Intelligent Vehicle Simulation and Debugging Environment Based on Physics Engine

Luo, Feng; Chu, Liu; Sun, Zhonghui

doi:10.1109/car.2009.38

Cited by 10 publications

(3 citation statements)

References 2 publications

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“…However, these 2D contact-impact models between car bodies have limitations and may not be applicable in all scenarios. In 3D contact-impact models between car bodies, the automatic-surface-to-surface contact method is frequently adopted to detect and calculate the contact force in FE simulation [27,[51][52][53][54][55]. The nonlinear elastic-plastic spring force element provided by most commercial MBS software has been used to model the contact-impact between vehicle bodies [56][57][58].…”

Section: Typical Post-derailment Contact-impact Models 2421 Contact-i...mentioning

confidence: 99%

“…Therefore, it is worth exploring new methods that can achieve high computational efficiency as well as a reasonable level of accuracy. The physics engine can approximately simulate the dynamic behaviours of objects in the real world based on physical principles, which have been successfully applied in the field of virtual reality, mechanical simulations, vehicle dynamics [52], and other sectors. More notably, the collision detection algorithms, which have already been successfully used in the simulation of post-derailment behaviour [21], and the real-time rigid body simulation framework in the physics engine, are suitable for rapidly constructing and simulating the large-scale post-derailment model of a train set.…”

Section: Post-derailment Behaviour Modellingmentioning

confidence: 99%

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Train post-derailment behaviours and containment methods: a review

Zhao

Wang

et al. 2023

Rail. Eng. Science

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Railway accidents, particularly serious derailments, can lead to catastrophic consequences. Therefore, it is essential to prevent derailment escalation to reduce the likelihood of severe derailments. Train post-derailment behaviours and containment methods play a critical role in preventing derailment escalation and providing passive safety protection and accident prevention in the event of a derailment. However, despite the increasing attention on this field from academia and industry in recent years, there is a lack of systematic exploration and summarization of emerging applications and containment methods in train post-derailment research. For this reason, this paper presents a comprehensive review of existing studies on train post-derailment behaviours, encompassing various topics such as post-derailment contact–impact models, dynamic modelling and simulation techniques, and the primary factors influencing post-derailment behaviours. Significantly, this review introduces and elucidates substitute guidance mechanisms (SGMs), which serve as railway-specific passive safety protection and accident prevention measures. The various types of SGMs are depicted, and their ongoing developments and applications are explored in depth. The review additionally points out several unresolved challenges including the adverse effects of SGMs, and proposes future research directions to advance the theoretical understanding and practical application of train post-derailment behaviours and containment methods. This review seeks to be a valuable reference for railway industry professionals in preventing catastrophic derailment consequences through post-derailment containment methods.

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Section: Typical Post-derailment Contact-impact Models 2421 Contact-i...mentioning

confidence: 99%

Section: Post-derailment Behaviour Modellingmentioning

confidence: 99%

Train post-derailment behaviours and containment methods: a review

Zhao

Wang

et al. 2023

Rail. Eng. Science

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“…To simplify the optimization problem, we assume Len has been restrict to 11, so the optimization problem can be described as followed: The result shown in the figure 13 is from a simulation environment (figure 12) developed in the reference [8], which delivers an exciting message that 1193 data are compressed into a 26*2 data group with a compression ratio as high as 22.3. Despite a high sampling density rare sharp data burrs escaping from the filter (IIR e.g.)…”

Section: Outcome Analysismentioning

confidence: 99%

Route memorization in real-time data processing using Run-Length Encoding

Luo

Huang

Yan

et al. 2009

2009 IEEE Intelligent Vehicles Symposium

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A real-time data processing algorithm based on Run-Length Encoding (RLE) for an intelligent racing vehicle is introduced in this paper. In order to improve the achievement of the intelligent racing vehicle's running in the second loop by recoding route information, a new method based on RLE is provided by setting an optimal calculus threshold. Simulated by Matlab/Simulink, the route memorization algorithm shows the obvious advantage in the data compression, which makes the compression ratio up to 22.3. In the meantime, the calculus threshold can be constructed in a certain range, which qualifies the algorithm with a good robustness. Compared with the optimal results achieved by Matlab's genetic algorithm and direct search toolbox, the RLE algorithm can satisfy the requirements very well. When the embedded system has to face the flood for the data increasing geometrically, this highquality real-time algorithm has been demonstrated with great practical potential.

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