A New Linear Platoon Model Based on Reactive Multi-agent Systems

El-Zaher, Madeleine; Gechter, Franck; Gruer, Pablo; Hajjar, Mohammad

doi:10.1109/ictai.2011.146

Cited by 17 publications

(3 citation statements)

References 3 publications

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“…In our platoon driving scenario, multiple intelligent heavy-duty trucks complete unified transportation tasks via communication. The platoon composed of these trucks can be regarded as a multi-agent system [8] . These trucks are equipped with a 5G-based intelligent truck system developed by SAIC Motor.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Agent Spatial Logic for Scenario-Based Decision Modeling and Verification in Platoon Systems

Huang

Shi

et al. 2021

J. Comput. Sci. Technol.

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To cater for the scenario of coordinated transportation of multiple trucks on the highway, a platoon system for autonomous driving has been extensively explored in the industry. Before such a platoon is deployed, it is necessary to ensure the safety of its driving behavior, whereby each vehicle's behavior is commanded by the decision-making function whose decision is based on the observed driving scenario. However, there is currently a lack of verification methods to ensure the reliability of the scenario-based decision-making process in the platoon system. In this paper, we focus on the platoon driving scenario, whereby the platoon is composed of intelligent heavy trucks driving on cross-sea highways. We propose a formal modeling and verification approach to provide safety assurance for platoon vehicles' cooperative driving behaviors. The existing Multi-Lane Spatial Logic (MLSL) with a dedicated abstract model can express driving scene spatial properties and prove the safety of multi-lane traffic maneuvers under the single-vehicle perspective. To cater for the platoon system's multi-vehicle perspective, we modify the existing abstract model and propose a Multi-Agent Spatial Logic (MASL) that extends MLSL by relative orientation and multi-agent observation. We then utilize a timed automata type supporting MASL formulas to model vehicles' decision controllers for platoon driving. Taking the behavior of a human-driven vehicle (HDV) joining the platoon as a case study, we have implemented the model and verified safety properties on the UPPAAL tool to illustrate the viability of our framework.

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Section: Introductionmentioning

confidence: 99%

A Multi-Agent Spatial Logic for Scenario-Based Decision Modeling and Verification in Platoon Systems

Huang

Shi

et al. 2021

J. Comput. Sci. Technol.

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“…They can be applied to a wide range of applications thanks to their intrinsic properties and features such as simplicity, flexibility, reliability, self-organization/emergent phenomena, low cost agent design and adaptation capacity. It has been shown that reactive multi-agent system are efficient to tackle complex problems [14], cooperation of situated agents/robots [15], data fusion and problem/game-solving [13]. In this context, our proposal consists in decision making by evaluating emergent properties of agent's organization.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Autonomous Navigation using Reactive Multi-agent System for Control Law Merging

Dafflon¹,

Vilca²,

Gechter³

et al. 2015

Procedia Computer Science

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International audienceThis paper deals with intelligent autonomous navigation of a vehicle in cluttered environment. We present a control architecture for safe and smooth navigation of a Unmanned Ground Vehicles (UGV). This control architecture is designed to allow the use of a single control law for different vehicle contexts (attraction to the target, obstacle avoidance, etc.) [4]. The reactive obstacle avoidance strategy is based on the limit-cycle approach [2]. To manage the interaction between the controllers according to the context, the multi-agent system is proposed. Multi-agent systems are an efficient approach for problem solving and decision making. They can be applied to a wide range of applications thanks to their intrinsic properties such as self-organization/emergent phenomena. Merging approach between control laws is based on their properties to adapt the control to the environment. Different simulations on cluttered environments show the performance and the efficiency of our proposal, to obtain fully reactive and safe control strategy, for the navigation of a UGV

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“…In platooning systems Research such as in [2,3], each vehicle determines its own position and orientation only from its perceptions of the surrounded environment. In this context, the reactive multi-agent paradigm is well adapted to specify and analyze this system.…”

Section: Introductionmentioning

confidence: 99%

Towards to an Agent-Oriented Modeling and Evaluating Approach for Vehicular Systems Security

Garoui¹,

Mazigh²,

Ayeb³

et al. 2014

IJITMC

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Agent technology is a software paradigm that permits to implement large and complex distributed applications. In order to assist the development of multi-agent systems, agent-oriented methodologies (AOM) have been created in the last years to support modeling more and more complex applications in many different domains. By defining in a non-ambiguous way concepts used in a specific domain, Meta modeling may represent a step towards such interoperability. In the Transport domain, this paper propose an agent-oriented meta-model that provides rigorous concepts for conducting transportation system problem modeling. The aim is to allow analysts to produce a transportation system model that precisely captures the knowledge of an organization so that an agent-oriented requirements specification of the system-to-be and its operational corporate environment can be derived from it. To this end, we extend and adapt an existing meta-model, Extended Gaia, to build a meta-model and an adequate model for transportation problems. Our new agent-oriented meta-model aims to allow the analyst to model and specify any transportation system as a multi-agent system. Based on the proposed meta-model, we proposes an approach for modeling and evaluating the Transportation System based on Stochastic Activity Network (SAN) components. The proposed process is based on seven steps from "Recognition" phase to "Quantitative Analysis" phase. These analyzes are based on the Dependability models which are built using the formalism Stochastic Activity Network. A real case study of Urban Public Transportation System has been conducted to show the benefits of the approach.

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A New Linear Platoon Model Based on Reactive Multi-agent Systems

Cited by 17 publications

References 3 publications

A Multi-Agent Spatial Logic for Scenario-Based Decision Modeling and Verification in Platoon Systems

A Multi-Agent Spatial Logic for Scenario-Based Decision Modeling and Verification in Platoon Systems

Adaptive Autonomous Navigation using Reactive Multi-agent System for Control Law Merging

Towards to an Agent-Oriented Modeling and Evaluating Approach for Vehicular Systems Security

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