Lane Change Decision Analysis Based on Drivers' Perception-Judgment and Game Theory

2013 ◽  
Vol 361-363 ◽  
pp. 1875-1879 ◽  
Author(s):  
Jin Shuan Peng ◽  
Ying Shi Guo ◽  
Yi Ming Shao
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Nash Equilibrium ◽  
Equilibrium Solution ◽  
Information Source ◽  
Driving Safety ◽  
External Information ◽  
Lane Change ◽  
Safety Level ◽  
Lane Changing

To clearly understand the mechanism of drivers lane-changing decision, based on drivers perception of external information, integrated cognitive judgment and game theory, the decision-making model was established, then the structure and operating mechanism of the model were detailedly analyzed. By introducing game theory-related knowledge, the non-cooperative mixed strategy game between the object vehicle and the following vehicle in the target lane was further discussed. Then, the benefits and Nash equilibrium solution of the participants in the game were deeply researched. Analysis shows that lane-changing decision is composed of information perception and three judgment-decision processes, the factors which would affect decision-making level include information source characteristics, the ability of drivers perception and comprehensive cognitive judgment, driving behavior characteristics and so on. The Nash equilibrium solution of the lane change game is determined by driving safety level, journey time and importance degree of the revenues.

scholarly journals A Game Theory-Based Approach for Modeling Autonomous Vehicle Behavior in Congested, Urban Lane-Changing Scenarios

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1523
Author(s):  
Nikita Smirnov ◽  
Yuzhou Liu ◽  
Aso Validi ◽  
Walter Morales-Alvarez ◽  
Cristina Olaverri-Monreal
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Urban Traffic ◽  
Road User ◽  
Lane Change ◽  
Traffic Light ◽  
User Interactions ◽  
Lane Changing

Autonomous vehicles are expected to display human-like behavior, at least to the extent that their decisions can be intuitively understood by other road users. If this is not the case, the coexistence of manual and autonomous vehicles in a mixed environment might affect road user interactions negatively and might jeopardize road safety. To this end, it is highly important to design algorithms that are capable of analyzing human decision-making processes and of reproducing them. In this context, lane-change maneuvers have been studied extensively. However, not all potential scenarios have been considered, since most works have focused on highway rather than urban scenarios. We contribute to the field of research by investigating a particular urban traffic scenario in which an autonomous vehicle needs to determine the level of cooperation of the vehicles in the adjacent lane in order to proceed with a lane change. To this end, we present a game theory-based decision-making model for lane changing in congested urban intersections. The model takes as input driving-related parameters related to vehicles in the intersection before they come to a complete stop. We validated the model by relying on the Co-AutoSim simulator. We compared the prediction model outcomes with actual participant decisions, i.e., whether they allowed the autonomous vehicle to drive in front of them. The results are promising, with the prediction accuracy being 100% in all of the cases in which the participants allowed the lane change and 83.3% in the other cases. The false predictions were due to delays in resuming driving after the traffic light turned green.

Applied Game Theory in Business Analytics

2014 ◽  
pp. 156-167 ◽  
Author(s):  
William P. Fox
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Nash Equilibrium ◽  
Pure Strategy ◽  
Business Analytics ◽  
Competitive Situation ◽  
Present Solution ◽  
Different Types ◽  
Applied Game Theory ◽  
Decision Making Tool

In this chapter we introduce the concept of game theory and its use as a decision making tool in a competitive situation among players. We define and describe some different types of games and solution methodologies. We present the assumptions regarding these different types of game. We define and represent the different types of games between two players as either total conflict or partial conflict. We present solution techniques to both total conflict and partial conflict games. We present both pure strategy and mixed strategy solutions. We discuss the Nash equilibrium.

scholarly journals From Nash Equilibria to Chain Recurrent Sets: An Algorithmic Solution Concept for Game Theory

Entropy ◽  
2018 ◽  
Vol 20 (10) ◽  
pp. 782 ◽  
Author(s):  
Christos Papadimitriou ◽  
Georgios Piliouras
Keyword(s):  
Game Theory ◽  
Nash Equilibrium ◽  
Dynamical Systems ◽  
Nash Equilibria ◽  
Equilibrium Solution ◽  
Solution Concept ◽  
Constructive Proof ◽  
Specific Information ◽  
Potential Game ◽  
Chain Recurrence

In 1950, Nash proposed a natural equilibrium solution concept for games hence called Nash equilibrium, and proved that all finite games have at least one. The proof is through a simple yet ingenious application of Brouwer’s (or, in another version Kakutani’s) fixed point theorem, the most sophisticated result in his era’s topology—in fact, recent algorithmic work has established that Nash equilibria are computationally equivalent to fixed points. In this paper, we propose a new class of universal non-equilibrium solution concepts arising from an important theorem in the topology of dynamical systems that was unavailable to Nash. This approach starts with both a game and a learning dynamics, defined over mixed strategies. The Nash equilibria are fixpoints of the dynamics, but the system behavior is captured by an object far more general than the Nash equilibrium that is known in dynamical systems theory as chain recurrent set. Informally, once we focus on this solution concept—this notion of “the outcome of the game”—every game behaves like a potential game with the dynamics converging to these states. In other words, unlike Nash equilibria, this solution concept is algorithmic in the sense that it has a constructive proof of existence. We characterize this solution for simple benchmark games under replicator dynamics, arguably the best known evolutionary dynamics in game theory. For (weighted) potential games, the new concept coincides with the fixpoints/equilibria of the dynamics. However, in (variants of) zero-sum games with fully mixed (i.e., interior) Nash equilibria, it covers the whole state space, as the dynamics satisfy specific information theoretic constants of motion. We discuss numerous novel computational, as well as structural, combinatorial questions raised by this chain recurrence conception of games.

A Countermeasure Model about Food Safety Regulatory

2013 ◽  
Vol 781-784 ◽  
pp. 1546-1549 ◽  
Author(s):  
Li Xia Cao ◽  
Wei Wen Chai
Keyword(s):  
Game Theory ◽  
Nash Equilibrium ◽  
Food Safety ◽  
Equilibrium Solution ◽  
Mixed Strategy ◽  
Game Model ◽  
Mixed Strategy Nash Equilibrium ◽  
Regulatory Strategy ◽  
The Status ◽  
Strategy Nash Equilibrium

By studying the status of the food safety regulatory, this paper points out the drawbacks of existing researches, that is, lack of operability; Relying on the equilibrium theory of game theory, this paper establishes a practical and effective regulatory game model, gives the models mixed strategy Nash equilibrium solution and a food safety regulatory strategy. Finally, to illustrate the effectiveness and feasibility of the model, an illustrative example is shown.

scholarly journals Multi-UUV Cooperative Dynamic Maneuver Decision-Making Algorithm Using Intuitionistic Fuzzy Game Theory

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Lu Liu ◽  
Lichuan Zhang ◽  
Shuo Zhang ◽  
Sheng Cao
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Nash Equilibrium ◽  
Fuzzy Sets ◽  
Optimization Method ◽  
Intuitionistic Fuzzy Sets ◽  
Modified Particle Swarm Optimization ◽  
Intuitionistic Fuzzy ◽  
Weak Connectivity ◽  
Decision Making Model

In this paper, a multi-unmanned underwater vehicle (UUV) cooperative dynamic maneuver decision-making algorithm is proposed based on the combination of game theory and intuitionistic fuzzy sets. Underwater environments with weak connectivity, underwater noise, and dynamic uncertainties are fully considered through intuitionistic fuzzy sets, which solves one of the main problems in making decisions underwater. Subsequently, the intuitionistic fuzzy multiattribute evaluation of a UUV maneuver strategy is conducted, and the intuitionistic fuzzy payment matrix of the cooperative dynamic maneuver game is obtained. Thereafter, the Nash equilibrium condition is proposed to satisfy the intuitionistic fuzzy total order, and the Nash equilibrium maneuver decision-making model under a dynamic underwater environment is established. Meanwhile, the modified particle swarm optimization method is presented to solve the established problem and find the optimal strategy. Finally, an example is used to verify the superiority of the proposed cooperative dynamic maneuver decision-making algorithm.

Multi-Player Dynamic Game-Based Automatic Lane-Changing Decision Model under Mixed Autonomous Vehicle and Human-Driven Vehicle Environment

2020 ◽  
Vol 2674 (11) ◽  
pp. 165-183
Author(s):  
Yuewen Yu ◽  
Shikun Liu ◽  
Peter J. Jin ◽  
Xia Luo ◽  
Mengxue Wang
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Splitting Method ◽  
Dynamic Game ◽  
Cruise Control ◽  
Lane Changing ◽  
Bicycle Model ◽  
Decision Making Model

The lane-changing decision-making process is challenging but critical to ensure safe and smooth maneuvers for autonomous vehicles (AVs). Conventional Gipps-type algorithms lack the flexibility for practical use under a mixed autonomous vehicle and human-driven vehicle (AV-HV) environment. Algorithms based on utility ignore the reactions of surrounding vehicles to the lane-changing vehicle. Game theory is a good way to solve the shortcomings of current algorithms, but most models based on game theory simplify the game with surrounding vehicles to the game with the following vehicle in the target lane, which means that the lane-changing decision under a mixed environment is not realized. This paper proposes a lane-changing decision-making model which is suitable for an AV to change lanes under a mixed environment based on a multi-player dynamic game theory. The overtaking expectation parameter (OEP) is introduced to estimate the utility of the following vehicle, OEP can be calculated by the proposed non-lane-based full velocity difference model with the consideration of lateral move and aggressiveness. This paper further proposes a hybrid splitting method algorithm to obtain the Nash equilibrium solution in the multi-player game to obtain the optimal strategy of lane-changing decision for AVs. An adaptive cruise control simulation environment is developed with MATLAB’s Simulink toolbox using Next Generation Simulation (NGSIM) data as the background traffic flow. The classic bicycle model is used in the control of involved HVs. Simulation results show the efficiency of the proposed multi-player dynamic game-based algorithm for lane-changing decision making by AVs under a mixed AV-HV environment.

scholarly journals Effects of Financial Incentives on the Breakdown of Mutual Trust

2002 ◽  
Vol 13 (3) ◽  
pp. 292-297 ◽  
Author(s):  
James E. Parco ◽  
Amnon Rapoport ◽  
William E. Stein
Keyword(s):  
Decision Making ◽  
Nash Equilibrium ◽  
Financial Incentives ◽  
Equilibrium Solution ◽  
Backward Induction ◽  
Mutual Trust ◽  
Interactive Decision Making ◽  
Patterns Of Behavior

Disagreements between psychologists and economists about the need for and size of financial incentives continue to be hotly discussed. We examine the effects of financial incentives in a class of interactive decision-making situations, called centipede games, in which mutual trust is essential for cooperation. Invoking backward induction, the Nash equilibrium solution for these games is counterintuitive. Our previous research showed that when the number of players in the centipede game is increased from two to three, the game is iterated in time, the players are rematched, and the stakes are unusually high, behavior approaches equilibrium play. Results from the present study show that reducing the size of the stakes elicits dramatically different patterns of behavior. We argue that when mutual trust is involved, the magnitude of financial incentives can induce a considerable difference.

scholarly journals New Approach of Multistage Model in Supply Chain with Game Theory

2016 ◽  
Vol 10 (4) ◽  
pp. 112
Author(s):  
Kamran Shahanaghi ◽  
Maryam Keyvani Rad
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Supply Chain ◽  
Nash Equilibrium ◽  
Third Party ◽  
Nash Equilibrium Point ◽  
New Approach ◽  
Multistage Model ◽  
The Third ◽  
Multi Level

<p>This paper researches the relationships between seller and buyer with regard to game theory. The research continues by assuming an indirectly managing by an Intermediation. The intermediation is considered as third party who tried to decrease the distance between seller and buyer willing. In our proposed methodology, Bi-level programming is used for modeling the decision making between seller and buyer in supply chain, and then extend the model in Multi-level decision making. In the presented solution, the third part offers a price to each of the seller and buyer individually and supposed as leader. Final answers of described algorithms are Nash equilibrium point for supply chain. The object of seller and buyer are considered as a follower in each stage. Profits maximization for sellers and buyer are calculated by considering their own constraints.</p>

An IMM-based POMDP decision algorithm using collision-risk function in mandatory lane change

2021 ◽  
pp. 095440702110397
Author(s):  
Yunfeng Huang ◽  
Wanzhong Zhao ◽  
Can Xu ◽  
Songchun Zou ◽  
Han Zhang
Keyword(s):  
Decision Making ◽  
Autonomous Vehicle ◽  
Risk Function ◽  
Interacting Multiple Model ◽  
Lane Change ◽  
Multiple Model ◽  
Collision Risk ◽  
Lane Changing ◽  
Decision Algorithm ◽  
Risk Environments

In order to make safe and reasonable decisions in some high-risk environments such as the mandatory lane change, we propose an IMM-based partially observable Markov decision process (POMDP) decision algorithm using the collision-risk function which combines the time-to-collision (TTC), the intervehicular time (IT), and the collision function for mandatory lane change. The newly proposed collision-risk function contains two parts: the vehicle impact factor and the collision function, which is used to assess the risk and determines whether the autonomous vehicle collides with surrounding vehicles. The IMM-base POMDP is used for decision-making and we apply the Monte Carlo Tree Search (MCTS) to solve the problem. In the decision-making process, the belief state is obtained by the Interacting Multiple Model (IMM) algorithm. With the collision-risk function and the probability distribution of the states of surrounding vehicles in the future, the proposed POMDP decision algorithm can determine whether the autonomous vehicle accelerates lane changing or decelerates lane changing, and obtain the acceleration corresponding to each path point. Finally, in order to verify the effectiveness of the algorithm, we perform a driver-in-the-loop simulation through Prescan. We use aggressive driver and conservative driver to control the rear vehicle of the target lane, respectively. Simulation results show that the proposed algorithm can accurately predict the accelerations of surrounding vehicles and make safe and reasonable decisions under two scenarios, which is superior to the general POMDP.

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