Telkwevr/Bench2Drive-VL-base
Bench2Drive-VL: Full-Stack Software for Closed-Loop Autonomous Driving with Vision Language Models Project Page | GitHub | Paper Bench2Drive-VL is a comprehensive closed-loop benchmark for Vision-Language Models in Autonomous Driving (VLM4AD). It extends the Bench2Drive benchmark by introducing closed-loop evaluation and the DriveCommenter expert model for automated annotation. This repository contains the natural language annotations for the Bench2Drive-Base1000 dataset. These… See the full description on the dataset page: https://huggingface.co/datasets/Telkwevr/Bench2Drive-VL-base.
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"type_id": "vehicle.lincoln.mkz_2017",728 "color": "16,16,16",729 "base_type": "car",730 "num_points": 2074,731 "distance": 3.818170692094264,732 "speed": 0.0,733 "brake": 0.0,734 "light_state": "3",735 "road_id": 196,736 "lane_id": 3,737 "section_id": 0,738 "world2vehicle": [739 [740 0.7756944298744202,741 -0.6294666528701782,742 -0.04549720138311386,743 -65.933837890625744 ],745 [746 0.6301091909408569,747 0.7765064835548401,748 -0.0002806195698212832,749 -743.395751953125750 ],751 [752 0.035505510866642,753 -0.028450528159737587,754 0.9989644289016724,755 -119.9437484741211756 ],757 [758 0.0,759 0.0,760 0.0,761 1.0762 ]763 ],764 "position": [765 2.1882253404351673,766 3.129405683686855,767 0.03685500413803311768 ],769 "yaw": 0.028024111255767564,770 "color_rgb": null,771 "color_name": null,772 "lane_type": 2,773 "lane_type_str": "Driving",774 "is_in_junction": false,775 "junction_id": -1,776 "distance_to_junction": 175.43359375,777 "next_junction_id": 307,778 "next_road_ids": [779 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"<c223<CAM_FRONT_RIGHT,1181.8,1470.0><CAM_BACK_RIGHT,-1295.0,1146.6><CAM_FRONT,1752.4,705.8>>"820 ]821 },822 {823 "Q": "What are the important objects in the scene? List them from most to least important.",824 "A": "The black car that is to the front right of the ego vehicle(<c223<CAM_FRONT_RIGHT,1181.8,1470.0><CAM_BACK_RIGHT,-1295.0,1146.6><CAM_FRONT,1752.4,705.8>>), the maroon SUV that is to the front right of the ego vehicle(<c224<CAM_FRONT,1155.0,520.1><CAM_FRONT_RIGHT,-224.2,543.6>>), the black police car that is to the front right of the ego vehicle(<c225<CAM_FRONT,989.9,491.4>>).",825 "C": null,826 "qid": 19,827 "con_up": -1,828 "con_down": -1,829 "cluster": 0,830 "layer": 0,831 "object_tags": [832 "<c223<CAM_FRONT_RIGHT,1181.8,1470.0><CAM_BACK_RIGHT,-1295.0,1146.6><CAM_FRONT,1752.4,705.8>>",833 "<c224<CAM_FRONT,1155.0,520.1><CAM_FRONT_RIGHT,-224.2,543.6>>",834 "<c225<CAM_FRONT,989.9,491.4>>"835 ]836 },837 {838 "Q": "Where on the road is the black car that is to the front right of the ego vehicle(<c223<CAM_FRONT_RIGHT,1181.8,1470.0><CAM_BACK_RIGHT,-1295.0,1146.6><CAM_FRONT,1752.4,705.8>>) located?",839 "A": "The black car that is to the front right of the ego vehicle(<c223<CAM_FRONT_RIGHT,1181.8,1470.0><CAM_BACK_RIGHT,-1295.0,1146.6><CAM_FRONT,1752.4,705.8>>) is on the same road stops in the same direction. It is one lane to the right of the ego vehicle.",840 "C": null,841 "qid": 20,842 "con_up": [843 [844 4,845 1846 ],847 [848 4,849 2850 ],851 [852 4,853 3854 ]855 ],856 "con_down": [857 [858 3,859 0860 ],861 [862 3,863 2864 ],865 [866 3,867 3868 ]869 ],870 "cluster": 4,871 "layer": 0,872 "object_tags": [873 "<c223<CAM_FRONT_RIGHT,1181.8,1470.0><CAM_BACK_RIGHT,-1295.0,1146.6><CAM_FRONT,1752.4,705.8>>"874 ]875 },876 {877 "Q": "Where on the road is the maroon SUV that is to the front right of the ego vehicle(<c224<CAM_FRONT,1155.0,520.1><CAM_FRONT_RIGHT,-224.2,543.6>>) located?",878 "A": "The maroon SUV that is to the front right of the ego vehicle(<c224<CAM_FRONT,1155.0,520.1><CAM_FRONT_RIGHT,-224.2,543.6>>) is on the same road stops in the same direction. It is one lane to the right of the ego vehicle.",879 "C": null,880 "qid": 20,881 "con_up": [882 [883 4,884 1885 ],886 [887 4,888 2889 ],890 [891 4,892 3893 ]894 ],895 "con_down": [896 [897 3,898 0899 ],900 [901 3,902 2903 ],904 [905 3,906 3907 ]908 ],909 "cluster": 4,910 "layer": 0,911 "object_tags": [912 "<c224<CAM_FRONT,1155.0,520.1><CAM_FRONT_RIGHT,-224.2,543.6>>"913 ]914 },915 {916 "Q": "Where on the road is the black police car that is to the front right of the ego vehicle(<c225<CAM_FRONT,989.9,491.4>>) located?",917 "A": "The black police car that is to the front right of the ego vehicle(<c225<CAM_FRONT,989.9,491.4>>) is on the same road stops in the same direction. It is one lane to the right of the ego vehicle.",918 "C": null,919 "qid": 20,920 "con_up": [921 [922 4,923 1924 ],925 [926 4,927 2928 ],929 [930 4,931 3932 ]933 ],934 "con_down": [935 [936 3,937 0938 ],939 [940 3,941 2942 ],943 [944 3,945 3946 ]947 ],948 "cluster": 4,949 "layer": 0,950 "object_tags": [951 "<c225<CAM_FRONT,989.9,491.4>>"952 ]953 },954 {955 "Q": "What are the important vehicles in the scene and where on the road are they located? List them from most to least important.",956 "A": "The black car that is to the front right of the ego vehicle(<c223<CAM_FRONT_RIGHT,1181.8,1470.0><CAM_BACK_RIGHT,-1295.0,1146.6><CAM_FRONT,1752.4,705.8>>), which is on the same road stops in the same direction. It is one lane to the right of the ego vehicle. The maroon SUV that is to the front right of the ego vehicle(<c224<CAM_FRONT,1155.0,520.1><CAM_FRONT_RIGHT,-224.2,543.6>>), which is on the same road stops in the same direction. It is one lane to the right of the ego vehicle. The black police car that is to the front right of the ego vehicle(<c225<CAM_FRONT,989.9,491.4>>), which is on the same road stops in the same direction. It is one lane to the right of the ego vehicle.",957 "C": null,958 "qid": 26,959 "con_up": [960 [961 4,962 3963 ]964 ],965 "con_down": [966 [967 4,968 0969 ]970 ],971 "cluster": 4,972 "layer": 1,973 "object_tags": [974 "<c223<CAM_FRONT_RIGHT,1181.8,1470.0><CAM_BACK_RIGHT,-1295.0,1146.6><CAM_FRONT,1752.4,705.8>>",975 "<c224<CAM_FRONT,1155.0,520.1><CAM_FRONT_RIGHT,-224.2,543.6>>",976 "<c225<CAM_FRONT,989.9,491.4>>"977 ]978 },979 {980 "Q": "The list of important vehicles in the current scene is 'the black car that is to the front right of the ego vehicle(<c223<CAM_FRONT_RIGHT,1181.8,1470.0><CAM_BACK_RIGHT,-1295.0,1146.6><CAM_FRONT,1752.4,705.8>>), the maroon SUV that is to the front right of the ego vehicle(<c224<CAM_FRONT,1155.0,520.1><CAM_FRONT_RIGHT,-224.2,543.6>>), the black police car that is to the front right of the ego vehicle(<c225<CAM_FRONT,989.9,491.4>>).' Where on the road are they located?",981 "A": "The black car that is to the front right of the ego vehicle(<c223<CAM_FRONT_RIGHT,1181.8,1470.0><CAM_BACK_RIGHT,-1295.0,1146.6><CAM_FRONT,1752.4,705.8>>) is on the same road stops in the same direction. It is one lane to the right of the ego vehicle. The maroon SUV that is to the front right of the ego vehicle(<c224<CAM_FRONT,1155.0,520.1><CAM_FRONT_RIGHT,-224.2,543.6>>) is on the same road stops in the same direction. It is one lane to the right of the ego vehicle. The black police car that is to the front right of the ego vehicle(<c225<CAM_FRONT,989.9,491.4>>) is on the same road stops in the same direction. It is one lane to the right of the ego vehicle.",982 "C": null,983 "qid": 27,984 "con_up": [985 [986 4,987 3988 ]989 ],990 "con_down": [991 [992 4,993 0994 ]995 ],996 "cluster": 4,997 "layer": 1,998 "object_tags": [999 "<c223<CAM_FRONT_RIGHT,1181.8,1470.0><CAM_BACK_RIGHT,-1295.0,1146.6><CAM_FRONT,1752.4,705.8>>",1000 "<c224<CAM_FRONT,1155.0,520.1><CAM_FRONT_RIGHT,-224.2,543.6>>",1001 "<c225<CAM_FRONT,989.9,491.4>>"1002 ]1003 },1004 {1005 "Q": "Is the ego vehicle at a junction?",1006 "A": "No, the ego vehicle is not at a junction.",1007 "C": null,1008 "qid": 35,1009 "con_up": [1010 [1011 1,1012 01013 ],1014 [1015 2,1016 01017 ],1018 [1019 3,1020 11021 ],1022 [1023 3,1024 21025 ],1026 [1027 3,1028 31029 ],1030 [1031 4,1032 01033 ]1034 ],1035 "con_down": -1,1036 "cluster": 3,1037 "layer": 0,1038 "object_tags": []1039 },1040 {1041 "Q": "How many lanes are there in the same direction as the ego car?",1042 "A": "There are two lanes in the same direction.",1043 "C": null,1044 "qid": 34,1045 "con_up": [1046 [1047 3,1048 11049 ],1050 [1051 3,1052 31053 ],1054 [1055 3,1056 41057 ],1058 [1059 3,1060 51061 ],1062 [1063 3,1064 61065 ],1066 [1067 3,1068 71069 ],1070 [1071 4,1072 01073 ]1074 ],1075 "con_down": [1076 [1077 3,1078 01079 ]1080 ],1081 "cluster": 3,1082 "layer": 2,1083 "object_tags": []1084 },1085 {1086 "Q": "How many lanes are there in the opposite direction to the ego car?",1087 "A": "There are no lanes in the opposite direction.",1088 "C": null,1089 "qid": 34,1090 "con_up": [1091 [1092 3,1093 11094 ],1095 [1096 3,1097 31098 ],1099 [1100 3,1101 41102 ],1103 [1104 3,1105 51106 ],1107 [1108 3,1109 61110 ],1111 [1112 3,1113 71114 ],1115 [1116 4,1117 01118 ]1119 ],1120 "con_down": [1121 [1122 3,1123 01124 ]1125 ],1126 "cluster": 3,1127 "layer": 2,1128 "object_tags": []1129 },1130 {1131 "Q": "On which lane is the ego vehicle (left most lane of the lanes going in the same direction is indicated with 0)?",1132 "A": "The ego vehicle is on lane 0.",1133 "C": null,1134 "qid": 33,1135 "con_up": [1136 [1137 3,1138 11139 ],1140 [1141 3,1142 41143 ],1144 [1145 3,1146 51147 ],1148 [1149 3,1150 61151 ],1152 [1153 4,1154 01155 ]1156 ],1157 "con_down": [1158 [1159 3,1160 01161 ]1162 ],1163 "cluster": 3,1164 "layer": 3,1165 "object_tags": []1166 },1167 {1168 "Q": "What lane marking is on the left side of the ego car?",1169 "A": "There is no lane marking on the left side of the ego car.",1170 "C": null,1171 "qid": 32,1172 "con_up": [1173 [1174 3,1175 51176 ],1177 [1178 3,1179 61180 ]1181 ],1182 "con_down": [1183 [1184 3,1185 21186 ],1187 [1188 3,1189 31190 ]1191 ],1192 "cluster": 3,1193 "layer": 4,1194 "object_tags": []1195 },1196 {1197 "Q": "What lane marking is on the right side of the ego car?",1198 "A": "The lane marking on the right side of the ego car is a white broken lane.",1199 "C": null,1200 "qid": 32,