DeepScenario: An Open Driving Scenario Dataset for Autonomous Driving System Testing
With the rapid development of autonomous driving systems (ADSs), testing ADSs under various environmental conditions has become a key method to ensure the successful deployment of ADS in the real world. However, it is impossible to test all the scenarios due to the inherent complexity and uncertainty of ADSs and the driving tasks. Further, testing of ADSs is expensive regarding time and computational resources. Therefore, a large-scale driving scenario dataset consisting of various driving conditions is needed. To this end, we present an open driving scenario dataset $\mathrm{DeepScenario}$, containing over 30\textit{K} \textit{executable} driving scenarios, which are collected by 2880 test executions of three driving scenario generation strategies. Each scenario in the dataset is labeled with six attributes characterizing test results. We further show the attribute statistics and distribution of driving scenarios. For example, there are 1050 collision scenarios, in 917 scenarios there were collisions with other vehicles, 105 and 28 with pedestrians and static obstacles, respectively. Target users include ADS developers who need to validate their systems under various environmental conditions.
Mon 15 MayDisplayed time zone: Hobart change
11:00 - 11:45 | SE for MLData and Tool Showcase Track / Technical Papers at Meeting Room 110 Chair(s): Sarah Nadi University of Alberta | ||
11:00 12mTalk | AutoML from Software Engineering Perspective: Landscapes and ChallengesDistinguished Paper Award Technical Papers Chao Wang Peking University, Zhenpeng Chen University College London, UK, Minghui Zhou Peking University Pre-print | ||
11:12 12mTalk | Characterizing and Understanding Software Security Vulnerabilities in Machine Learning Libraries Technical Papers Nima Shiri Harzevili York University, Jiho Shin York University, Junjie Wang Institute of Software at Chinese Academy of Sciences; University of Chinese Academy of Sciences, Song Wang York University, Nachiappan Nagappan Facebook | ||
11:24 6mTalk | DeepScenario: An Open Driving Scenario Dataset for Autonomous Driving System Testing Data and Tool Showcase Track Chengjie Lu Simula Research Laboratory and University of Oslo, Tao Yue Simula Research Laboratory, Shaukat Ali Simula Research Laboratory Pre-print | ||
11:30 6mTalk | NICHE: A Curated Dataset of Engineered Machine Learning Projects in Python Data and Tool Showcase Track Ratnadira Widyasari Singapore Management University, Singapore, Zhou Yang Singapore Management University, Ferdian Thung Singapore Management University, Sheng Qin Sim Singapore Management University, Singapore, Fiona Wee Singapore Management University, Singapore, Camellia Lok Singapore Management University, Singapore, Jack Phan Singapore Management University, Singapore, Haodi Qi Singapore Management University, Singapore, Constance Tan Singapore Management University, Singapore, Qijin Tay Singapore Management University, Singapore, David Lo Singapore Management University | ||
11:36 6mTalk | PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages Data and Tool Showcase Track Wenxin Jiang Purdue University, Nicholas Synovic Loyola University Chicago, Purvish Jajal Purdue University, Taylor R. Schorlemmer Purdue University, Arav Tewari Purdue University, Bhavesh Pareek Purdue University, George K. Thiruvathukal Loyola University Chicago and Argonne National Laboratory, James C. Davis Purdue University Pre-print | ||