<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Implicit Communication | Meng's Page</title><link>https://www.zhangmeng43.com/tags/implicit-communication/</link><atom:link href="https://www.zhangmeng43.com/tags/implicit-communication/index.xml" rel="self" type="application/rss+xml"/><description>Implicit Communication</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 18 Sep 2024 00:00:00 +0000</lastBuildDate><image><url>https://www.zhangmeng43.com/media/icon_hu_3c4bb17454bfe3f5.png</url><title>Implicit Communication</title><link>https://www.zhangmeng43.com/tags/implicit-communication/</link></image><item><title>Do cyclists disregard ‘priority-to-the-right’ more often than motorists?</title><link>https://www.zhangmeng43.com/publications/trf-cyclist-paper/</link><pubDate>Wed, 18 Sep 2024 00:00:00 +0000</pubDate><guid>https://www.zhangmeng43.com/publications/trf-cyclist-paper/</guid><description>&lt;div class="text-base text-justify"&gt;
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&lt;h3 id="background"&gt;Background&lt;/h3&gt;
&lt;p&gt;Do cyclists disregard traffic rules more often than motorists? Answering this is essential for optimizing traffic &lt;strong&gt;safety and efficiency&lt;/strong&gt; as we transition toward autonomous driving in mixed environments. Grounded in naturalistic observations at urban unsignalized intersections, our study utilizes &lt;strong&gt;quasi-experimental methods&lt;/strong&gt; and &lt;strong&gt;regression analysis&lt;/strong&gt; to quantify compliance behaviors. This research is the result of a seamless collaboration between project managers, sensor technicians, data engineers, and human factors researchers, aiming to provide the critical behavioral data needed for safe human-machine coexistence.&lt;/p&gt;
&lt;figure class="w-full my-6 flex flex-col items-center"&gt;
&lt;img src="workflow.svg"&gt;
&lt;figcaption class="figure-caption"&gt;
&lt;strong&gt;Figure 1. The Collaborative Project Workflow.&lt;/strong&gt;
&lt;/figcaption&gt;
&lt;/figure&gt;
&lt;hr&gt;
&lt;h3 id="methods"&gt;Methods&lt;/h3&gt;
&lt;p&gt;Using stationary cameras, a 12-day naturalistic traffic observation was conducted at an urban T-intersection in &lt;em&gt;Braunschweig, Germany&lt;/em&gt;. The video footage underwent spatial calibration to establish a real-world coordinate system. Road users were detected and classified, and their movements were converted into georeferenced trajectories. In &lt;strong&gt;202&lt;/strong&gt; interaction cases, a car from the right (Ego, with priority) encountered a car or a bike from the left (Foe, without priority). The study examined how the following factors associated with the &lt;strong&gt;violation&lt;/strong&gt; using logistic regression:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Ego&amp;rsquo;s turning direction (left vs. right)&lt;/li&gt;
&lt;li&gt;Foe&amp;rsquo;s type (car vs. bike)&lt;/li&gt;
&lt;li&gt;Relative arrival time&lt;/li&gt;
&lt;li&gt;Foe&amp;rsquo;s lateral position&lt;/li&gt;
&lt;/ul&gt;
&lt;figure class="w-full my-6 flex flex-col items-center"&gt;
&lt;iframe src="traffic_demo1.html"
class="w-full h-[520px] rounded-xl border border-gray-200 shadow-sm bg-white"
loading="lazy"
allowfullscreen&gt;
&lt;/iframe&gt;
&lt;figcaption class="figure-caption"&gt;
&lt;strong&gt;Figure 2.&lt;/strong&gt; Traffic Scenarios: Compliance vs Violation.
&lt;/figcaption&gt;
&lt;/figure&gt;
&lt;hr&gt;
&lt;h3 id="key-findings"&gt;Key Findings&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;Cyclists violated the “priority-to-the-right” rule more frequently than motorists.&lt;/li&gt;
&lt;li&gt;Road users with priority were more likely to yield when:
&lt;ul&gt;
&lt;li&gt;turning right&lt;/li&gt;
&lt;li&gt;facing a bike&lt;/li&gt;
&lt;li&gt;arriving later at the intersection&lt;/li&gt;
&lt;li&gt;facing a road user &lt;strong&gt;close to the lane center&lt;/strong&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;/li&gt;
&lt;/ul&gt;
&lt;hr&gt;
&lt;h3 id="conclusion"&gt;Conclusion&lt;/h3&gt;
&lt;p&gt;This study underscores the importance of implicit communication in mixed traffic. It provides empirical benchmarks for designing human-like autonomous driving systems, which is supposed to be capable of interpreting and responding to nuanced road-user interactions at unsignalized intersections.&lt;/p&gt;
&lt;/div&gt;</description></item></channel></rss>