A Survey on Simulators for Testing Self-Driving Cars

Kaur, Prabhjot; Taghavi, Samira; Tian, Zhaofeng; Shi, Wei

doi:10.48550/arxiv.2101.05337

Cited by 3 publications

(4 citation statements)

References 20 publications

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“…[26] showcases the advanced capabilities of Gazebo where the user defines a prius model of a car moving in a simulated M-City. These realistic simulations are possible in Gazebo because of the three main libraries namely, physics, rendering, and communication libraries [27]. Gazebo is the most popular simulator in the robotic community because it seamlessly integrates with Robotic Operating System (ROS) [28], [29].…”

Section: A Simulators For 3d Environment Robot and Sensor Modellingmentioning

confidence: 99%

Simulators for Mobile Social Robots:State-of-the-Art and Challenges

Kaur¹,

Liu²,

Shi³

2022

Preprint

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The future robots are expected to work in a shared physical space with humans [1], however, the presence of humans leads to a dynamic environment that is challenging for mobile robots to navigate. The path planning algorithms designed to navigate a collision free path in complex human environments are often tested in real environments due to the lack of simulation frameworks. This paper identifies key requirements for an ideal simulator for this task, evaluates existing simulation frameworks and most importantly, it identifies the challenges and limitations of the existing simulation techniques.First and foremost, we recognize that the simulators needed for the purpose of testing mobile robots designed for human environments are unique as they must model realistic pedestrian behavior in addition to the modelling of mobile robots. Our study finds that Pedsim ros [2] and a more recent SocNavBench framework [3] are the only two 3D simulation frameworks that meet most of the key requirements defined in our paper. In summary, we identify the need for developing more simulators that offer an ability to create realistic 3D pedestrian rich virtual environments along with the flexibility of designing complex robots and their sensor models from scratch.

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Section: A Simulators For 3d Environment Robot and Sensor Modellingmentioning

confidence: 99%

Simulators for Mobile Social Robots:State-of-the-Art and Challenges

Kaur¹,

Liu²,

Shi³

2022

Preprint

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“…Study [9] introduces multiple simulation software and frameworks for testing self-driving cars. Also, the comparisons among the simulation software are shown, which gives other researchers guidance on choosing an appropriate simulator for their own research.…”

Section: Background and Motivationmentioning

confidence: 99%

“…For instance, the traditional automotive industry may use simulation to test vehicle dynamics, driving comfort, and fuel economy, which is more related to the vehicle per se. While the autonomous driving industry is interested in sensing the environments with multi-type sensors, behavior planning, and motion planning [9]. In our study, our simulator mainly focuses on autonomous drivingrelated applications like sensing, detection, and navigation.…”

Section: Applicationsmentioning

confidence: 99%

Design and Implement an Enhanced Simulator for Autonomous Delivery Robot

Tian¹,

Shi²

2022

Preprint

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As autonomous driving technology is getting more and more mature today, autonomous delivery companies like Starship, Marble, and Nuro has been making progress in the tests of their autonomous delivery robots. While simulations and simulators are very important for the final product landing of the autonomous delivery robots since the autonomous delivery robots need to navigate on the sidewalk, campus, and other urban scenarios, where the simulations can avoid real damage to pedestrians and properties in the real world caused by any algorithm failures and programming errors and thus accelerate the whole developing procedure and cut down the cost. In this case, this study proposes an open-source simulator based on our autonomous delivery robot ZebraT to accelerate the research on autonomous delivery. The simulator developing procedure is illustrated step by step. What is more, the applications on the simulator that we are working on are also introduced, which includes autonomous navigation in the simulated urban environment, cooperation between an autonomous vehicle and an autonomous delivery robot, and reinforcement learning practice on the task training in the simulator. We have published the proposed simulator in Github.

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“…com/en, https://citycardriving.com] which deliver a good immersive experience to the users at the cost of computing power and with limited number of scenarios. The same is true for simulators oriented to testing self-driving cars [1], as they require accurate representation of the 3D world so that the simulated sensors can get data of the same quality than their real counterparts. This is the first work where simulated traffic environments come from real maps and the simulation is computationally inexpensive, like many of the psychometric driving test tools, with the addition of including the modeling of partially autonomous driving of the vehicle.…”

Section: Introductionmentioning

confidence: 96%

Partially Automated Vehicle Simulation for Studying Driver Distraction in Real Scenarios

Bendahmane,

Ribas-Xirgo

2024

Preprint

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Driver’s distractions are more prone to occur with automated driving vehicles, which might turn into cancelling some of their advantages. Traffic reports, naturalistic observations and in-lab tests are carried out to determine the influence of driver’s distractions in car crashes and to develop technology to detect and prevent them from happening. One of the best strategies to cope with this problem is education. In this work we propose a simulation environment to design laboratory experiments to study driver’s distractions as well as simple games to train drivers to take over the control of the vehicle when required. The result framework enables drivers to experience driving highly automated cars in their neighborhoods or in places of their choice with different levels of events to check their ability in taking over the control when required.

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A Survey on Simulators for Testing Self-Driving Cars

Cited by 3 publications

References 20 publications

Simulators for Mobile Social Robots:State-of-the-Art and Challenges

Simulators for Mobile Social Robots:State-of-the-Art and Challenges

Design and Implement an Enhanced Simulator for Autonomous Delivery Robot

Partially Automated Vehicle Simulation for Studying Driver Distraction in Real Scenarios

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