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<!DOCTYPE html>
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<title>ESP: Extro-Spective Prediction for Long-term Behavior Reasoning in Emergency Scenarios</title>
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<h1 class="title is-1 publication-title">ESP: Extro-Spective Prediction </h1>
<h1 class="title is-5 publication-title">For Long-term Behavior Reasoning in Emergency Scenarios</h2>
<div class="is-size-5 publication-authors">
<span class="author-block">
<a href="https://www.linkedin.com/in/dingrui-wang/">Dingrui Wang</a><sup>1,4</sup>,</span>
<span class="author-block">
<a href="https://en.inceptio.ai/">Zheyuan Lai</a><sup>1</sup>,</span>
<span class="author-block">
<a href="https://en.inceptio.ai/">Yuda Li</a><sup>1</sup>,
</span>
<span class="author-block">
<a href="https://www.njupt.edu.cn/">Yi Wu</a><sup>2</sup>,
</span>
<span class="author-block">
<a href="https://yuexinma.me/">Yuexin Ma</a><sup>3</sup>,
</span>
<span class="author-block">
<a href="https://www.mos.ed.tum.de/en/avs/team/prof-dr-ing-johannes-betz/">Johannes Betz</a><sup>4</sup>,
</span>
<span class="author-block">
<a href="https://en.inceptio.ai/">Ruigang Yang</a><sup>1</sup>,
</span>
<span class="author-block">
<a href="https://en.inceptio.ai/">Wei Li</a><sup>1</sup>
</span>
</div>
<div class="is-size-5 publication-authors">
<span class="author-block"><sup>1</sup>Inceptio Technology,</span>
<span class="author-block"><sup>2</sup>NJUPT,</span>
<span class="author-block"><sup>3</sup>SHTU,</span>
<span class="author-block"><sup>4</sup>TUM</span>
</div>
<div class="column has-text-centered">
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class="external-link button is-normal is-rounded is-dark">
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<span>arXiv</span>
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<span>Data</span>
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</section>
<h2 class="title has-text-centered">
An Emergency Scenario
<img class="emergency-icon" src="./icons/emergency_icon.svg" alt="Emergency Icon">
</h2>
<section class="hero teaser">
<div class="hero-body">
<div class="video-container">
<div class="video-wrapper">
<video poster="" id="steve" autoplay muted loop playsinline height="100%">
<source src="./static/videos/left_cam.mp4"
type="video/mp4">
</video>
<h2 class="subtitle has-text-centered">
Left camera
</h2>
</div>
<div class="video-wrapper">
<video poster="" id="chair-tp" autoplay muted loop playsinline height="100%">
<source src="./static/videos/front_cam.mp4"
type="video/mp4">
</video>
<h2 class="subtitle has-text-centered">
Front Camera
</div>
</div>
<div class="video-container">
<div class="video-wrapper">
<video id="teaser" autoplay muted loop playsinline height="100%">
<source src="./static/videos/teaser.mp4"
type="video/mp4">
</video>
<h2 class="subtitle has-text-centered">
The autonomous truck was forced to brake suddenly as a sedan cut in front of it on the highway.
</h2>
</div>
</div>
</div>
</section>
<h2 class="title has-text-centered">
Front blocking scenarios
<img class="impression-icon" src="./icons/block.svg" alt="Impression Icon">
</h2>
<section class="hero is-light is-small">
<div class="hero-body">
<div class="container">
<div id="results-carousel" class="carousel results-carousel">
<div class="item item-steve">
<video poster="" id="steve" autoplay controls muted loop playsinline height="100%">
<source src="./dataset_samples_vid/front_blocking/9a6ef3ae-462a-54a3-a717-2e89a91413bb.mp4"
type="video/mp4">
</video>
</div>
<div class="item item-chair-tp">
<video poster="" id="chair-tp" autoplay controls muted loop playsinline height="100%">
<source src="./dataset_samples_vid/front_blocking/19c410d6-2a23-4445-9c72-2314da3710c9.mp4"
type="video/mp4">
</video>
</div>
<div class="item item-shiba">
<video poster="" id="shiba" autoplay controls muted loop playsinline height="100%">
<source src="./dataset_samples_vid/front_blocking/644b0778-db3a-5de6-9feb-df114f4c4301.mp4"
type="video/mp4">
</video>
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<video poster="" id="shiba" autoplay controls muted loop playsinline height="100%">
<source src="./dataset_samples_vid/front_blocking/adb6432c-5327-4f93-a21c-96aa36f98238.mp4"
type="video/mp4">
</video>
</div>
</div>
</div>
</div>
</section>
<h2 class="title has-text-centered">
On ramp merge scenarios
<img class="impression-icon" src="./icons/merge.svg" alt="Impression Icon">
</h2>
<section class="hero is-light is-small">
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<div class="container">
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<source src="./dataset_samples_vid/on_ramp_merge/2fc2cc6c-dad2-4550-a91a-3f7282322e82.mp4"
type="video/mp4">
</video>
</div>
<div class="item item-chair-tp">
<video poster="" id="chair-tp" autoplay controls muted loop playsinline height="100%">
<source src="./dataset_samples_vid/on_ramp_merge/37201cfb-89d0-4205-9035-b90c223876e3.mp4"
type="video/mp4">
</video>
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type="video/mp4">
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type="video/mp4">
</video>
</div>
</div>
</div>
</div>
</section>
<h2 class="title has-text-centered">
Ramp out scenarios
<img class="impression-icon" src="./icons/rampout.png" alt="Impression Icon">
</h2>
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type="video/mp4">
</video>
</div>
<div class="item item-chair-tp">
<video poster="" id="chair-tp" autoplay controls muted loop playsinline height="100%">
<source src="./dataset_samples_vid/ramp_out/69c210ea-4095-40d9-9f32-ffea539d68a5.mp4"
type="video/mp4">
</video>
</div>
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<source src="./dataset_samples_vid/ramp_out/333c5d6e-a71f-5529-b65c-571c8e328a61.mp4"
type="video/mp4">
</video>
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<source src="./dataset_samples_vid/ramp_out/f2c8c065-77fa-40ed-bcbd-aaf267311a2d.mp4"
type="video/mp4">
</video>
</div>
</div>
</div>
</div>
</section>
<div class="container is-max-desktop">
<!-- Abstract. -->
<div class="columns is-centered has-text-centered">
<div class="column ">
<div class="content has-text-justified">
<p>
Videos of examples from the ESP dataset. The ESP-Dataset with semantic environment information focuses on
emergency-event-based challenging scenarios. The collected scenarios encompassed
various interactions such as merges, lane changes, ramp
out, cone block, and zip lane.
</p>
</div>
</div>
</div>
<section class="section">
<div class="container is-max-desktop">
<!-- Abstract. -->
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<h2 class="title is-3">Abstract</h2>
<div class="content has-text-justified">
<p>
Emergent-scene safety is the key milestone for fully autonomous driving,
and reliable on-time prediction is essential to maintain safety in emergency scenarios.
However, these emergency scenarios are long-tailed and hard to collect,
which restricts the system from getting reliable predictions.
</p>
<p>
In this paper, we build a new dataset, which aims at the long-term prediction with the inconspicuous
state variation in history for the emergency event, named the <i>Extro-Spective Prediction (ESP)</i> problem.
Based on the proposed dataset, a flexible feature encoder for <i>ESP</i> is introduced to various prediction methods
as a seamless plug-in, and its consistent performance improvement underscores its efficacy.
Furthermore, a new metric named <i>clamped temporal error (CTE)</i> is proposed to give a more comprehensive
evaluation of prediction performance, especially in time-sensitive emergency events of subseconds.
Interestingly, as our <i>ESP</i> features can be described in human-readable language naturally, the application of
integrating into <i>ChatGPT</i> also shows huge potential.
</p>
</div>
</div>
</div>
<!--/ Abstract. -->
<!-- Paper video. -->
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<h2 class="title is-3">Video</h2>
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<iframe src="https://www.youtube.com/embed/SsYsCZs2Sys?si=r0elQ9mFwKCl1hFw&showinfo=0"
frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
</div>
</div>
</div>
<!--/ Paper video. -->
</div>
</section>
<section class="section" id="BibTeX">
<div class="container is-max-desktop content">
<h2 class="title">BibTeX</h2>
<pre><code>@article{dingrui2024esp,
author = {Wang, Dingrui and Lai, Zheyuan and Li, Yuda and Wu, Yi and Ma, Yuexin and Betz, Johannes and Yang, Ruigang and Li, Wei},
title = {ESP: Extro-Spective Prediction for Long-term Behavior Reasoning in Emergency Scenarios},
journal = {ICRA},
year = {2024},
}</code></pre>
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