Application of Data Science Technologies in Intelligent Prediction of Traffic Congestion

<table class="fixed-width table-group" id="tab3"><tr><td><table class="table"><colgroup><col style="width:8.58em"/><col style="width:12.72em"/><col style="width:13.60em"/></colgroup><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td class="align_left">Congestion Grade </td><td class="align_center">Average Road Occupancy <svg height="15.7358pt" id="M56" style="vertical-align:-3.5977pt" version="1.1" viewbox="-0.0498162 -12.1381 11.9019 15.7358" width="11.9019pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><rect height="0.65243" width="11.8022" x="0" y="-11.4359"></rect><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M445 282C445 390 384 448 297 448C266 448 231 437 189 418C96 376 23 279 23 151C23 65 66 -12 169 -12C233 -12 294 18 337 53C411 113 445 201 445 282ZM355 280C355 161 302 62 243 36C231 31 219 30 207 30C147 30 111 78 111 154C111 302 180 380 220 399C231 404 246 407 264 407C311 407 355 367 355 280Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,6.084,-4.661)"><path d="M545 403C545 425 527 451 498 451C448 451 400 404 312 286L290 341C262 412 246 451 219 451C182 451 138 404 92 345L112 323C152 368 169 378 181 378C192 378 201 359 216 321L257 214C184 115 142 69 113 69C102 69 93 73 88 79S78 89 68 89C47 89 24 61 24 40C24 8 49 -12 75 -12C125 -12 175 31 271 175L312 64C330 15 357 -12 382 -12C421 -12 475 35 515 98L496 121C466 88 439 62 420 62C402 62 384 92 363 147L325 247C349 280 374 309 397 333C422 361 446 381 462 381C471 381 481 374 488 366C493 360 499 357 505 357C521 357 545 380 545 403Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,6.019,3.438)"><path d="M329 433H203L239 587L230 596L147 534L123 433H57L30 395L34 388H115L61 129C37 16 59 -12 85 -12C147 -12 222 58 260 98L241 125C212 95 160 62 144 62C132 62 127 71 138 126L192 386L305 394L329 433Z"></path></g></svg></td><td class="align_center">Preliminary Congestion Grade </td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left">No Congestion</td><td class="align_center"> -</td><td class="align_center">No Congestion</td></tr><tr><td class="align_left">Slight Congestion</td><td class="align_center"> -</td><td class="align_center">Slight Congestion</td></tr><tr><td class="align_left">No Congestion</td><td class="align_center"> <svg height="15.7358pt" id="M57" style="vertical-align:-3.5977pt" version="1.1" viewbox="-0.0498162 -12.1381 63.5138 15.7358" width="63.5138pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"></path></g><g transform="matrix(.013,0,0,-0.013,9.872,0)"><path d="M531 71V127L115 310L531 494V550L57 335V285L531 71ZM531 -40V10H57V-40H531Z"></path></g><rect height="0.65243" width="11.8022" x="21.1347" 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class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Result of congestion grade based on road occupancy.</div>

Journal of Advanced Transportation

tab3

Table 3

Table 3: Application of Data Science Technologies in Intelligent Prediction of Traffic Congestion 