|dc.description.abstract||Over 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
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