A Personalized Navigation Route Recommendation Strategy Based on Differential Perceptron Tracking User’s Driving Preference

<table class="table-group" id="tab10"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td class="align_left">Paths</td><td class="align_center">Types</td><td class="align_center"><i>L</i> (km)</td><td class="align_center"><span style="width: 19.7768ptpx;"><svg height="11.927pt" id="M106" style="vertical-align:-3.291101pt" version="1.1" viewbox="-0.0498162 -8.6359 19.7768 11.927" width="19.7768pt" 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="M715 650H476L470 622C550 619 562 610 562 570C562 536 553 481 535 384L523 321C485 121 408 37 283 37C178 37 99 109 134 297L178 532C193 612 199 616 278 622L284 650H29L23 622C105 616 109 609 94 532L48 291C23 160 51 83 98 40C143 -1 202 -16 260 -16C321 -16 387 3 439 49C509 111 542 204 563 312L577 384C595 479 608 533 619 569C629 603 637 620 709 622L715 650Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,8.606,3.132)"><path d="M655 676H628C608 656 600 650 571 650H156C118 650 114 651 102 676H77C63 615 45 548 24 485L60 486C81 531 97 562 114 580C134 603 148 611 252 611H308L217 127C201 41 196 38 105 32L98 0H384L393 32C300 38 288 41 304 127L393 611H466C553 611 571 604 582 580C592 559 597 530 595 485L630 489C636 548 645 624 655 676Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,14.478,3.132)"><path d="M485 418C485 434 469 451 441 451C389 451 312 387 255 335C221 304 194 278 159 242H157L259 678C264 698 264 710 255 710C242 710 183 681 96 673L90 643L128 642C165 641 171 640 162 602L24 -5L31 -12C51 -4 81 4 110 9L145 181C154 195 180 220 205 242C233 170 263 106 291 53C318 1 335 -12 360 -12C383 -12 425 0 483 82L463 105C437 79 411 57 400 57C388 57 378 68 355 110C329 156 288 244 268 298C299 333 355 376 405 376C426 376 440 373 448 368C453 365 465 368 468 373C477 386 485 405 485 418Z"></path></g></svg></span></td><td class="align_center"><span style="width: 26.1106ptpx;"><svg height="11.9316pt" id="M107" style="vertical-align:-3.2957pt" version="1.1" viewbox="-0.0498162 -8.6359 26.1106 11.9316" width="26.1106pt" 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="M645 631C614 643 545 666 457 666C215 666 23 519 23 283C23 90 158 -16 337 -16C412 -16 489 2 522 10C543 39 590 127 606 167L580 181C519 89 459 18 348 18C201 18 122 136 122 287C122 464 244 632 435 632C544 632 602 595 608 472L639 475C643 526 645 581 645 631Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,8.619,3.132)"><path d="M303 37L293 66C280 59 256 49 231 49S173 63 173 143V396H281C294 404 298 428 287 439H173V575L158 577L92 509V439H46L17 408L22 396H92V107C92 27 128 -12 192 -12C203 -12 218 -9 237 2L303 37Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,11.412,3.132)"><path d="M262 451C169 451 38 375 38 210C38 98 121 -12 261 -12C360 -12 481 64 481 227C481 351 386 451 262 451ZM249 414C337 414 385 320 385 204C385 70 333 25 272 25C189 25 134 117 134 241C134 355 189 414 249 414Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,16.035,3.132)"><path d="M303 37L293 66C280 59 256 49 231 49S173 63 173 143V396H281C294 404 298 428 287 439H173V575L158 577L92 509V439H46L17 408L22 396H92V107C92 27 128 -12 192 -12C203 -12 218 -9 237 2L303 37Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,18.929,3.132)"><path d="M442 39L431 68C420 63 406 57 394 57C377 57 359 71 359 118V301C359 353 349 393 314 424C291 443 261 451 230 451C171 438 107 401 79 381C59 366 46 355 46 340C46 316 72 295 91 295C106 295 117 303 122 319C131 350 139 371 152 384C163 397 178 404 197 404C246 404 281 365 281 293V278C260 262 186 232 124 213C69 194 41 161 41 112C41 47 92 -12 163 -12C195 -12 243 25 283 51C288 35 293 22 308 7C319 -4 339 -12 354 -12L442 39ZM281 87C262 68 226 51 199 51C169 51 129 74 129 126C129 162 151 181 190 198C211 208 259 229 281 240V87Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,23.051,3.132)"><path d="M244 0V30C178 35 170 41 170 107V710C136 697 72 680 18 675V647C83 642 89 639 89 572V107C89 43 80 35 16 30V0H244Z"></path></g></svg></span></td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td class="align_left" rowspan="2">Initially planned route</td><td class="align_center"><i>M</i></td><td class="align_center">42.90</td><td class="align_center">20.652</td><td class="align_center" rowspan="2">20.936</td></tr><tr><td class="align_center"><i>S</i></td><td class="align_center">0.51</td><td class="align_center">0.284</td></tr><tr><td class="align_left" colspan="5"><hr/></td></tr><tr><td class="align_left" rowspan="3">Actual path</td><td class="align_center"><i>M</i></td><td class="align_center">4.09</td><td class="align_center">1.969</td><td class="align_center" rowspan="3">33.673</td></tr><tr><td class="align_center"><i>E</i></td><td class="align_center">60.4</td><td class="align_center">31.420</td></tr><tr><td class="align_center"><i>S</i></td><td class="align_center">0.51</td><td class="align_center">0.284</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>The total cost of the first two paths before adjusting in Experiment 1.</div>

Computational Intelligence and Neuroscience

tab10

Table 10

Table 10: A Personalized Navigation Route Recommendation Strategy Based on Differential Perceptron Tracking User’s Driving Preference 