Situation Assessment in Tactical Lane Change Behavior Planning for Automated Vehicles

2015 ◽  
Author(s):  
Simon Ulbrich ◽  
Markus Maurer
Keyword(s):  
Lane Change ◽  
Automated Vehicles ◽  
Situation Assessment ◽  
Change Behavior

An Interaction-Aware Lane Change Behavior Planner for Automated Vehicles on Highways Based on Polygon Clipping

2019 ◽  
Vol 4 (2) ◽  
pp. 1876-1883 ◽  
Author(s):  
Manuel Schmidt ◽  
Carlo Manna ◽  
Jan Holger Braun ◽  
Christian Wissing ◽  
Manoj Mohamed ◽  
...  
Keyword(s):  
Lane Change ◽  
Automated Vehicles ◽  
Change Behavior

Curvilinear-Coordinate-Based Object and Situation Assessment for Highly Automated Vehicles

2015 ◽  
Vol 16 (3) ◽  
pp. 1559-1575 ◽  
Author(s):  
Junsoo Kim ◽  
Kichun Jo ◽  
Wontaek Lim ◽  
Minchul Lee ◽  
Myoungho Sunwoo
Keyword(s):  
Automated Vehicles ◽  
Situation Assessment ◽  
Curvilinear Coordinate

Cellular Automata–Based Modeling and Simulation of a Mixed Traffic Flow of Manual and Automated Vehicles

2017 ◽  
Vol 2622 (1) ◽  
pp. 105-116 ◽  
Author(s):  
Da Yang ◽  
Xiaoping Qiu ◽  
Lina Ma ◽  
Danhong Wu ◽  
Liling Zhu ◽  
...  
Keyword(s):  
Reaction Time ◽  
Traffic Flow ◽  
Road Traffic ◽  
Flow Characteristics ◽  
Lane Change ◽  
Mixed Traffic ◽  
Automated Vehicles ◽  
Obvious Effect ◽  
Mixed Traffic Flow ◽  
Automated Vehicle

In recent years, automated vehicles have been developing rapidly, and some automated vehicles have begun to drive on highways. The market share of automated vehicles is expected to increase and will greatly affect traffic flow characteristics. This paper focuses on the mixed traffic flow of manual and automated vehicles. The study improves the existing cellular automaton model to capture the differences between manual vehicles and automated vehicles. Computer simulations are employed to analyze the characteristic variations in the mixed traffic flow under different automated vehicle proportions, lane change probabilities, and reaction times. Several new conclusions are drawn in the paper. First, with the increment of the proportion of automated vehicles, freeway capacity increases; the capacity increment is more significant for single-lane traffic than for two-lane traffic. Second, for single-lane traffic flow, reducing the reaction time of the automated vehicle can significantly improve road traffic capacity—as much as doubling it—and reaction time reduction has no obvious effect on the capacity of the two-lane traffic. Third, with the proportion increment of automated vehicles, lane change frequency reduces significantly. Fourth, when the density is 15 < ρ < 55 vehicles/km, the addition of 20% automated vehicles to a traffic flow that consisted of only manual vehicles can decrease congestion by up to 16.7%.

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