Virtual intelligent vehicle urban simulator: Application to vehicle platoon evaluation

Gechter, Franck; Contet, Jean-Michel; Galland, Stéphane; Lamotte, Olivier; Koukam, Abderraf́ıâa

doi:10.1016/j.simpat.2012.02.001

Cited by 31 publications

(9 citation statements)

References 5 publications

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“…In a slightly different domain, VIVUS (Virtual Intelligent Vehicle Urban Simulator) [15] simulates vehicles and sensors, taking into consideration their physical structure, while applying artificial intelligence algorithms such as platoon solutions [13] and obstacle avoidance techniques [16]. The urban vehicle simulator is based on two main engines: one for physics simulation and one for 3D immersion in a topological environment.…”

Section: Transportation-related Simulation Toolsmentioning

confidence: 99%

“…Then the availability of charger and energy to start the charging immediately is checked (lines 9-12). If both charger and energy exist, then the price to pay for the charging p j is calculated and the event state is set to accepted (lines [13][14][15][16][17]. If no charger and/or no energy is available for immediate charging, then the scheduling of the event for later charging is considered.…”

Section: Discharge (V2g Technology)mentioning

confidence: 99%

“…For all charging events the requested energy is 8 kWh. In scenario 3 the order and the requested energy measured in kWh are the following: slow (20), fast (20), slow (20), fast (20), slow (30), fast (20), slow (15), slow (20), fast (25), fast (25). Figures 17 and 18 demonstrate the number of charging events in the waiting lists and the remaining energy amounts of each energy source, after the insertion of all charging events at each occasion.…”

Section: Fast Eventsmentioning

confidence: 99%

See 2 more Smart Citations

EVLibSim: A tool for the simulation of electric vehicles’ charging stations using the EVLib library

Rigas

Karapostolakis

Bassiliades

et al. 2018

Simulation Modelling Practice and Theory

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Electric Vehicles (EVs) are considered an efficient alternative to internal combustion engined ones, aiming to reduce global CO 2 emissions. In the last years, EVs are entering the market in an increasing pace. In contrast to conventional cars, EVs have a more complicated recharging procedure. Thus, the development of tools for the efficient simulation of the charging of large numbers of EVs is critical. In this vein, EVLibSim is a tool for the simulation of EV activities at a charging station level. EVLibSim unifies EVLib's primary functions such as the charging and dis-charging of batteries, battery swapping, as well as parking/inductive charging. EVLib is a Java library that provides a simple, yet efficient framework for the management of a number of Electric Vehicle (EV) activities, at a charging station level, within a Smart Grid. EVLibSim provides a great variety of configuration options such as the types and number of chargers, the available energy, the waiting queues, etc. Furthermore, through plots and overview dashboards each user can supervise the operation of the tool in real time. Both EVLib's and EVLibSim's efficiency and scalability have been tested in realistic scenarios, while the correctness and safety of the code have been verified using state of the art tools. Finally, the user experience of the EVLibSim has been evaluated and improved through a detailed user evaluation.

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Section: Transportation-related Simulation Toolsmentioning

confidence: 99%

Section: Discharge (V2g Technology)mentioning

confidence: 99%

Section: Fast Eventsmentioning

confidence: 99%

See 1 more Smart Citation

EVLibSim: A tool for the simulation of electric vehicles’ charging stations using the EVLib library

Rigas

Karapostolakis

Bassiliades

et al. 2018

Simulation Modelling Practice and Theory

View full text Add to dashboard Cite

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“…The body participates to the solving of this challenge by providing sensors that are defined or constrained by geometries. For example, the view perception may be supported by a camera in the real world [8], or by a geometrical shape in a simulated environment [7]. In this last case, the shape of the field-of-view is defined by geometrical elements that have a position relative to the position of the agent's body in the physical environment.…”

Section: Mastering the Mind Conceptmentioning

confidence: 99%

Agent Bodies: An Interface Between Agent and Environment

Carrascosa

Galland

Kanmeugne

2015

Lecture Notes in Computer Science

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Abstract. Interfacing the agents with their environment is a classical problem when designing multiagent systems. However, the models pertaining to this interface generally choose to either embed it in the agents, or in the environment. In this position paper, we propose to highlight the role of agent bodies as primary components of the multiagent system design. We propose a tentative definition of an agent body, and discuss its responsibilities in terms of MAS components. The agent body takes from both agent and environment: low-level agent mechanisms such as perception and influences are treated locally in the agent bodies. These mechanism participate in the cognitive process, but are not driven by symbol manipulation. Furthermore, it allows to define several bodies for one mind, either to simulate different capabilities, or to interact in the different environments -physical, social-the agent is immersed in. We also draw the main challenges to apply this concept effectively.

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“…Biswas et al [4] proposed vehicle-tovehicle communication protocols for traffic safety enhancement, and simulation analysis showed that their proposed algorithm could mitigate the risk of rear-endcollision in a three-vehicle platoon. Contet et al [5][6] tackled the issue of linear platoon control both by simulation and experimental analysis using test vehicles and a multiagent system. Yi and Chong [7] proposed and evaluated a vehicle control algorithm designed to make five-vehicle platoons safer and thus mitigate the risk of rear-end collisions.…”

Section: Introductionmentioning

confidence: 99%

Applicability of microscopic shockwave theory for evaluating collision risk in vehicle platoon

Suzuki

Kubota

2013

2013 IEEE International Conference on Mechatronics and Automation

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In this study, an applicability of microscopic shockwave ( SW μ ) theory is evaluated whether it is efficient in assessing the risk of rear-end collision in vehicle platoon. Two different types of SW μ behavior are proposed for the evaluation; one is the car-following that shows a higher risk, whereas the other is a low-risk vehicle platooning. The numerical analysis attempts to evaluate whether the conventional risk evaluation approaches are able to distinguish those two cases; high and low risk platooning based on the proposed SW μ technique. The statistical analysis showed that the behavior of SW μ is capable of assessing the risk of rear-end collision of platooning vehicles.

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Virtual intelligent vehicle urban simulator: Application to vehicle platoon evaluation

Cited by 31 publications

References 5 publications

EVLibSim: A tool for the simulation of electric vehicles’ charging stations using the EVLib library

EVLibSim: A tool for the simulation of electric vehicles’ charging stations using the EVLib library

Agent Bodies: An Interface Between Agent and Environment

Applicability of microscopic shockwave theory for evaluating collision risk in vehicle platoon

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