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dc.contributor.advisorRan, Bin
dc.contributor.authorAlazmi, Asmaa
dc.date.accessioned2019-01-14T16:25:30Z
dc.date.available2019-01-14T16:25:30Z
dc.date.issued2018
dc.identifier.urihttp://digital.library.wisc.edu/1793/78898
dc.description.abstractOver the last few years, the applications of Autonomous Vehicles in the Freeway network have attracted increased attention both in practice and in the research field. However, the detection of the effect of the Autonomous Vehicles remains a challenging task due to the complex environment and heterogeneity characteristics the Freeway network has. Fortunately, the recent development of the connected vehicle technologies may provide a promising platform to observe and estimate effect of implement AV on roadway Capacity. The efficiency of the transport network is determined by its capacity. On Freeway, the capacity is dependent on the maximum possible flow of traffic on the road sections as well as the percentage of the Heavy Vehicles, Manual Vehicles and the Autonomous Vehicles entering the Freeway. Autonomous vehicles maneuver in traffic through road networks does not requiring humans as supervisors or decision makers. Autonomous vehicles increase comfort for their passengers by removing the need for them to perform driving tasks. Autonomous Vehicle level 3 is could eliminate human reaction, and this should increase the roadway capacity since the gap acceptance would decrease. While the capacity at traffic is determined by the amount of time required by individuals, the capacity of the Freeway may improve by implement the technics of Autonomous in the road either on the passenger cars or on the heavy vehicles. The entry of Heavy vehicles into the traffic stream affect the number of vehicle that can be observed also they have poorer operation capacities than the passenger cars. This project explores how the decrease of the gap acceptance will affect the roadway capacity also the different percentage of level 3 automated heavy vehicle would investigate on the freeway capacity by using VISSIM as a microsimulation tool. Different scenarios were set up in the VISSIM freeway network to detect how different gap acceptance and different percentages of level 3 automated heavy vehicles in the traffic mix may change the freeway capacity. This study is to demonstrate how does the Autonomous Heavy Vehicles will improve the Freeway Capacity reduction due to the heavy vehicles. The physical characteristics of heavy vehicles such as low acceleration and slow speed have less reduction effects after implement the Automated behaviors.en_US
dc.language.isoen_USen_US
dc.titleIMPACT OF LEVEL 3 HIGHLY AUTOMATED HEAVY VEHICLES ON FREEWAY CAPACITYen_US
dc.typeThesisen_US


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