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<title>High-definition map</title>

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High-definition map

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A high-definition map (HD map) is a highly accurate <a href="Map" title="Map">map</a> used primarily in the field of <a href="Self-driving_car" title="Self-driving car">autonomous driving</a>,<a href="#cite_note-1">[1]</a><a href="#cite_note-2">[2]</a> containing details not normally present on traditional maps.<a href="#cite_note-Geospacial-3">[3]</a><a href="#cite_note-EETimes-4">[4]</a> HD maps are often captured using an array of sensors, such as <a href="LiDAR" class="mw-redirect" title="LiDAR">LiDARs</a>, <a href="Radar" title="Radar">radars</a>, <a href="Digital_camera" title="Digital camera">digital cameras</a>, and <a href="GPS" class="mw-redirect" title="GPS">GPS</a>,<a href="#cite_note-Geospacial-3">[3]</a><a href="#cite_note-5">[5]</a><a href="#cite_note-6">[6]</a> and they can also be constructed using <a href="Aerial_imagery" class="mw-redirect" title="Aerial imagery">aerial imagery</a>.<a href="#cite_note-7">[7]</a><a href="#cite_note-8">[8]</a> Such maps can be precise at a centimetre level.<a href="#cite_note-Geospacial-3">[3]</a><a href="#cite_note-9">[9]</a>

High-definition maps for self-driving cars usually include map elements such as road shape, <a href="Road_surface_marking" title="Road surface marking">road marking</a>, <a href="Traffic_sign" title="Traffic sign">traffic signs</a>, and barriers.<a href="#cite_note-EETimes-4">[4]</a><a href="#cite_note-10">[10]</a> Maintaining high accuracy is one of the biggest challenges in building HD maps of real-world roads. With regard to accuracy, there are two main focus points that determine the quality of an HD map:

<ul><li>Global accuracy (positioning of a feature on the surface of the Earth).</li>

<li>Local accuracy (positioning of a feature in relation to road elements around it).</li></ul>

In areas with good GPS reception it is possible to achieve a global accuracy of less than 3 cm (1.2 in) deviation using satellite signals and correction data from base stations.

In GPS-denied areas, however, inaccuracy rises with distance traveled through the area, being largest in its middle. This means that the maximum GPS error can be expressed as a percentage of the distance traveled through a GPS-denied area: this value is less than 0.5%.<a href="#cite_note-11">[11]</a>

<div class="mw-heading mw-heading2"><h2 id="References">References</h2></div>

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</style><cite id="CITEREFLiuWangZhang2019" class="citation journal cs1">Liu, Rong; Wang, Jinling; Zhang, Bingqi (27 August 2019). <a rel="nofollow" class="external text" href="https://www.cambridge.org/core/product/identifier/S0373463319000638/type/journal_article">"High Definition Map for Automated Driving: Overview and Analysis"</a>. Journal of Navigation. 73 (2): 324–341. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1017%2FS0373463319000638">10.1017/S0373463319000638</a>. <a href="Hdl_(identifier)" class="mw-redirect" title="Hdl (identifier)">hdl</a>:<a rel="nofollow" class="external text" href="https://hdl.handle.net/1959.4%2Funsworks_77182">1959.4/unsworks_77182</a>. <a href="ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/0373-4633">0373-4633</a>. <a href="S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:202906063">202906063</a>. Retrieved 2024-11-08.</cite>

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