Research Article
Development of Pavement Distress Deterioration Prediction Models for Urban Road Network Using Genetic Programming
Table 2
Traffic volume data of road sections.
| Section ID | Cycle | Rickshaw/rehri | Scooter/M-cycle | Car/jeep/auto | Bus/truck/tractor/trolly | Cart | Total | ESA in the year 2013 (in millions) |
| UR01 | 198 | 118 | 350 | 371 | 112 | 22 | 1171 | 0.281 | 16.9 | 10 | 30 | 31.7 | 9.6 | 1.8 | 100 | UR02 | 234 | 73 | 552 | 285 | 33 | 5 | 1182 | 0.072 | 19.8 | 6.2 | 46.7 | 24.1 | 2.8 | 0.4 | 100 | UR03 | 152 | 141 | 341 | 285 | 78 | 5 | 1002 | 0.112 | 15.2 | 14.07 | 34.03 | 28.44 | 7.8 | 0.5 | 100 | UR04 | 108 | 18 | 251 | 115 | 10 | 3 | 505 | 0.194 | 21.7 | 3.5 | 49.7 | 22.7 | 1.9 | 0.6 | 100 | UR05 | 110 | 69 | 272 | 317 | 120 | 12 | 900 | 0.424 | 12.2 | 7.66 | 30.2 | 35.2 | 13.3 | 1.44 | 100 | UR06 | 251 | 180 | 547 | 265 | 33 | 4 | 1280 | 0.144 | 20 | 14 | 42 | 21 | 2.6 | 0.4 | 100 | UR07 | 267 | 201 | 584 | 535 | 129 | 15 | 1731 | 0.230 | 15.4 | 11.6 | 33.7 | 31 | 7.4 | 0.9 | 100 | UR08 | 191 | 207 | 651 | 880 | 425 | 3 | 2357 | 0.127 | 8.1 | 8.8 | 27.61 | 37.34 | 18.03 | 0.12 | 100 | UR09 | 171 | 158 | 470 | 338 | 29 | 2 | 1168 | 0.225 | 15 | 14 | 40 | 28.4 | 2.5 | 0.1 | 100 | UR10 | 407 | 459 | 1104 | 65 | 5 | ā | 2040 | 0.129 | 20 | 22.5 | 54.1 | 3.2 | 0.2 | ā | 100 | UR11 | 583 | 247 | 705 | 864 | 438 | 5 | 2842 | 0.166 | 21 | 9 | 25 | 29.8 | 15 | 0.2 | 100 | UR12 | 464 | 358 | 722 | 878 | 34 | 12 | 2468 | 0.036 | 19 | 14.5 | 29 | 35.6 | 1.4 | 0.5 | 100 | UR13 | 404 | 92 | 548 | 347 | 196 | 5 | 1592 | 0.902 | 25.4 | 5.8 | 34.4 | 21.8 | 12.3 | 0.3 | 100 | UR14 | 554 | 349 | 1275 | 1106 | 112 | 8 | 3404 | 0.115 | 16.3 | 10.2 | 37.5 | 32.5 | 3.3 | 0.2 | 100 | UR15 | 381 | 319 | 1427 | 1179 | 714 | 20 | 4040 | 0.928 | 9.4 | 7.6 | 35.2 | 29.2 | 17.6 | 1 | 100 | UR16 | 371 | 180 | 580 | 144 | 2 | 3 | 1280 | 0.003 | 29 | 14 | 45.3 | 11.3 | 0.15 | 0.25 | 100 |
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