{"id":29636,"date":"2026-03-25T08:00:00","date_gmt":"2026-03-25T07:00:00","guid":{"rendered":"https:\/\/blog.ptvgroup.com\/?p=29636"},"modified":"2026-02-18T14:07:00","modified_gmt":"2026-02-18T13:07:00","slug":"cargo-bike-traffic-simulation-ptv-vissim","status":"publish","type":"post","link":"https:\/\/blog.ptvgroup.com\/en\/modeling-planning\/cargo-bike-traffic-simulation-ptv-vissim\/","title":{"rendered":"Cargo bike traffic simulation for cycling infrastructure"},"content":{"rendered":"\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<div class=\"wp-block-yoast-seo-table-of-contents yoast-table-of-contents\"><h2>Table of contents<\/h2><ul><li><a href=\"#h-cargo-bike-traffic-simulation-behavior-amp-design\" data-level=\"2\">Cargo bike traffic simulation: behavior &amp; design<\/a><\/li><li><a href=\"#h-tfl-s-cargo-bike-traffic-simulation-in-ptv-vissim\" data-level=\"2\">TfL\u2019s cargo bike traffic simulation in PTV Vissim<\/a><\/li><li><a href=\"#h-from-vehicle-traits-to-network-effects\" data-level=\"2\">From vehicle traits to network effects<\/a><ul><li><a href=\"#h-micro-level-width-amp-acceleration\" data-level=\"3\">Micro level: Width &amp; acceleration<\/a><\/li><li><a href=\"#h-meso-level-infrastructure-limits\" data-level=\"3\">Meso level: Infrastructure limits<\/a><\/li><li><a href=\"#h-macro-level-network-outcomes\" data-level=\"3\">Macro level: Network outcomes<\/a><\/li><\/ul><\/li><li><a href=\"#h-why-ptv-vissim-for-cycling-network-planning\" data-level=\"2\">Why PTV Vissim for cycling\u2011network planning<\/a><\/li><li><a href=\"#h-key-lessons-for-mobility-planners\" data-level=\"2\">Key lessons for mobility planners<\/a><\/li><\/ul><\/div>\n\n\n\n<p>Cargo bike traffic simulation is now <a href=\"https:\/\/blog.ptvgroup.com\/en\/trend-topics\/bike-friendly-cities-traffic-simulation\/\" target=\"_blank\" rel=\"noreferrer noopener\">essential<\/a> as cargo bikes are becoming increasingly popular in cities. Using <a href=\"https:\/\/blog.ptvgroup.com\/en\/technologyplus\/realistic-traffic-simulation-driving-behavior-is-key\/\" target=\"_blank\" rel=\"noreferrer noopener\">PTV Vissim<\/a>, Transport for London modelled the Parliament Square area to test network effects when a share of light\u2011goods vehicles shift to cargo bikes.<\/p>\n\n\n\n<p>The Vissim model captured width, acceleration, lateral behavior and overtaking, and assessed interactions with lane geometry, segregation and junctions. Results show clear thresholds: narrow lanes restrict passing and amplify cyclist delay, while segregated facilities keep general traffic and buses stable; cars and taxis can benefit as vans decline.<\/p>\n\n\n\n<p>Led by TfL\u2019s <a href=\"https:\/\/www.linkedin.com\/in\/birendra-shrestha-44aa49a2\/\" type=\"link\" id=\"https:\/\/www.linkedin.com\/in\/birendra-shrestha-44aa49a2\/\" target=\"_blank\" rel=\"noreferrer noopener\">Birendra Shrestha<\/a> and <a href=\"https:\/\/www.linkedin.com\/in\/evangelos-kotsialos-46a24a74\/\" type=\"link\" id=\"https:\/\/www.linkedin.com\/in\/evangelos-kotsialos-46a24a74\/\" target=\"_blank\" rel=\"noreferrer noopener\">Evangelos Kotsialos<\/a>, this work offers practical guidance: design for overtaking with effective widths, prioritise segregation on busy corridors, and use <a href=\"https:\/\/blog.ptvgroup.com\/en\/modeling-planning\/scenario-management-one-of-the-key-features-for-traffic-simulation-2\/\" target=\"_blank\" rel=\"noreferrer noopener\">scenario testing<\/a> to de\u2011risk delivery.<\/p>\n\n\n\n<p>[This article is based on the webinar <a href=\"https:\/\/www.youtube.com\/watch?v=Hx6FkbOn0eU&amp;t=755s\" target=\"_blank\" rel=\"noreferrer noopener\"><em>PTV Vissim | Modelling Cargo Bikes in London\u2019s Road Network<\/em><\/a>, part of PTV\u2019s Spotlight Talks series.]<\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;69e85a991c31f&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"69e85a991c31f\" class=\"wp-block-image size-full is-resized wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"500\" height=\"386\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo2-rotated.jpg\" alt=\"Cargo bike traffic simulation - shift toward cargo bikes and network impacts (TfL, PTV Vissim)\" class=\"wp-image-29628\" style=\"width:500px;height:auto\" srcset=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo2-rotated.jpg 500w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo2-466x360.jpg 466w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo2-259x200.jpg 259w\" sizes=\"auto, (max-width: 500px) 100vw, 500px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">Shift toward cargo bikes and network impacts (Source: TfL)<\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-cargo-bike-traffic-simulation-behavior-amp-design\"><strong>Cargo bike traffic simulation: behavior &amp; design<\/strong><\/h2>\n\n\n\n<p>Cargo bikes vary significantly in design: front loaders, longtails, trikes and emerging four\u2011wheel cargo platforms. These designs differ not only in geometry but also in maneuverability, rider behavior and acceleration characteristics.<\/p>\n\n\n\n<p>For planners, this creates real uncertainty. Standard cycling models are not sufficient, because:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Additional width <\/strong>affects overtaking and lateral positioning<\/li>\n\n\n\n<li><strong>Slower acceleration<\/strong> alters queue formation at junctions<\/li>\n\n\n\n<li><strong>Larger turning radii<\/strong> affect behavior at narrow corners or shared paths<\/li>\n\n\n\n<li><strong>New <\/strong><a href=\"https:\/\/blog.ptvgroup.com\/en\/trend-topics\/e-bikes-reshaping-urban-mobility\/\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>e\u2011assist models<\/strong><\/a> change speed stability under loads<\/li>\n\n\n\n<li><strong>Emerging vehicle types<\/strong> lack robust field data<\/li>\n<\/ul>\n\n\n\n<p>Without simulation, assumptions risk oversimplifying how cargo bikes behave &#8211; especially in dense, high\u2011demand corridors where every meter of lane width affects flow. This is where cargo bike traffic simulation with PTV Vissim provides the necessary behavioral realism to explore overtaking, lateral movements, and queue formation in congested conditions.<\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;69e85a991cdda&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"69e85a991cdda\" class=\"wp-block-image size-full wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"500\" height=\"386\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo3-rotated.jpg\" alt=\"\" class=\"wp-image-29626\" srcset=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo3-rotated.jpg 500w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo3-466x360.jpg 466w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo3-259x200.jpg 259w\" sizes=\"auto, (max-width: 500px) 100vw, 500px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">Study scope and modelling limitations (Source: TfL)<\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-tfl-s-cargo-bike-traffic-simulation-in-ptv-vissim\"><strong>TfL\u2019s cargo bike traffic simulation in PTV Vissim<\/strong><\/h2>\n\n\n\n<p>Transport for London undertook a detailed Vissim <a href=\"https:\/\/blog.ptvgroup.com\/en\/user-insights\/how-microsimulation-reduces-risk-in-complex-urban-projects\/\" target=\"_blank\" rel=\"noreferrer noopener\">microsimulation<\/a> study in the Parliament Square area &#8211; one of London\u2019s busiest and most complex multimodal nodes. To evaluate cargo bike traffic simulation outcomes at this complex multimodal node, TfL modelled Parliament Square with mode\u2011shift scenarios replacing 5\u201330% of LGVs.<\/p>\n\n\n\n<p>TfL\u2019s team derived cargo\u2011bike parameters from roughly 200 on\u2011street observations, covering attributes such as: length and width, desired speed distribution, acceleration and braking behavior, lateral movement tendencies, and minimum overtaking distances.<\/p>\n\n\n\n<p>To maintain reliability, TfL limited its scope to two\u2011wheel cargo bikes, since field data for four\u2011wheel cargo bikes was insufficient. They also adopted clear modelling assumptions:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Cargo bikes use cycle infrastructure wherever available<\/li>\n\n\n\n<li>No overtaking into opposing\u2011direction lanes<\/li>\n\n\n\n<li>Van routing patterns were unchanged (micro\u2011hub effects not modelled)<\/li>\n\n\n\n<li>Cargo\u2011bike flow and travel\u2011time validation was not possible due to lacking field data<\/li>\n<\/ul>\n\n\n\n<p>Scope note: results apply to <strong>two\u2011wheel cargo bikes<\/strong>; four\u2011wheel cargo platforms were out of scope due to limited field data.<\/p>\n\n\n\n<p>These limitations demonstrate <em>why<\/em> simulation is required: the rapid pace of cargo\u2011bike innovation outstrips available real\u2011world evidence.<\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;69e85a991d82f&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"69e85a991d82f\" class=\"wp-block-image size-full wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"500\" height=\"386\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo7-rotated.jpg\" alt=\"\" class=\"wp-image-29622\" srcset=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo7-rotated.jpg 500w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo7-466x360.jpg 466w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo7-259x200.jpg 259w\" sizes=\"auto, (max-width: 500px) 100vw, 500px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">Mode shift scenarios and cargo bike volumes (Source: TfL)<\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-from-vehicle-traits-to-network-effects\"><strong>From vehicle traits to network effects<\/strong><\/h2>\n\n\n\n<p>A central insight from the study is that the interaction between <strong>vehicle characteristics<\/strong> and <strong>infrastructure geometry<\/strong> creates network impacts that are larger than expected.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-micro-level-width-amp-acceleration\"><strong>Micro level: Width &amp; acceleration<\/strong><\/h3>\n\n\n\n<p>Two characteristics stood out:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Cargo bikes accelerate more slowly than standard bicycles<\/li>\n\n\n\n<li>Their greater width reduces maneuvering space for overtaking<\/li>\n<\/ul>\n\n\n\n<p>In combination, these traits create queuing effects in narrow cycling lanes because faster cyclists cannot pass as freely. The slower take\u2011off increases delays at <a href=\"https:\/\/blog.ptvgroup.com\/en\/user-insights\/pedestrian-crossing-planning-benchmarking-signalised-junctions\/\" target=\"_blank\" rel=\"noreferrer noopener\">junctions<\/a>, while the width restricts lateral movement.<\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;69e85a991e24f&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"69e85a991e24f\" class=\"wp-block-image size-full wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"500\" height=\"386\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo6-rotated.jpg\" alt=\"\" class=\"wp-image-29624\" style=\"object-fit:cover\" srcset=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo6-rotated.jpg 500w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo6-466x360.jpg 466w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo6-259x200.jpg 259w\" sizes=\"auto, (max-width: 500px) 100vw, 500px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">Cargo bike speed, size and behavior parameters (Source: TfL)<\/figcaption><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-meso-level-infrastructure-limits\"><strong>Meso level: Infrastructure limits<\/strong><\/h3>\n\n\n\n<p>Vissim simulations revealed clear <a href=\"https:\/\/blog.ptvgroup.com\/en\/modeling-planning\/bordeaux-metropoles-new-approach-to-bicycle-traffic-modeling\/\" target=\"_blank\" rel=\"noreferrer noopener\">infrastructure thresholds<\/a>:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/blog.ptvgroup.com\/en\/trend-topics\/bike-friendly-cities-traffic-simulation\/\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>Cycle lanes<\/strong><\/a><strong> under 1.5 m<\/strong> experienced the highest increases in delay &#8211; up to ~60% in some scenarios.<\/li>\n\n\n\n<li>Lanes <strong>wider than 2 m<\/strong> showed significantly more stable performance due to overtaking opportunities.<\/li>\n\n\n\n<li><a href=\"https:\/\/blog.ptvgroup.com\/en\/trend-topics\/driving-toward-safer-smarter-cities-how-vision-zero-is-shaping-the-future-of-urban-mobility\/\" target=\"_blank\" rel=\"noreferrer noopener\">Segregated facilities<\/a> reduced conflicts between cargo bikes and general traffic.<\/li>\n\n\n\n<li>High\u2011demand corridors amplified delays where lane width was limited.<\/li>\n<\/ul>\n\n\n\n<p>This reinforces a key cycling\u2011infrastructure insight: small variations in effective width can dramatically change performance under rising demand.<\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;69e85a991ec47&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"69e85a991ec47\" class=\"wp-block-image size-full wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"500\" height=\"386\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo12-rotated.jpg\" alt=\"Cargo bike traffic simulation - lane width thresholds and delay sensitivity\" class=\"wp-image-29620\" srcset=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo12-rotated.jpg 500w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo12-466x360.jpg 466w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo12-259x200.jpg 259w\" sizes=\"auto, (max-width: 500px) 100vw, 500px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">Lane width sensitivity; narrow lanes amplify delays (Source: TfL)<\/figcaption><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-macro-level-network-outcomes\"><strong>Macro level: Network outcomes<\/strong><\/h3>\n\n\n\n<p>The most notable outcome was that cargo\u2011bike adoption produced mildly surprising effects:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/blog.ptvgroup.com\/en\/user-insights\/vissim-microsimulation-helps-liverpool-cut-no%E2%82%82-vehicle-emissions\/\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>General traffic<\/strong><\/a><strong> and buses <\/strong>remained stable.<\/li>\n\n\n\n<li><strong>Cars and taxis <\/strong>experienced slight improvements thanks to fewer vans.<\/li>\n\n\n\n<li><strong>Cyclists <\/strong>experienced increased delays, especially on narrow or high\u2011demand links.<\/li>\n\n\n\n<li><strong>Segregated infrastructure<\/strong> enabled positive system\u2011level results by keeping cargo bikes out of motor\u2011traffic lanes.<\/li>\n<\/ul>\n\n\n\n<p>This demonstrates the value of multimodal traffic simulation: results are not always intuitive, and infrastructure design plays a decisive role.<\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;69e85a991f510&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"69e85a991f510\" class=\"wp-block-image size-full wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"500\" height=\"386\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/NEWCargo8-rotated.jpg\" alt=\"Cargo bike traffic simulation - network delay shifts across modes\" class=\"wp-image-29632\" srcset=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/NEWCargo8-rotated.jpg 500w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/NEWCargo8-466x360.jpg 466w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/NEWCargo8-259x200.jpg 259w\" sizes=\"auto, (max-width: 500px) 100vw, 500px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">Network delay shifts across user groups (Source: TfL)<\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-why-ptv-vissim-for-cycling-network-planning\"><strong>Why PTV Vissim for cycling\u2011network planning<\/strong><\/h2>\n\n\n\n<p>PTV Vissim supports rigorous cargo bike modelling by enabling planners to:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Build <strong>custom cargo\u2011bike vehicle classes<\/strong> with realistic widths, acceleration curves and behavioral parameters.<\/li>\n\n\n\n<li>Capture <strong>lateral behavior<\/strong> and overtaking constraints in narrow cycle lanes.<\/li>\n\n\n\n<li>Simulate <strong>segregated cycling infrastructure<\/strong> and detailed junction layouts.<\/li>\n\n\n\n<li>Conduct <strong>scenario\u2011based experiments<\/strong> for mode shifts, replacement ratios and routing strategies.<\/li>\n\n\n\n<li>Analyze both <strong>local bottlenecks<\/strong> and <a href=\"https:\/\/blog.ptvgroup.com\/en\/modeling-planning\/at-the-highest-level-30-years-of-traffic-simulation-with-ptv-vissim\/\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>networkwide multimodal impacts<\/strong><\/a>.<\/li>\n<\/ul>\n\n\n\n<p>How to replicate: Start with custom vehicle classes and lateral behavior; then scenario\u2011test lane width and segregation alternatives in PTV Vissim.<\/p>\n\n\n\n<p>For cities anticipating large\u2011scale cargo\u2011bike adoption, these capabilities allow engineers to make evidence\u2011based decisions about lane widths, segregation strategies, junction design and cycling\u2011network capacity.<\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;69e85a991fd26&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"69e85a991fd26\" class=\"wp-block-image size-full wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"500\" height=\"386\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo15-rotated.jpg\" alt=\"\" class=\"wp-image-29618\" srcset=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo15-rotated.jpg 500w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo15-466x360.jpg 466w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Cargo15-259x200.jpg 259w\" sizes=\"auto, (max-width: 500px) 100vw, 500px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">Updated Vissim template and behaviour features (Source: TfL)<\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-key-lessons-for-mobility-planners\"><strong>Key lessons for mobility planners<\/strong><\/h2>\n\n\n\n<ol start=\"1\" class=\"wp-block-list\">\n<li>Cargo bikes can be simulated explicitly in traffic studies.<br><\/li>\n\n\n\n<li>Width and slower acceleration can affect cycling\u2011network performance.<br><\/li>\n\n\n\n<li>Narrow cycle lane widths could increase congestion under higher cargo\u2011bike volumes.<br><\/li>\n\n\n\n<li>Segregated cycle lanes improve outcomes across multiple modes.<br><\/li>\n\n\n\n<li>Scenario testing is essential because effects are not intuitive.<br><\/li>\n\n\n\n<li>Emerging vehicle types require adaptable, behaviorally rich simulation tools.<\/li>\n<\/ol>\n\n\n\n<p>For cities planning capacity upgrades and segregation strategies, cargo bike traffic simulation is the fastest way to de\u2011risk design choices before they reach the street.<\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;69e85a9920559&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"69e85a9920559\" class=\"wp-block-image size-full wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"500\" height=\"386\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/NEWCargo13-rotated.jpg\" alt=\"\" class=\"wp-image-29630\" srcset=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/NEWCargo13-rotated.jpg 500w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/NEWCargo13-466x360.jpg 466w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/NEWCargo13-259x200.jpg 259w\" sizes=\"auto, (max-width: 500px) 100vw, 500px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">Summary: impacts on cyclists and lane width effects (Source: TfL)<\/figcaption><\/figure>\n<\/div>\n\n\n\n<div class=\"wp-block-column cta-box is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<div class=\"wp-block-cover\"><img loading=\"lazy\" decoding=\"async\" width=\"1254\" height=\"836\" class=\"wp-block-cover__image-background wp-image-25406\" alt=\"\" src=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2024\/10\/iStock-1312502184.jpg\" data-object-fit=\"cover\" srcset=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2024\/10\/iStock-1312502184.jpg 1254w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2024\/10\/iStock-1312502184-540x360.jpg 540w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2024\/10\/iStock-1312502184-936x624.jpg 936w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2024\/10\/iStock-1312502184-768x512.jpg 768w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2024\/10\/iStock-1312502184-300x200.jpg 300w\" sizes=\"auto, (max-width: 1254px) 100vw, 1254px\" \/><span aria-hidden=\"true\" class=\"wp-block-cover__background has-background-dim-80 has-background-dim wp-block-cover__gradient-background has-background-gradient\" style=\"background:linear-gradient(135deg,rgb(66,104,249) 28%,rgb(41,224,133) 88%)\"><\/span><div class=\"wp-block-cover__inner-container is-layout-constrained wp-block-cover-is-layout-constrained\">\n<p class=\"has-text-align-center\" style=\"font-size:24px;font-style:normal;font-weight:700\">Urban mobility planning: simulation\u2011first strategies<\/p>\n\n\n\n<p class=\"has-text-align-center\">Our experts\u2019 free guide<br>for mobility and transportation planners<\/p>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-14c487f4 wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button is-style-fill\"><a class=\"wp-block-button__link has-white-background-color has-text-color has-background has-link-color has-text-align-center has-custom-font-size wp-element-button\" href=\"https:\/\/www.ptvgroup.com\/en\/application-areas\/urban-mobility\" style=\"border-radius:8px;color:#6482f6;font-size:14px;font-style:normal;font-weight:500\" target=\"_blank\" rel=\"noreferrer noopener\">Discover now<\/a><\/div>\n<\/div>\n<\/div><\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-cover\" style=\"min-height:300px;aspect-ratio:unset;\"><img loading=\"lazy\" decoding=\"async\" width=\"1254\" height=\"836\" class=\"wp-block-cover__image-background wp-image-25406\" alt=\"\" src=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2024\/10\/iStock-1312502184.jpg\" data-object-fit=\"cover\" srcset=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2024\/10\/iStock-1312502184.jpg 1254w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2024\/10\/iStock-1312502184-540x360.jpg 540w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2024\/10\/iStock-1312502184-936x624.jpg 936w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2024\/10\/iStock-1312502184-768x512.jpg 768w, https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2024\/10\/iStock-1312502184-300x200.jpg 300w\" sizes=\"auto, (max-width: 1254px) 100vw, 1254px\" \/><span aria-hidden=\"true\" class=\"wp-block-cover__background has-background-dim-80 has-background-dim wp-block-cover__gradient-background has-background-gradient\" style=\"background:linear-gradient(135deg,rgb(66,104,249) 28%,rgb(41,224,133) 88%)\"><\/span><div class=\"wp-block-cover__inner-container is-layout-constrained wp-block-cover-is-layout-constrained\">\n<p class=\"has-text-align-center\" style=\"font-size:24px;font-style:normal;font-weight:700\">Urban mobility planning: simulation\u2011first strategies<\/p>\n\n\n\n<p class=\"has-text-align-center\">Our experts\u2019 free guide for mobility and transportation planners<\/p>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-14c487f4 wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button 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[&#8230;]<\/p>\n<p class=\"m-0\"><a class=\"btn btn-outline-secondary btn-read-more\" href=\"https:\/\/blog.ptvgroup.com\/en\/modeling-planning\/cargo-bike-traffic-simulation-ptv-vissim\/\">Read More<\/a><\/p>\n","protected":false},"author":5,"featured_media":29634,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[8326,8322],"tags":[8407,8377,8371],"ppma_author":[8497],"class_list":["post-29636","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-modeling-planning","category-user-insights","tag-cycling","tag-traffic-simulation","tag-urban-mobility"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.0 (Yoast SEO v27.4) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Cargo bike traffic simulation with PTV Vissim | PTV Blog<\/title>\n<meta name=\"description\" content=\"Cargo bike traffic simulation with PTV Vissim shows how width, acceleration and lane design affect cycling performance in TfL\u2019s London study.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/blog.ptvgroup.com\/en\/modeling-planning\/cargo-bike-traffic-simulation-ptv-vissim\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Cargo bike traffic simulation for cycling infrastructure\" \/>\n<meta property=\"og:description\" content=\"Cargo bike traffic simulation with PTV Vissim shows how width, acceleration and lane design affect cycling performance in TfL\u2019s London study.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/blog.ptvgroup.com\/en\/modeling-planning\/cargo-bike-traffic-simulation-ptv-vissim\/\" \/>\n<meta property=\"og:site_name\" content=\"PTV Blog\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/PTVGroupGlobal\/\" \/>\n<meta property=\"article:published_time\" content=\"2026-03-25T07:00:00+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/blog.ptvgroup.com\/wp-content\/uploads\/2026\/02\/Untitled-design-7.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1025\" \/>\n\t<meta property=\"og:image:height\" content=\"577\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Devrim Kara\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"_ptadmin\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"7 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/blog.ptvgroup.com\\\/en\\\/modeling-planning\\\/cargo-bike-traffic-simulation-ptv-vissim\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/blog.ptvgroup.com\\\/en\\\/modeling-planning\\\/cargo-bike-traffic-simulation-ptv-vissim\\\/\"},\"author\":{\"name\":\"Guest Author\",\"@id\":\"https:\\\/\\\/blog.ptvgroup.com\\\/en\\\/#\\\/schema\\\/person\\\/ed495d952d445e59d4114dedcd7a86ba\"},\"headline\":\"Cargo bike traffic simulation for cycling infrastructure\",\"datePublished\":\"2026-03-25T07:00:00+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/blog.ptvgroup.com\\\/en\\\/modeling-planning\\\/cargo-bike-traffic-simulation-ptv-vissim\\\/\"},\"wordCount\":1098,\"publisher\":{\"@id\":\"https:\\\/\\\/blog.ptvgroup.com\\\/en\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/blog.ptvgroup.com\\\/en\\\/modeling-planning\\\/cargo-bike-traffic-simulation-ptv-vissim\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/blog.ptvgroup.com\\\/wp-content\\\/uploads\\\/2026\\\/02\\\/Untitled-design-7.png\",\"keywords\":[\"Cycling\",\"Traffic Simulation\",\"Urban Mobility\"],\"articleSection\":[\"Modeling &amp; 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