scholarly journals A Repeated Game Freeway Lane Changing Model

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1554 ◽  
Author(s):  
Kyungwon Kang ◽  
Hesham A. Rakha
Keyword(s):  
Decision Making ◽  
Repeated Game ◽  
Superior Performance ◽  
Game Model ◽  
Lane Changing ◽  
Agent Based ◽  
Lane Changes ◽  
Payoff Functions ◽  
Decision Making Model

Lane changes are complex safety- and throughput-critical driver actions. Most lane-changing models deal with lane-changing maneuvers solely from the merging driver’s standpoint and thus ignore driver interaction. 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. Specifically, this paper advances our repeated game model by using updated payoff functions. 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. In addition, a sensitivity analysis demonstrates the rationality of the model and its sensitivity to variations in various factors. 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. The proposed repeated game model produces superior performance to a one-shot game model when simulating actual freeway merging behaviors. Finally, this lane change model, which captures the collective decision-making between human drivers, can be used to develop automated vehicle driving strategies.

Modeling Driver Merging Behavior: A Repeated Game Theoretical Approach

2018 ◽  
Vol 2672 (20) ◽  
pp. 144-153 ◽  
Author(s):  
Kyungwon Kang ◽  
Hesham A. Rakha
Keyword(s):  
Decision Making ◽  
Theoretical Approach ◽  
Repeated Game ◽  
Simulation Software ◽  
Lane Changing ◽  
Microscopic Traffic Simulation ◽  
Game Theoretical Approach ◽  
The Subject ◽  
Merging Behavior ◽  
Decision Making Model

Various lane-changing models have been developed for use within microscopic traffic simulation software to replicate driver merging behavior. An understanding of human driving behavior, which can be gained through such modeling, will be critical in harmonizing emerging advanced vehicle technology, such as connected automated vehicles, with human drivers. Therefore, it is important to ensure that lane-changing models are clearly understood, appropriately designed, and carefully calibrated. An earlier study by Kang and Rakha proposed and developed a decision-making model for merging maneuvers using a game theoretical approach considering two drivers: the driver of the subject vehicle (DS) in an acceleration lane and the driver of the following lag vehicle (DL) in the target lane. The previous model assumed that the DS and DL decide on an action at the first point only, where the subject and lag vehicles are identified. The current study extends the Kang and Rakha model by introducing the concept of a repeated game, assuming that a lane change decision is made repeatedly to adjust to changes in surrounding conditions. For example, drivers often decide to change their initial decision as a result of conflicts with other drivers. A repeated game helps the proposed model produce more realistic decision-making in the lane-changing process. To evaluate the model, driver decisions at a certain stage, along with accumulated historical decision data, were extracted from Next Generation SIMulation (NGSIM) data. The validation results reveal that the proposed repeated game model produces considerable prediction accuracy (above 75%).

scholarly journals A Discretionary Lane-Changing Decision-Making Mechanism Incorporating Drivers’ Heterogeneity: A Signalling Game-Based Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Haipeng Shao ◽  
Miaoran Zhang ◽  
Tao Feng ◽  
Yifan Dong
Keyword(s):  
Decision Making ◽  
Perfect Bayesian Equilibrium ◽  
Lane Changing ◽  
Time To Collision ◽  
Mixed Traffic Flow ◽  
Bayesian Equilibrium ◽  
Proposed Model ◽  
Payoff Functions ◽  
Comparative Results ◽  
Decision Making Model

This paper attempts to propose a discretionary lane-changing decision-making model based on signalling game in the context of mixed traffic flow of autonomous and regular vehicles. The effects of the heterogeneity among different drivers and the endogeneity of same drivers in lane-changing behaviours, e.g., aggressive or conservative, are incorporated through the specification of different payoff functions under different scenarios. The model is calibrated and validated using the NGSIM dataset with a bilevel calibration framework, including two kinds of methods, genetic algorithm and perfect Bayesian equilibrium. Comparative results based on simulation show that the signalling game-based model outperforms the traditional space-based lane-changing model in the sense that the proposed model yields relatively stable reciprocal of time to collision and higher success rate of lane-changing under different traffic densities. Finally, a sensitivity analysis is performed to test the robustness of the proposed model, which indicates that the signalling game-based model is stable to the varying ratios of driver type.

Group Decision Model Based on Ordered Weighted Distance to Aid Decisions on Logistics

2018 ◽  
Vol 26 (02) ◽  
pp. 233-254 ◽  
Author(s):  
Jose Leao E Silva Filho ◽  
Danielle Costa Morais
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Decision Model ◽  
Group Decision ◽  
Decision Rules ◽  
Decision Makers ◽  
Weighted Distance ◽  
Model Based ◽  
Decision Making Model

This paper presents a group decision-making model using a distance aggregator based on Ordered Weighted Distance (OWD) which offers a solution that can reduce disagreement between decision makers (DMs). This paper discusses decision rules and sets out measures to evaluate compensatory effects that have a bearing on DMs’ opinions. The model uses formulations of distances to reveal the differences in opinion among DMs and discusses the meanings of distance and the information presented by each DM. Finally, a case study of a logistics problem is used to illustrate how the model is applied.

scholarly journals Approaches to Modeling the Gas-Turbine Maintenance Process

2011 ◽  
Vol 12 (1) ◽  
Author(s):  
Tai-Tuck Yu ◽  
James P. Scanlan ◽  
Richard M. Crowder ◽  
Gary B. Wills
Keyword(s):  
Decision Making ◽  
Gas Turbine ◽  
Discrete Event ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Event Modeling ◽  
Human Decision ◽  
Event Model ◽  
Discrete Event Model

Discrete-event modeling has long been used for logistics and scheduling problems, while multi-agent modeling closely matches human decision-making process. In this paper, a metric-based comparison between the traditional discrete-event and the emerging agent-based modeling approaches is reported. The case study involved the implementation of two functionally identical models based on a realistic, nontrivial, civil aircraft gas turbine global repair operation. The size, structural complexity, and coupling metrics from the two models were used to gauge the benefits and drawbacks of each modeling paradigm. The agent-based model was significantly better than the discrete-event model in terms of execution times, scalability, understandability, modifiability, and structural flexibility. In contrast, and importantly in an engineering context, the discrete-event model guaranteed predictable and repeatable results and was comparatively easy to test because of its single-threaded operation. However, neither modeling approach on its own possesses all these characteristics nor can each handle the wide range of resolutions and scales frequently encountered in problems exemplified by the case study scenario. It is recognized that agent-based modeling can emulate high-level human decision-making and communication closely while discrete-event modeling provides a good fit for low-level sequential processes such as those found in manufacturing and logistics.

A multi-criteria decision making model for outsourcing maintenance services

Facilities ◽  
2015 ◽  
Vol 33 (3/4) ◽  
pp. 229-244 ◽  
Author(s):  
Mohammad A. Hassanain ◽  
Sadi Assaf ◽  
Abdul-Mohsen Al-Hammad ◽  
Ahmed Al-Nehmi
Keyword(s):  
Decision Making ◽  
Air Conditioning ◽  
Relative Weight ◽  
Equal Weight ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Air Conditioning Systems ◽  
Decision Making Model ◽  
Outsourcing Decision

Purpose – The purpose of this paper is to present the development of a multi-criteria decision-making model for use by maintenance managers to consider before making a decision on outsourcing. Design/methodology/approach – Thirty-eight factors were identified for outsourcing maintenance services. These factors were grouped under six categories, namely: “strategic”, “management”, “technological”, “quality”, “economic” and “function characteristics”. The Analytic Hierarchy Process, as a multi-criteria decision-making model, was introduced and applied as an approach for maintenance managers in Saudi Arabian universities to consider before making a decision on outsourcing. A case study on the outsourcing decision of maintenance services of air-conditioning systems was carried out to apply the developed model. Findings – Data analysis indicated that all outsourcing decision groups of factors have almost equal weight, with the “quality” group of factors having the highest weight and the “technological” group of factors having the least weight. Further, the analysis indicated, in general, that the recommended decision for the maintenance managers is to outsource. However, an application of the developed model through a case study on the outsourcing of maintenance services of air-conditioning systems showed that the recommended action is not to outsource. Originality/value – The presented approach in this paper could be of practical benefit to maintenance managers in their decision making of whether or not to outsource maintenance services. The factors in the model were identified through a literature survey of research carried out in different countries. Therefore, the model could be applied in different settings, depending on the relative weight of the factors by the users.

scholarly journals A fuzzy-TOPSIS model for maintenance outsourcing considering the quality of submitted tender documents

2021 ◽  
Vol 23 (3) ◽  
pp. 443-453
Author(s):  
Maysa Alshraideh ◽  
Shereen Ababneh ◽  
Elif Elcin Gunay ◽  
Omar Al-Araidah
Keyword(s):  
Decision Making ◽  
Selection Criteria ◽  
Fuzzy Topsis ◽  
Final Decision ◽  
Proposed Model ◽  
Maintenance Outsourcing ◽  
Multiple Experts ◽  
Decision Making Model

The paper provides a multiple-experts Fuzzy-TOPSIS decision-making model for the selection among maintenance contractors based on the quality of tendering documents. The study introduces a set of selection criteria utilizing benefit and cost criteria from literature. The proposed model aggregates subjective linguistic assessments of multiple experts that express their opinions on the degree of importance of criteria and allows multiple decisionmakers to evaluate the compliance of contractors’ documents. For a case study, the model is applied to select among contractors tendering to maintain the heavy-duty cranes of an international steel company from literature. Several decision-making scenarios are investigated, and major changes in the final decision are observed. The changes in obtained results illustrate the need to better address uncertainties in rating and tendering an overqualified contractor at a higher cost.

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