Finally, this lane change model, which captures the collective decision-making between human drivers, can be used to develop automated vehicle driving strategies. The proposed repeated game model produces superior performance to a one-shot game model when simulating actual freeway merging behaviors. To provide evidence of the benefits of the repeated game approach, which takes into account previous decision-making results, a case study is conducted using an agent-based simulation model. In addition, a sensitivity analysis demonstrates the rationality of the model and its sensitivity to variations in various factors. Validation results using the Next Generation SIMulation (NGSIM) empirical data show that the developed game-theoretical model provides better prediction accuracy compared to previous work, giving correct predictions approximately 86% of the time. Specifically, this paper advances our repeated game model by using updated payoff functions. To overcome this shortcoming, we develop a game-theoretical decision-making model and validate the model using empirical merging maneuver data at a freeway on-ramp. Most lane-changing models deal with lane-changing maneuvers solely from the merging driver’s standpoint and thus ignore driver interaction. Do you think you have nerves of steel so you can race down the highway at 250 km/h without getting scared? No matter what you're looking for exactly, if you love speed and cars, our highway games will give you many hours of fun, so what are you waiting for? Have fun with our fast-paced collection of the best highway games, as always online and free on Silvergames.Lane changes are complex safety- and throughput-critical driver actions. Race your motorcycle, your Porsche or your Maserati over the roads and make the tires squeal.

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