Force-based Heterogeneous Traffic Simulation for Autonomous Vehicle Testing

Chao, Qianwen; Jin, Xiaogang; Huang, Hen-Wei; Foong, Shaohui; Yu, Lap-Fai; Yeung, Sai-Kit

doi:10.1109/icra.2019.8794430

Cited by 22 publications

(28 citation statements)

References 21 publications

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“…Feliciani et al [71] further evaluated the necessity of introducing a new crosswalk and/or switching to a traffic light. Chao et al [44] developed a microscopic-based traffic simulator based on a force model to represent the behaviour and interactions between the road users, and aimed for autonomous vehicle development and testing. Chen et al [45] proposed a simulation platform composed of several behaviour models at crosswalks for vehicle-pedestrian conflicts assessment.…”

Section: Pedestrian and Driving Simulatorsmentioning

confidence: 99%

Pedestrian Models for Autonomous Driving Part II: High-Level Models of Human Behavior

Camara

Bellotto

Coşar

et al. 2021

IEEE Trans. Intell. Transport. Syst.

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Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles navigating through crowds on pedestrianized high-streets. Unlike static and kinematic obstacles, pedestrians are active agents with complex, interactive motions. Planning AV actions in the presence of pedestrians thus requires modelling of their probable future behaviour as well as detecting and tracking them. This narrative review article is Part II of a pair, together surveying the current technology stack involved in this process, organising recent research into a hierarchical taxonomy ranging from lowlevel image detection to high-level psychological models. This selfcontained Part II covers the higher levels of this stack, consisting of models of pedestrian behaviour, from prediction of individual pedestrians' likely destinations and paths, to game-theoretic models of interactions between pedestrians and autonomous vehicles. This survey clearly shows that, although there are good models for optimal walking behaviour, high-level psychological and social modelling of pedestrian behaviour still remains an open research question that requires many conceptual issues to be clarified. Early work has been done on descriptive and qualitative models of behaviour, but much work is still needed to translate them into quantitative algorithms for practical AV control.

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Section: Pedestrian and Driving Simulatorsmentioning

confidence: 99%

Pedestrian Models for Autonomous Driving Part II: High-Level Models of Human Behavior

Camara

Bellotto

Coşar

et al. 2021

IEEE Trans. Intell. Transport. Syst.

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“…[WSL13], (d) the reconstructed city‐scale traffic using GPS data from Li et al. [LWL17], and (e) a heterogeneous traffic simulation used for autonomous driving testing [CJH*19].…”

Section: Model‐based Traffic Simulationmentioning

confidence: 99%

A Survey on Visual Traffic Simulation: Models, Evaluations, and Applications in Autonomous Driving

Chao

et al. 2019

Computer Graphics Forum

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100

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Virtualized traffic via various simulation models and real‐world traffic data are promising approaches to reconstruct detailed traffic flows. A variety of applications can benefit from the virtual traffic, including, but not limited to, video games, virtual reality, traffic engineering and autonomous driving. In this survey, we provide a comprehensive review on the state‐of‐the‐art techniques for traffic simulation and animation. We start with a discussion on three classes of traffic simulation models applied at different levels of detail. Then, we introduce various data‐driven animation techniques, including existing data collection methods, and the validation and evaluation of simulated traffic flows. Next, we discuss how traffic simulations can benefit the training and testing of autonomous vehicles. Finally, we discuss the current states of traffic simulation and animation and suggest future research directions.

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“…Recently, Chao et al 6 propose a force‐based framework for heterogeneous traffic simulation that encodes the behaviors of pedestrians, bicycles, and vehicles into forces in a unified way. The net force acting on each road user can be classified as the desired force to a target, the repulsive forces from neighbors and the built environment, and the interaction forces between different kinds of road‐users.…”

Section: Introductionmentioning

confidence: 99%

A simplified force model for mixed traffic simulation

Han

Chao

Jin

2020

Computer Animation & Virtual

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We present a simplified force-based heterogeneous traffic simulation model to facilitate consistent adjustment of the parameters involved. Different from previous work which requires the adjustment of multiple ad hoc parameters to produce satisfactory results, our approach can achieve similar results by using clear and meaningful parameters to simulate interactions between various kinds of road users. To simulate diverse and realistic motions of road users, we parameterize the coefficients of the force model for better detailed motion control. Our approach is also scalable to new types of road users, and facilitates an object-oriented implementation with high performance. We validate our framework with extensive experiments.

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Force-based Heterogeneous Traffic Simulation for Autonomous Vehicle Testing

Cited by 22 publications

References 21 publications

Pedestrian Models for Autonomous Driving Part II: High-Level Models of Human Behavior

Pedestrian Models for Autonomous Driving Part II: High-Level Models of Human Behavior

A Survey on Visual Traffic Simulation: Models, Evaluations, and Applications in Autonomous Driving

A simplified force model for mixed traffic simulation

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