, and CO<sub>2<\/sub>\u00a0emissions in multimodal freight Intelligent Transportation Systems. The model specifies the constant elastic (log-linear) responses of traffic performance and generalized costs to adoption, enabling the closed-form characterization of system-level rebound and road\u2013rail reallocation effects. The analytical results show that an internal adoption threshold\u00a0<span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" tabindex=\"0\" role=\"presentation\" data-mathml=\"&lt;math xmlns=&quot;http:\/\/www.w3.org\/1998\/Math\/MathML&quot; display=&quot;inline&quot;&gt;&lt;semantics&gt;&lt;msup&gt;&lt;mi&gt;P&lt;\/mi&gt;&lt;mo&gt;*&lt;\/mo&gt;&lt;\/msup&gt;&lt;\/semantics&gt;&lt;\/math&gt;\"><span id=\"MathJax-Span-1\" class=\"math\"><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"semantics\"><span id=\"MathJax-Span-4\" class=\"msup\"><span id=\"MathJax-Span-5\" class=\"mi\">\ud835\udc43<\/span><span id=\"MathJax-Span-6\" class=\"mo\">\u2217<\/span><\/span><\/span><\/span><\/span><\/span>\u00a0emerges, defined by\u00a0<span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" tabindex=\"0\" role=\"presentation\" data-mathml=\"&lt;math xmlns=&quot;http:\/\/www.w3.org\/1998\/Math\/MathML&quot; display=&quot;inline&quot;&gt;&lt;semantics&gt;&lt;mrow&gt;&lt;mi&gt;d&lt;\/mi&gt;&lt;mover accent=&quot;true&quot;&gt;&lt;mi&gt;E&lt;\/mi&gt;&lt;mo stretchy=&quot;false&quot;&gt;^&lt;\/mo&gt;&lt;\/mover&gt;&lt;mo&gt;\/&lt;\/mo&gt;&lt;mi&gt;d&lt;\/mi&gt;&lt;mi&gt;P&lt;\/mi&gt;&lt;mo&gt;=&lt;\/mo&gt;&lt;mn&gt;0&lt;\/mn&gt;&lt;\/mrow&gt;&lt;\/semantics&gt;&lt;\/math&gt;\"><span id=\"MathJax-Span-7\" class=\"math\"><span id=\"MathJax-Span-8\" class=\"mrow\"><span id=\"MathJax-Span-9\" class=\"semantics\"><span id=\"MathJax-Span-10\" class=\"mrow\"><span id=\"MathJax-Span-11\" class=\"mi\">\ud835\udc51<\/span><span id=\"MathJax-Span-12\" class=\"mover\"><span id=\"MathJax-Span-13\" class=\"mi\">\ud835\udc38<\/span><span id=\"MathJax-Span-14\" class=\"mo\">\u0302\u00a0<\/span><\/span><span id=\"MathJax-Span-15\" class=\"mo\">\/<\/span><span id=\"MathJax-Span-16\" class=\"mi\">\ud835\udc51<\/span><span id=\"MathJax-Span-17\" class=\"mi\">\ud835\udc43<\/span><span id=\"MathJax-Span-18\" class=\"mo\">=<\/span><span id=\"MathJax-Span-19\" class=\"mn\">0<\/span><\/span><\/span><\/span><\/span><\/span>, which separates a beneficial regime (efficiency gains dominate) from an adverse regime (rebound and modal shift dominate). Comparative statics indicate that\u00a0<span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" tabindex=\"0\" role=\"presentation\" data-mathml=\"&lt;math xmlns=&quot;http:\/\/www.w3.org\/1998\/Math\/MathML&quot; display=&quot;inline&quot;&gt;&lt;semantics&gt;&lt;msup&gt;&lt;mi&gt;P&lt;\/mi&gt;&lt;mo&gt;*&lt;\/mo&gt;&lt;\/msup&gt;&lt;\/semantics&gt;&lt;\/math&gt;\"><span id=\"MathJax-Span-20\" class=\"math\"><span id=\"MathJax-Span-21\" class=\"mrow\"><span id=\"MathJax-Span-22\" class=\"semantics\"><span id=\"MathJax-Span-23\" class=\"msup\"><span id=\"MathJax-Span-24\" class=\"mi\">\ud835\udc43<\/span><span id=\"MathJax-Span-25\" class=\"mo\">\u2217<\/span><\/span><\/span><\/span><\/span><\/span>\u00a0decreases with stronger ITS capability\u00a0<span class=\"html-italic\">A<\/span>\u00a0and increases with rebound intensity\u00a0<span class=\"html-italic\">R<\/span>\u00a0and the road\u2013rail carbon intensity contrast\u00a0<span class=\"html-italic\">K<\/span>. Numerical experiments across representative corridor contexts illustrate induced demand effects exceeding 25% under high-rebound conditions and threshold ranges around\u00a0<span id=\"MathJax-Element-4-Frame\" class=\"MathJax\" tabindex=\"0\" role=\"presentation\" data-mathml=\"&lt;math xmlns=&quot;http:\/\/www.w3.org\/1998\/Math\/MathML&quot; display=&quot;inline&quot;&gt;&lt;semantics&gt;&lt;mrow&gt;&lt;msup&gt;&lt;mi&gt;P&lt;\/mi&gt;&lt;mo&gt;*&lt;\/mo&gt;&lt;\/msup&gt;&lt;mo&gt;&amp;#x2248;&lt;\/mo&gt;&lt;mn&gt;0.3&lt;\/mn&gt;&lt;\/mrow&gt;&lt;\/semantics&gt;&lt;\/math&gt;\"><span id=\"MathJax-Span-26\" class=\"math\"><span id=\"MathJax-Span-27\" class=\"mrow\"><span id=\"MathJax-Span-28\" class=\"semantics\"><span id=\"MathJax-Span-29\" class=\"mrow\"><span id=\"MathJax-Span-30\" class=\"msup\"><span id=\"MathJax-Span-31\" class=\"mi\">\ud835\udc43<\/span><span id=\"MathJax-Span-32\" class=\"mo\">\u2217<\/span><\/span><span id=\"MathJax-Span-33\" class=\"mo\">\u2248<\/span><span id=\"MathJax-Span-34\" class=\"mn\">0.3<\/span><\/span><\/span><\/span><\/span><\/span>\u20130.4 for plausible parameters. The results provide interpretable guidance for coordinating autonomous truck deployment with intermodal logistics design and decarbonization strategies.<\/dt>\n<dt><\/dt>\n<dt><\/dt>\n<dt><\/dt>\n<\/dl>\n<p><a href=\"https:\/\/www.mdpi.com\/2673-7590\/6\/1\/20\">Evaluating Autonomous Truck Adoption: An Elasticity-Based Model of Demand, Modal Shift, and Emissions<\/a><\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Evaluating Autonomous Truck Adoption: An Elasticity-Based Model of Demand, Modal Shift, and Emissions &#8211;  [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[22],"tags":[99],"class_list":["post-9211","post","type-post","status-publish","format-standard","hentry","category-news-en","tag-research-en"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.waseda.jp\/fsss\/gsss\/wp-json\/wp\/v2\/posts\/9211","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.waseda.jp\/fsss\/gsss\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.waseda.jp\/fsss\/gsss\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.waseda.jp\/fsss\/gsss\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.waseda.jp\/fsss\/gsss\/wp-json\/wp\/v2\/comments?post=9211"}],"version-history":[{"count":1,"href":"https:\/\/www.waseda.jp\/fsss\/gsss\/wp-json\/wp\/v2\/posts\/9211\/revisions"}],"predecessor-version":[{"id":9213,"href":"https:\/\/www.waseda.jp\/fsss\/gsss\/wp-json\/wp\/v2\/posts\/9211\/revisions\/9213"}],"wp:attachment":[{"href":"https:\/\/www.waseda.jp\/fsss\/gsss\/wp-json\/wp\/v2\/media?parent=9211"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.waseda.jp\/fsss\/gsss\/wp-json\/wp\/v2\/categories?post=9211"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.waseda.jp\/fsss\/gsss\/wp-json\/wp\/v2\/tags?post=9211"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}