Today: Sunday, 6 April 2025
Evaluation of car following (Car Following) simulation models
Volume 3, Issue 2, 2021, Pages 17 - 20
Author(s) : Shadi ahmadbeigi* 1 , kimiya shirini rad 2

1 department of engineering, college of computer north Tehran branch, Islamic Azad university Tehran, Iran.

2 Tabriz sahand university

Abstract :
Astract: The use of traffic simulation software for performance analysis is developing rapidly. Therefore, it is important to know the models used in these softwares and the capabilities and limitations of the models used to ensure the accuracy of the results obtained. Among these models are car following models. So far, various models have been presented to express the behavior of vehicles in adjusting their distance to the vehicle ahead in the form of a mathematical formulation that is used in traffic simulation software. In this article, after reviewing the types of these models, the car models are compared in two traffic simulation software VISSIM and AIMSUN. For better analysis and display of the difference between the performance of these two softwares and analysis of their sensitivity.
Keywords :
Keyword: CONTINUOUS CARS, TRAFFIC NETWORK DYNAMICAL MODELS, MICROSCOPIC SIMULATION
periodic arraynonlinearly loaded straight wirenonlinear current approachNonlinear currents approach; harmonic balancenonlinear dipoleMedical Data MiningMultiple ClassificationDempster-Shafer TheoryArtificial neural networkfatty livermedical technologydispersive ground; grounding grid; lightning strokeAutonomus QuadcopterFPCNNImage Processinglandingtake-offIrisauthenticationimage categorizationbiometric system“Active Filter”“High Voltage DC”“CMOS”“F MHz”“Distortion”Keywords MathematicsEducationKeywords Internet of Things6LowPANBLENFCZ-WaveZigBeeSIGFOXCellularLTE-AD2DVoIPMode SwitchingSoftware TestingTest Data GenerationSearch AlgorithmsGenetic Algorithmcloud computingload distributioncuckoo algorithmvehicular ad hoc networkBayesian algorithmAODV protocolreduce of package loss rateaverage end-to-end delayMachine LearningDeep LearningNeural networksCorona virus Pattern RecognitionincidentresponsedefensiveoffensiveITILNISTincident response‎ Robust optimizationData MiningCrimeClassificationEnsemble methodInfluence PropagationInfluence MaximizationLinear Threshold ModelElectronic citySmart citybig dataincident computerincident managerSoftware testing techniqueSoft ComputingKeyword CONTINUOUS CARSMICROSCOPIC SIMULATIONSQLNOSQLCloud NetworkWorkflows constructiontechnologiesarchitectureCyberinfiltrationfirewalldefenseattackFling Ad-hoc networksRoutingImprovementIoTInternet SecurityHealthCyberspace ThreatsCyber SecurityAlgorithmsVirtualizationDatabase SecuritySQL ServerCyberspace platformscivil liabilityVicarious liabilitysecurityChannel EstimationMIMO-OFDMNOMASNRsparse signalsensor LNALinearizationRF circuitSensor glassesmobility aidsense sightwearable strapalarmblindnessultrasonicsmartdetectorwarningLearningFace tagUser's facecommunicationsocial mediasitesmediaSatelliteCan SatSatPC32sensorsCiscoCYMEdpvdrgSTATCOMLSTMRNN