Fault-Tolerant Cooperative Motion Planning of Connected and Automated Vehicles at a Signal-Free and Lane-Free Intersection

Bai, Li; Zhang, Youmin

doi:10.1016/j.ifacol.2018.09.529

Cited by 24 publications

(10 citation statements)

References 23 publications

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“…It has proven its efficiency in both fault excitation and fault mitigation in an autonomous system, such as the electrical power train of an autonomous vehicle. In the same area of interest, connected vehicles represent the future of automotive, and work [ 20 ] proposes a fault-tolerant cooperative motion planning method for a cloud of connected vehicles designed to a more flexible driving, thereby promoting the throughput to reducing congestions. The solution relies on a parallel computation framework, which enables to keep solving the original goals as much as possible when faults have partially degraded the vehicle cloud’s work capability.…”

Section: Related Workmentioning

confidence: 99%

Intelligent Network Applications Monitoring and Diagnosis Employing Software Sensing and Machine Learning Solutions

Minea

Dumitrescu

Minea³

2021

Sensors

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The article presents a research in the field of complex sensing, detection, and recovery of communications networks applications and hardware, in case of failures, maloperations, or unauthorized intrusions. A case study, based on Davis AI engine operation versus human maintenance operation is performed on the efficiency of artificial intelligence agents in detecting faulty operation, in the context of growing complexity of communications networks, and the perspective of future development of internet of things, big data, smart cities, and connected vehicles. (*). In the second part of the article, a new solution is proposed for the detection of applications faults or unauthorized intrusions in traffic of communications networks. The first objective of the proposed method is to propose an approach for predicting time series. This approach is based on a multi-resolution decomposition of the signals employing the undecimate wavelet transform (UWT). The second approach for assessing traffic flow is based on the analysis of long-range dependence (LRD) (for this case, a long-term dependence). Estimating the degree of long-range dependence is performed by estimating the Hurst parameter of the analyzed time series. This is a relatively new statistical concept in communications traffic analysis and can be implemented using UWT. This property has important implications for network performance, design, and sizing. The presence of long-range dependency in network traffic is assumed to have a significant impact on network performance, and the occurrence of LRD can be the result of faults that occur during certain periods. The strategy chosen for this purpose is based on long-term dependence on traffic, and for the prediction of faults occurrence, a predictive control model (MPC) is proposed, combined with a neural network with radial function (RBF). It is demonstrated via simulations that, in the case of communications traffic, time location is the most important feature of the proposed algorithm.

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Section: Related Workmentioning

confidence: 99%

Intelligent Network Applications Monitoring and Diagnosis Employing Software Sensing and Machine Learning Solutions

Minea

Dumitrescu

Minea³

2021

Sensors

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“…Current research activities concerning AGV control aim at further improving the path following capabilities, for instance a robust H ∞ output-feedback control strategy is refined and applied in [ 3 ]. Another central issue in AGV control is the motion planning; several researchers worldwide address this issue [ 4 , 5 ]. Several research groups look into navigation tasks and self-orientation, such as simultaneous localization and mapping (SLAM) [ 6 , 7 , 8 , 9 ].…”

Section: State Of the Artmentioning

confidence: 99%

A Fuzzy Virtual Actuator for Automated Guided Vehicles

Stetter

2020

Sensors

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In the last decades, virtual sensors have found increasing attention in the research community. Virtual sensors employ mathematical models and different sources of information such as actuator states or sensors, which are already existing in a system, in order to generate virtual measurements. Additionally, in recent years, the concept of virtual actuators has been proposed by leading researchers. Virtual actuators are parts of a fault-tolerant control strategy and aim to accommodate faults and to achieve a safe operation of a faulty plant. This paper describes a novel concept for a fuzzy virtual actuator applied to an automated guided vehicle (AGV). The application of fuzzy logic rules allows integrating expert knowledge or experimental data into the decision making of the virtual actuator. The AGV under consideration disposes of an innovative steering concept, which leads to considerable advantages in terms of maneuverability, but requires an elaborate control system. The application of the virtual actuator allows the accommodation of several possible faults, such as a slippery surface under one of the drive modules of the AGV.

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“…The system-optimal policy is the second most-used priority policy where the crossing sequence is determined based on system-level performance measures, such as overall delay, throughput, travel time, etc. 12 Carlino et al [28] 12 Bashiri and Fleming [21] n/a Bashiri et al [29] 12 Jiang et al [30] n/a Kamal et al [12] 12 Carlson [25] 2 Levin and Rey [31] 12 Zohdy et al [19] 4 Du et al [32] 2 Ding et al [15] 12 Bashiri et al [33] 12 Li et al [13] unlimited Jin et al [26] 2 Mirheli et al [34] 8 Li and Zhang [35] unlimited Wuthishuwong et al [36] 12 Liu et al [17] 12 Zohdy and Hakha [18] 12 Zhao et al [37] 12 Hassan and Hakha [38] 4 Stone et al [39] 12 Fayazi et al [22] 4 Lam and Katupitiya [24] 2 Creemers et al [40] 5 Other priority policies have been reported, such as longestqueue-first policy [41], vehicle type-based policy [42], custom priority score-based policy [17], and auction-based policy [28]. Table III lists the major AIM study with regard to the coverage of the three-layer intersection management structure.…”

Section: B Priority Policymentioning

confidence: 99%

“…8 displays the simulated vehicles and the number of turning movements for an intersection among the reviewed studies. The vehicle-based (VB) AIM [13,35] is not shown, as it theoretically has an infinite number of turning movements. Due to the nature of the intersection-based (IB) reservation (occupancy of an entire intersection), the simulated movements did not excess 4 in the previous studies.…”

Section: A Simulation Scalementioning

confidence: 99%

Autonomous and Semi-Autonomous Intersection Management: A Survey

Zhong,

Nejad,

Lee

2020

Preprint

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Intersection is a major source of traffic delays and accidents within modern transportation systems. Compared to signalized intersection management, autonomous intersection management (AIM) coordinates the intersection crossing at an individual vehicle level with additional flexibility. AIM can potentially eliminate stopping in intersection crossing due to traffic lights while maintaining a safe separation among conflicting movements. In this paper, the state-of-the-art AIM research among various disciplines (e.g., traffic engineering, control engineering) is surveyed from the perspective of three hierarchical layers: corridor coordination layer, intersection management layer, and vehicle control layer. The key aspects of AIM designs are discussed in details, including conflict detection schemes, priority rules, control centralization, computation complexity, etc. The potential improvements for AIM evaluation with the emphasis of realistic scenarios are provided. This survey serves as a comprehensive review of AIM design and provides promising directions for future research.

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Fault-Tolerant Cooperative Motion Planning of Connected and Automated Vehicles at a Signal-Free and Lane-Free Intersection

Cited by 24 publications

References 23 publications

Intelligent Network Applications Monitoring and Diagnosis Employing Software Sensing and Machine Learning Solutions

Intelligent Network Applications Monitoring and Diagnosis Employing Software Sensing and Machine Learning Solutions

A Fuzzy Virtual Actuator for Automated Guided Vehicles

Autonomous and Semi-Autonomous Intersection Management: A Survey

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