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<title>CALM</title>
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<h1>CALM</h1>
<p class="sub">Comfort-Aware Longitudinal Motion</p>
<p class="tag">Slow down for the bump, not for the sake of it.</p>
<p>Every driver knows the moment. A speed bump comes up, you have half a second to decide, and the car answers with a jolt that should have been a ripple. CALM is an open research project about that decision: how a car can read the road ahead and ease off by exactly as much as the bump deserves, so the people inside barely notice it.</p>
<p>CALM began as a bachelor thesis at TU Berlin and has grown into an open source stack for comfort-aware speed recommendation. It contributes:</p>
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<li><b>An open source software stack for the slowdown-depth decision:</b> a half-car simulator with nonlinear suspension, a Gymnasium environment, an acados MPC, a PPO policy and ISO 2631-1 comfort scoring.</li>
<li><b>The CALM dataset:</b> 159 real bump crossings from <a href="https://huggingface.co/CARD-Data">CARD</a> (114 Germany, 45 Italy; 105 usable), an extended real-time dataset for comfort.</li>
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<h2>Models and data</h2>
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<a class="card" href="https://huggingface.co/CALM-Dataset/CALM-PPO"><b>CALM-PPO</b><small>The trained speed recommender, with its five training runs.</small></a>
<a class="card" href="https://huggingface.co/datasets/CALM-Dataset/CALM-Scenarios"><b>CALM-Scenarios</b><small>Road profiles of 159 real crossings, ready to simulate.</small></a>
<a class="card" href="https://huggingface.co/datasets/CALM-Dataset/CALM-Germany"><b>CALM-Germany</b><small>114 crossings with camera, depth and sensor recordings. Access on request.</small></a>
<a class="card" href="https://huggingface.co/datasets/CALM-Dataset/CALM-Italy"><b>CALM-Italy</b><small>45 crossings with camera, depth and sensor recordings. Access on request.</small></a>
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<h2>Code</h2>
<p>The simulator and the planners are on <a href="https://github.com/CALM-Dataset">GitHub</a>, together with the MATLAB ride models in <a href="https://github.com/CALM-Dataset/ride-models-matlab">ride-models-matlab</a>.</p>
<p class="foot">Acknowledgements: the real-road recordings build on the <a href="https://huggingface.co/CARD-Data">CARD dataset</a> (<a href="https://arxiv.org/abs/2605.05014">Elazab et al., CVPR 2026</a>).</p>
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