TIMIPLAN: A Tool for Transportation Tasks

Garcı́a, Javier; Torralba, Álvaro; Florez, José E.; Borrajo, Daniel; López, Carlos Linares; García-Olaya, Ángel

doi:10.1007/978-3-319-25808-9_16

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…Only plans with cost equal or lower than the bound will be valid, with the assumption that no plan will exist reaching all goals with such cost bound. Examples of such limited and insufficient resources appear in space exploration [1,6], transportation [7] and in many other applications.…”

Section: Introductionmentioning

confidence: 99%

Selecting goals in oversubscription planning using relaxed plans

García-Olaya

Rosa

Borrajo

2021

Artificial Intelligence

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Section: Introductionmentioning

confidence: 99%

Selecting goals in oversubscription planning using relaxed plans

García-Olaya

Rosa

Borrajo

2021

Artificial Intelligence

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Improving the Road and Traffic Control Prediction Based on Fuzzy Logic Approach in Multiple Intersections

2022

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Traffic congestion is a significant issue in many countries today. The suggested method is a novel control method based on multiple intersections considering the kind of traffic light and the duration of the green phase to determine the optimal balance at intersections by using fuzzy logic control, for which the balance should be adaptable to the unchanging behavior of time. It should reduce traffic volume in transport, average waits for each vehicle, and collisions between cars by controlling this balance in response to the typical behavior of time and randomness in traffic conditions. The proposed method is investigated at intersections using a sampling multi-agent system to set traffic light timings appropriately. The program is provided with many intersections, each of which is an independent entity exchanging information with the others. The stability per entity is proven separately. Simulation results show that Takagi–Sugeno (TS) fuzzy modeling performs better than Takagi–Sugeno (TS) fixed-time scheduling in decreasing the length of queueing times for vehicles.

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Ubiquitous IoT in the Automotive Domain

Varga

2018

Advances in Systems Analysis, Software Engineering, and High Performance Computing

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Ubiquitous IoT systems open new ground in the automotive domain. With the advent of autonomous vehicles, there will be several actors that adapt to changes in traffic, and decentralized adaptation will be a new type of issue that needs to be studied. This chapter investigates the effects of adaptive route planning when real-time online traffic information is exploited. Simulation results show that if the agents selfishly optimize their actions, then in some situations the ubiquitous IoT system may fluctuate and the agents may be worse off with real-time data than without real-time data. The proposed solution to this problem is to use anticipatory techniques, where the future state of the environment is predicted from the intentions of the agents. This chapter concludes with this conjecture: if simultaneous decision making is prevented, then intention-propagation-based prediction can limit the fluctuation and help the ubiquitous IoT system converge to the Nash equilibrium.

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TIMIPLAN: A Tool for Transportation Tasks

Cited by 3 publications

References 11 publications

Selecting goals in oversubscription planning using relaxed plans

Selecting goals in oversubscription planning using relaxed plans

Improving the Road and Traffic Control Prediction Based on Fuzzy Logic Approach in Multiple Intersections

Ubiquitous IoT in the Automotive Domain

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