Our dataset contains about fifteen hours of driving data, including easy mode, medium mode and hard mode. We record data and motion commands at 10 frames per second. The labeling contains steering angle, accelerator and brake.

The dataset is divided into 3 folders according to task difficulty, i.e., easy, mdium and hard. Each difficulty of data is further divided into 5 csv files according to episode, and an episode means a process from the starting point to the end point. One single csv file contains a maximum of 300 episodes, and one difficulty of data contains nearly 1300 episodes, so there are 5 csv files in each diffculty data folder. Note that the name of csv file also incates the index range of episodes.

In each csv file, there are 29 columns and many number of rows, and a row of data are sampled within one single frame. The first 2 columns is the episode and frame indices. That is, frames sampled in the same episode have a same episode index, and every epiode in the same difficulty of dataset has a unique episode index. Note that episodes may contain different number of frames.

The other 27 columns is the vehicles' kinematic and command data, and can be further divided into four part. The first and second part denotes the X- and Y-Axis coordinates and speed values of ego-vehicle and other sorrounding vehicles. The third part three columns of data stands for the accelerator, braking values and the steering angle of the ego-vehicle. Finally, the last part contains distances from the center of ego-vehicle to the left and right lane lines of the current lane and the road boundaries, respectively.

All data columns and their detailed meanings are listed below.

This is an example of the top 10 rows in one cvs file. Note that the first column is the row indices and has no column name. The other 29 columns all have column names which indicate the meanning of each column data as metioned before.

| | vx_other_1 | vx_other_2 | vx_other_3 | vx_other_4 | vy_ego | vy_other_1 | vy_other_2 | vy_other_3 | vy_other_4 | throttle | braking | steering | d_left_1 | d_right_1 | d_left_2 | d_right_2 | | ---- | ---------- | ---------- | ---------- | ---------- | --------- | ---------- | ---------- | ---------- | ---------- | ---------- | ---------- | ---------- | ------------- | --------- | --------- | ------------- | --------- | --------- | --------- | --------- | --------- | --------- | --- | --- | --------- | -------- | -------- | -------- | -------- | | 0 | 0 | 0 | -1.378816 | 43.075848 | 37.514030 | -21.242659 | -33.793720 | 207.399994 | 207.399994 | 204.199997 | 204.099991 | 203.800003 | 0.000000e+00 | 0.000000 | 0.000000 | 0.000000e+00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.000000 | 1.599994 | 1.900006 | 5.099994 | 1.900006 | | 1 | 0 | 1 | -1.378816 | 43.075848 | 37.514030 | -21.242659 | -33.793720 | 207.399994 | 207.399994 | 204.199997 | 204.099991 | 203.800003 | 0.000000e+00 | 0.000000 | 0.000000 | 0.000000e+00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 1.0 | -0.800000 | 1.599994 | 1.900006 | 5.099994 | 1.900006 | | 2 | 0 | 2 | -1.378816 | 43.075848 | 37.516048 | -21.242188 | -33.793720 | 207.399994 | 207.399994 | 204.199982 | 204.100021 | 203.800003 | 0.000000e+00 | 0.000000 | 0.039877 | -7.456872e-12 | 0.000000 | 0.000000 | 0.000000 | -0.000003 | 0.001109 | 0.000000 | 0.0 | NaN | 0.800000 | 1.599994 | 1.900006 | 5.099994 | 1.900006 | | 3 | 0 | 3 | -1.377847 | 43.081387 | 37.518650 | -21.240322 | -33.793350 | 207.399445 | 207.399796 | 204.200546 | 204.099854 | 203.800003 | 3.657267e-04 | -0.002114 | -0.001971 | 9.642183e-04 | 0.000000 | -0.037941 | -0.001820 | 0.001286 | -0.004583 | 0.000000 | 0.7 | 0.0 | -0.031490 | 1.599445 | 1.900555 | 5.099445 | 1.900555 | | 4 | 0 | 4 | -1.377867 | 43.081009 | 37.518475 | -21.240503 | -33.791050 | 207.399368 | 207.399689 | 204.200424 | 204.099777 | 203.801300 | -5.397946e-08 | -0.001512 | -0.001016 | -5.815665e-04 | 0.000019 | 0.004897 | 0.001210 | -0.001752 | 0.001263 | -0.000171 | 0.7 | 0.0 | -0.215264 | 1.599368 | 1.900632 | 5.099368 | 1.900632 | | 5 | 0 | 5 | -1.377816 | 43.080799 | 37.518440 | -21.240761 | -33.791470 | 207.398987 | 207.399628 | 204.200394 | 204.099777 | 203.800613 | -8.069370e-05 | -0.000661 | -0.000463 | -2.371819e-04 | -0.000642 | 0.009371 | 0.001019 | -0.001033 | 0.001417 | -0.000556 | 0.7 | 0.0 | -0.006196 | 1.598987 | 1.901013 | 5.098987 | 1.901013 | | 6 | 0 | 6 | -1.377796 | 43.080723 | 37.518429 | -21.240871 | -33.791767 | 207.398987 | 207.399643 | 204.200302 | 204.099899 | 203.800308 | -4.515704e-05 | -0.000242 | -0.000166 | -9.692906e-05 | -0.000291 | 0.005386 | 0.000418 | -0.000467 | 0.000626 | -0.000237 | 0.7 | 0.0 | 0.000687 | 1.598987 | 1.901013 | 5.098987 | 1.901013 | | 7 | 0 | 7 | -1.377786 | 43.080692 | 37.518425 | -21.240913 | -33.791897 | 207.398987 | 207.399582 | 204.200348 | 204.099854 | 203.800171 | -1.858471e-05 | -0.000087 | -0.000056 | -4.138955e-05 | -0.000123 | 0.002229 | 0.000157 | 0.000058 | -0.000028 | -0.000093 | 0.7 | 0.0 | 0.002111 | 1.598987 | 1.901013 | 5.098987 | 1.901013 | | 8 | 0 | 8 | -1.377783 | 43.080692 | 37.518433 | -21.240925 | -33.791950 | 207.398804 | 207.399567 | 204.200363 | 204.099838 | 203.800125 | -6.908410e-06 | -0.000036 | -0.000022 | -1.640508e-05 | -0.000049 | 0.000196 | -0.000004 | 0.000030 | -0.000041 | -0.000040 | 0.7 | 0.0 | 0.002621 | 1.598804 | 1.901196 | 5.098804 | 1.901196 | | 9 | 0 | 9 | -1.377782 | 43.080692 | 37.518433 | -21.240932 | -33.791965 | 207.398743 | 207.399567 | 204.200363 | 204.099823 | 203.800095 | -2.370085e-06 | -0.000020 | -0.000013 | -6.677407e-06 | -0.000017 | 0.000040 | -0.000002 | 0.000012 | -0.000017 | -0.000039 | 0.7 | 0.0 | 0.002692 | 1.598743 | 1.901257 | 5.098743 | 1.901257 |

This is an example of ego-vehicle(blue) overtaking other vehicle(orange) in our dataset, captured in the CARLA simulator.