An Intersection Game-Theory-Based Traffic Control Algorithm in a Connected Vehicle Environment

Adaptive Game-Theoretic Decision Making for Autonomous Vehicle Control at Roundabouts

“…The weight in (2) is chosen as w = [1000, 500, 5, 100, 50, 1] . The discount factor in the cumulative reward function is λ = 0.8, and the update step size in the adaptation law (7) is β = 0.6. We first test the AV controller's performance versus opponent vehicles controlled by type-1 or 2 drivers.…”

“…With the use of the above three neural networks, we move the computations to solve the optimization problems (4), (5), and (6) from online to offline. The online control is policybased and requires only neural network evaluations, where the policy adapts to the opponent vehicle's driver by the adaptation law (7). The overall structure of the AV controller is shown in Fig 2.…”

“…Game-theoretic modelings of driver and vehicle interactions in highway traffic scenarios for use in autonomous vehicle control development are discussed in [3], [4], [5]. Game-theoretic autonomous vehicle control algorithms for intersection traffic scenarios are proposed in [6], [7]. In [6], vehicle-to-vehicle interactions at an unsignalized four-way intersection are modeled using a game-theoretic framework, and then an autonomous vehicle controller for such an intersection is developed based on the vehicle interaction model.…”

Driving strategy selection for cooperative vehicles using maneuver templates

“…. , k 4 result from the derivation of (8) and (10) with respect to x (see (16)), respectively, and depend on v Vn,x (t f ) and u Vn,x for n ∈ {1, 2, 3}. The optimal control input can be deduced from…”

Reliable Intersection Control in Non-cooperative Environments

“…This approach leads to relatively complex algorithms to compute the intersection allocation and requires a payment system. In [3], the authors have proposed a chicken-game [4] inspired intersection control. The proposed game includes two players, where the players aim to minimize their delay while also avoiding any collision; and the intersection manager controls their actions, i.e., swerve or not, to achieve a Nash equilibrium [5] of the game.…”