{"list":"other","total":73,"rows":[{"id":"2303.08774","title":"GPT-4 Technical Report","created":"2023-03-15","cited_by_count":18396},{"id":"1903.11027","title":"nuScenes: A multimodal dataset for autonomous driving","created":"2019-03-26","cited_by_count":4523},{"id":"1912.04838","title":"Scalability in Perception for Autonomous Driving: Waymo Open Dataset","created":"2019-12-10","cited_by_count":2451},{"id":"1711.03938","title":"CARLA: An Open Urban Driving Simulator","created":"2017-11-10","cited_by_count":2449},{"id":"1606.01540","title":"OpenAI Gym","created":"2016-06-05","cited_by_count":1736},{"id":"1911.02620","title":"Argoverse: 3D Tracking and Forecasting with Rich Maps","created":"2019-11-06","cited_by_count":732},{"id":"2301.00493","title":"Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting","created":"2023-01-02","cited_by_count":707},{"id":"1705.05065","title":"AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles","created":"2017-05-15","cited_by_count":523},{"id":"2106.11810","title":"NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles","created":"2021-06-22","cited_by_count":493},{"id":"2109.12674","title":"MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning","created":"2021-09-26","cited_by_count":290},{"id":"1810.05642","title":"The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems","created":"2018-10-11","cited_by_count":277},{"id":"2006.14480","title":"One Thousand and One Hours: Self-driving Motion Prediction Dataset","created":"2020-06-25","cited_by_count":240},{"id":"1910.03088","title":"INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps","created":"2019-09-30","cited_by_count":231},{"id":"2306.03083","title":"MotionDiffuser: Controllable Multi-Agent Motion Prediction using Diffusion","created":"2023-06-05","cited_by_count":213},{"id":"2101.06557","title":"TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors","created":"2021-01-17","cited_by_count":193},{"id":"2210.17366","title":"Guided Conditional Diffusion for Controllable Traffic Simulation","created":"2022-10-31","cited_by_count":190},{"id":"2310.08710","title":"Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research","created":"2023-10-12","cited_by_count":160},{"id":"1911.07602","title":"The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections","created":"2019-11-18","cited_by_count":137},{"id":"2306.06344","title":"Language-Guided Traffic Simulation via Scene-Level Diffusion","created":"2023-06-10","cited_by_count":111},{"id":"2210.06609","title":"TrafficGen: Learning to Generate Diverse and Realistic Traffic Scenarios","created":"2022-10-12","cited_by_count":106},{"id":"2403.04133","title":"Towards learning-based planning:The nuPlan benchmark for real-world autonomous driving","created":"2024-03-07","cited_by_count":104},{"id":"2107.07455","title":"Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks","created":"2021-07-15","cited_by_count":101},{"id":"2204.13683","title":"KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients","created":"2022-04-28","cited_by_count":96},{"id":"2405.14062","title":"ChatScene: Knowledge-Enabled Safety-Critical Scenario Generation for Autonomous Vehicles","created":"2024-05-22","cited_by_count":93},{"id":"2402.05746","title":"Editable Scene Simulation for Autonomous Driving via Collaborative LLM-Agents","created":"2024-02-08","cited_by_count":91},{"id":"2307.07947","title":"Language Conditioned Traffic Generation","created":"2023-07-16","cited_by_count":87},{"id":"2305.12032","title":"The Waymo Open Sim Agents Challenge","created":"2023-05-19","cited_by_count":86},{"id":"2101.06541","title":"SceneGen: Learning to Generate Realistic Traffic Scenes","created":"2021-01-16","cited_by_count":84},{"id":"2111.12083","title":"VISTA 2.0: An Open, Data-driven Simulator for Multimodal Sensing and Policy Learning for Autonomous Vehicles","created":"2021-11-23","cited_by_count":81},{"id":"2208.12403","title":"BITS: Bi-level Imitation for Traffic Simulation","created":"2022-08-26","cited_by_count":80},{"id":"2105.12332","title":"SimNet: Learning Reactive Self-driving Simulations from Real-world Observations","created":"2021-05-26","cited_by_count":77},{"id":"1902.01909","title":"Adaptive Stress Testing for Autonomous Vehicles","created":"2019-02-05","cited_by_count":71},{"id":"2205.03195","title":"Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation","created":"2022-05-06","cited_by_count":61},{"id":"2312.04535","title":"Trajeglish: Traffic Modeling as Next-Token Prediction","created":"2023-12-07","cited_by_count":60},{"id":"2206.09889","title":"Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world","created":"2022-06-20","cited_by_count":56},{"id":"2303.04116","title":"TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction","created":"2023-03-07","cited_by_count":56},{"id":"1911.04175","title":"Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learning","created":"2019-11-11","cited_by_count":53},{"id":"1803.01044","title":"Multi-Agent Imitation Learning for Driving Simulation","created":"2018-03-02","cited_by_count":50},{"id":"2209.08744","title":"AdvDO: Realistic Adversarial Attacks for Trajectory Prediction","created":"2022-09-19","cited_by_count":49},{"id":"2312.13303","title":"RealGen: Retrieval Augmented Generation for Controllable Traffic Scenarios","created":"2023-12-19","cited_by_count":46},{"id":"2006.06412","title":"Modeling Human Driving Behavior through Generative Adversarial Imitation Learning","created":"2020-06-10","cited_by_count":45},{"id":"2004.06531","title":"Adversarial Evaluation of Autonomous Vehicles in Lane-Change Scenarios","created":"2020-04-14","cited_by_count":43},{"id":"1911.04074","title":"SUMMIT: A Simulator for Urban Driving in Massive Mixed Traffic","created":"2019-11-11","cited_by_count":40},{"id":"1903.10654","title":"Failure-Scenario Maker for Rule-Based Agent using Multi-agent Adversarial Reinforcement Learning and its Application to Autonomous Driving","created":"2019-03-26","cited_by_count":36},{"id":"2409.09040","title":"ChatSUMO: Large Language Model for Automating Traffic Scenario Generation in Simulation of Urban MObility","created":"2024-08-29","cited_by_count":34},{"id":"2402.01246","title":"LimSim++: A Closed-Loop Platform for Deploying Multimodal LLMs in Autonomous Driving","created":"2024-02-02","cited_by_count":33},{"id":"1708.05869","title":"Sim4CV: A Photo-Realistic Simulator for Computer Vision Applications","created":"2017-08-19","cited_by_count":31},{"id":"2007.08463","title":"openDD: A Large-Scale Roundabout Drone Dataset","created":"2020-07-16","cited_by_count":29},{"id":"2310.15975","title":"Data-driven Traffic Simulation: A Comprehensive Review","created":"2023-10-24","cited_by_count":29},{"id":"2210.14413","title":"InterSim: Interactive Traffic Simulation via Explicit Relation Modeling","created":"2022-10-26","cited_by_count":27},{"id":"2403.19918","title":"CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning","created":"2024-03-29","cited_by_count":27},{"id":"2103.11575","title":"Learn-to-Race: A Multimodal Control Environment for Autonomous Racing","created":"2021-03-22","cited_by_count":23},{"id":"2111.06889","title":"DriverGym: Democratising Reinforcement Learning for Autonomous Driving","created":"2021-11-12","cited_by_count":23},{"id":"2203.16792","title":"TrajGen: Generating Realistic and Diverse Trajectories with Reactive and Feasible Agent Behaviors for Autonomous Driving","created":"2022-03-31","cited_by_count":23},{"id":"2003.02604","title":"BARK: Open Behavior Benchmarking in Multi-Agent Environments","created":"2020-03-05","cited_by_count":21},{"id":"2309.00709","title":"Reinforcement Learning with Human Feedback for Realistic Traffic Simulation","created":"2023-09-01","cited_by_count":21},{"id":"2409.05863","title":"Promptable Closed-loop Traffic Simulation","created":"2024-09-09","cited_by_count":20},{"id":"2405.15388","title":"Language-Driven Interactive Traffic Trajectory Generation","created":"2024-05-24","cited_by_count":19},{"id":"2409.06450","title":"Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles","created":"2024-09-10","cited_by_count":18},{"id":"2403.19648","title":"Human-compatible driving partners through data-regularized self-play reinforcement learning","created":"2024-03-28","cited_by_count":17},{"id":"2010.00993","title":"MADRaS : Multi Agent Driving Simulator","created":"2020-10-02","cited_by_count":15},{"id":"2011.03748","title":"B-GAP: Behavior-Rich Simulation and Navigation for Autonomous Driving","created":"2020-11-07","cited_by_count":15},{"id":"2103.00906","title":"Diverse Critical Interaction Generation for Planning and Planner Evaluation","created":"2021-03-01","cited_by_count":15},{"id":"2011.05741","title":"Behaviorally Diverse Traffic Simulation via Reinforcement Learning","created":"2020-11-11","cited_by_count":11},{"id":"2112.00298","title":"Exploring Social Posterior Collapse in Variational Autoencoder for Interaction Modeling","created":"2021-12-01","cited_by_count":11},{"id":"2203.01261","title":"TAE: A Semi-supervised Controllable Behavior-aware Trajectory Generator and Predictor","created":"2022-03-02","cited_by_count":10},{"id":"2406.03870","title":"GOOSE: Goal-Conditioned Reinforcement Learning for Safety-Critical Scenario Generation","created":"2024-06-06","cited_by_count":10},{"id":"2012.11329","title":"CARLA Real Traffic Scenarios -- novel training ground and benchmark for autonomous driving","created":"2020-12-16","cited_by_count":8},{"id":"2211.03408","title":"RITA: Boost Driving Simulators with Realistic Interactive Traffic Flow","created":"2022-11-07","cited_by_count":7},{"id":"2405.04491","title":"TorchDriveEnv: A Reinforcement Learning Benchmark for Autonomous Driving with Reactive, Realistic, and Diverse Non-Playable Characters","created":"2024-05-07","cited_by_count":6},{"id":"2208.04559","title":"Analyzing and Enhancing Closed-loop Stability in Reactive Simulation","created":"2022-08-09","cited_by_count":4},{"id":"2102.06588","title":"A taxonomy for quality in simulation-based development and testing of automated driving systems","created":"2021-02-12","cited_by_count":3},{"id":"2306.06401","title":"Long-term Microscopic Traffic Simulation with History-Masked Multi-agent Imitation Learning","created":"2023-06-10","cited_by_count":3}],"next_cursor":null}