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dc.contributor.authorYang, Xinyi
dc.description.abstractAs the rapid development of smart cities, autonomous vehicles are considered to be the future ground transportation measure which provides many benefits over traditional human-driving vehicles. However, there will be decades before the autonomous vehicles fully penetrate, during when human-drivers will share the same road systems with the autonomous vehicles, where the majority of accidents associated with autonomous vehicles are induced by the operation inconsistency of human drivers, which can be avoided if there is communication between the autonomous vehicles and the infrastructure (V2I). This study develops cumulative-anticipative car-following (CACF) model for autonomous vehicles based on the Cooperate Adaptive Cruise Control/ Adaptive Cruise Control (CACC/ACC) model by considering cumulative influences from multiple preceding vehicles. The simulation results from 128 simulation runs using the micro-simulator VISSIM showed that the CACF model can improve the safety and traffic congestions compared to the Wiedemann 99, the ACC, and the CACC models.en_US
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU policy 190.6.2en_US
dc.titleCumulative-Anticipative Car-Following Model for Enhanced Safety in Autonomous Vehiclesen_US
dc.typeThesisen_US
dc.date.accessioned2024-01-19T17:15:00Z
dc.date.available2024-01-19T17:15:00Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/10365/33622
dc.subjectAdaptive Cruise Controlen_US
dc.subjectautonomous vehiclesen_US
dc.subjectcar-following modelen_US
dc.subjectCooperate Adaptive Cruise Controlen_US
dc.subjectcumulative-anticipative car-following modelen_US
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdfen_US
ndsu.degreeMaster of Science (MS)en_US
ndsu.collegeEngineeringen_US
ndsu.departmentCivil, Construction, and Environmental Engineeringen_US
ndsu.programCivil Engineeringen_US
ndsu.advisorHuang, Ying


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