我的数据包括vehicle_ID、x 和y 坐标（用于位置）、车辆的速度、它们行驶的时间。我们想知道哪些汽车走的是相同的道路？
这是我的数据样本，其中有 1 辆 ID 为 1 的车辆，我有 700000 个车辆 ID 需要分析
所以基本上我需要了解我们如何找出不同的道路以及我们如何将一条道路与另一条道路分开？
time vehicleID X Y speed
37081 1 13379.67 13854.72 0
37082 1 13379.322 13852.335 2.41
37083 1 13378.634 13847.615 4.77
37084 1 13377.623 13840.689 7
37085 1 13376.545 13833.297 7.47
37086 1 13375.136 13826.096 7.34
37087 1 13373.474 13818.24 8.03
37088 1 13371.802 13810.335 8.08
37089 1 13370.169 13802.616 7.89
37090 1 13368.569 13795.053 7.73
37091 1 13366.955 13787.422 7.8
37092 1 13365.392 13780.035 7.56
37093 1 13363.871 13772.844 7.35
37094 1 13363.711 13765.055 7.87
37095 1 13364.266 13758.629 6.45
37096 1 13364.638 13754.325 4.31
37097 1 13357.84 13745.829 6.5
37098 1 13349.609 13743.875 8.46
37099 1 13339.753 13741.536 10.14
37100 1 13328.213 13738.797 11.86
37101 1 13314.81 13735.516 13.8
37102 1 13303.798 13732.684 11.37
37103 1 13295.846 13730.64 8.2
37104 1 13290.481 13729.26 5.54
37105 1 13272.703 13727.245 7.4
37106 1 13263.911 13727.606 8.79
37107 1 13253.599 13728.03 10.32
37108 1 13241.689 13728.52 11.92
37109 1 13228.271 13729.071 13.43
37110 1 13214.942 13729.619 13.34
37111 1 13201.094 13730.188 13.86
37112 1 13188.944 13730.687 12.16
37113 1 13179.592 13731.072 9.37
37114 1 13173.727 13731.317 5.86
37115 1 13170.45 13731.454 3.28
37116 1 13149.29 13724.032 5.38
37117 1 13142.731 13720.212 7.59
37118 1 13135.04 13715.734 8.9
37119 1 13122.401 13705.994 10.24
37120 1 13113.877 13697.358 12.19
37121 1 13109.867 13685.023 12.97
37122 1 13095.963 13675.928 13.76
37123 1 13083.114 13672.126 13.4
37124 1 13070.658 13668.44 12.98
37125 1 13058.278 13664.777 12.92
37126 1 13045.822 13661.091 12.98
37127 1 13034.085 13657.619 12.24
37128 1 13026.376 13655.337 8.04
37129 1 13021.054 13653.763 5.55
37130 1 13001.211 13641.21 6.93
37131 1 12994.959 13634.708 9.02
37132 1 12987.682 13627.139 10.51
37133 1 12979.33 13618.452 12.05
37134 1 12970.403 13609.168 12.87
37135 1 12961.123 13599.515 13.4
37136 1 12952.217 13590.252 12.85
37137 1 12934.75 13572.71 13.69
37138 1 12924.495 13563.808 13.58
37139 1 12914.437 13555.076 13.33
37140 1 12904.507 13546.455 13.15
37141 1 12894.131 13537.448 13.74
37142 1 12885.575 13530.02 11.33
37143 1 12880.01 13525.189 7.37
37144 1 12876.015 13521.721 5.29
37145 1 12874.784 13520.652 1.63
37146 1 12862.971 13510.873 3.16
37147 1 12859.101 13507.851 4.91
37148 1 12854.12 13503.961 6.32
37149 1 12847.949 13499.141 7.83
37150 1 12840.21 13493.096 9.82
37151 1 12830.934 13485.852 11.77
37152 1 12822.446 13479.222 10.76
37153 1 12814.622 13473.322 9.8
37154 1 12808.253 13468.581 7.94
37155 1 12804.065 13465.464 5.22
37156 1 12802.212 13464.085 2.31
37157 1 12796.969 13444.202 4.17
37158 1 12797.734 13438.251 5.99
37159 1 12798.746 13430.375 7.95
37160 1 12799.913 13421.29 9.16
37161 1 12801.268 13410.747 10.63
37162 1 12802.834 13398.557 12.28
37163 1 12792.406 13383.284 13.64
37164 1 12782.269 13374.52 13.39
37165 1 12772.352 13365.946 13.11
37166 1 12761.928 13356.934 13.78
37167 1 12751.965 13348.32 13.17
37168 1 12744.529 13341.891 9.84
37169 1 12739.582 13337.614 6.53
37170 1 12737.259 13335.606 3.07
37171 1 12732.41 13322.801 5.27
37172 1 12737.789 13318.106 7.14
37173 1 12744.69 13312.082 9.16
37174 1 12753.226 13304.631 11.33
37175 1 12762.718 13296.345 12.6
37176 1 12772.421 13287.876 12.88
37177 1 12782.306 13279.248 13.12
37178 1 12792.152 13270.653 13.08
37179 1 12800.333 13263.511 10.86
37180 1 12805.615 13258.901 7.01