Spacing Allocation Method for Vehicular Platoon: A Cooperative Game Theory Approach

Liu, Yang; Zong, Changfu; Xiao-jian, Han; Zhang, Dong; Zheng, Hongyu; Shi, Chunmei

doi:10.3390/app10165589

Cited by 8 publications

(4 citation statements)

References 36 publications

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“…The motion controller and spacing policies have an impact on the platoon’s overall performance and profit. A systematic spacing policy was presented by Liu et al [ 76 ] to study the spacing decision based on coalitional GT. Based on the concepts of bionic motion, a flock’s model was employed as the payoff function.…”

Section: The Analyses Of Decision-making Relevant Solutions For Auton...mentioning

confidence: 99%

How Do Autonomous Vehicles Decide?

Malik

Khan

El-Sayed

et al. 2022

Sensors

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The advancement in sensor technologies, mobile network technologies, and artificial intelligence has pushed the boundaries of different verticals, e.g., eHealth and autonomous driving. Statistics show that more than one million people are killed in traffic accidents yearly, where the vast majority of the accidents are caused by human negligence. Higher-level autonomous driving has great potential to enhance road safety and traffic efficiency. One of the most crucial links to building an autonomous system is the task of decision-making. The ability of a vehicle to make robust decisions on its own by anticipating and evaluating future outcomes is what makes it intelligent. Planning and decision-making technology in autonomous driving becomes even more challenging, due to the diversity of the dynamic environments the vehicle operates in, the uncertainty in the sensor information, and the complex interaction with other road participants. A significant amount of research has been carried out toward deploying autonomous vehicles to solve plenty of issues, however, how to deal with the high-level decision-making in a complex, uncertain, and urban environment is a comparatively less explored area. This paper provides an analysis of decision-making solutions approaches for autonomous driving. Various categories of approaches are analyzed with a comparison to classical decision-making approaches. Following, a crucial range of research gaps and open challenges have been highlighted that need to be addressed before higher-level autonomous vehicles hit the roads. We believe this survey will contribute to the research of decision-making methods for autonomous vehicles in the future by equipping the researchers with an overview of decision-making technology, its potential solution approaches, and challenges.

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Section: The Analyses Of Decision-making Relevant Solutions For Auton...mentioning

confidence: 99%

How Do Autonomous Vehicles Decide?

Malik

Khan

El-Sayed

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…A coupling process before arriving at a station and the resulting coupled state are shown in Figure 1. In this process, automated control trains are regarded as agents of the system that influence the behavior of the group [17]. This section presents the two main states of virtual coupling: the coupling state and the coupled state.…”

Section: Problem Statementmentioning

confidence: 99%

“…Yang et al [15] proposed a non-signalized intersection driving model using cooperative game theory and the Shapley allocation method. Liu et al [17] proposed a spacing allocation method for vehicular platoons using cooperative game theory and the Shapley values to allocate the spacings fairly. With the gradual deepening of virtual coupling research, it is feasible to regard autonomous trains in a convoy as rational participants.…”

Section: Introductionmentioning

confidence: 99%

Optimized Control of Virtual Coupling at Junctions: A Cooperative Game-Based Approach

et al. 2021

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Recently, virtual coupling has aroused increasing interest in regard to achieving flexible and on-demand train operations. However, one of the main challenges in increasing the throughput of a train network is to couple trains quickly at junctions. Pre-programmed train operation strategies cause trains to decelerate or stop at junctions. Such strategies can reduce the coupling efficiency or even cause trains to fail to reach coupled status. To fill this critical gap, this paper proposes a cooperative game model to represent train coupling at junctions and adopts the Shapley theorem to solve the formulated game. Due to the discrete and high-dimensional characteristics of the model, the optimal solution method is non-convex and is difficult to solve in a reasonable amount of time. To find optimal operation strategies for large-scale models in a reasonable amount of time, we propose an improved particle swarm optimization algorithm by introducing self-adaptive parameters and a mutation method. This paper compares the strategy for train coupling at junctions generated by the proposed method with two naive strategies and unimproved particle swarm optimization. The results show that the operation time was reduced by using the proposed cooperative game-based optimization approach.

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“…On the contrary, an inter-vehicular communication system can range from that of a V2V or V2I communication in which the vehicles exchange information like speed, distance, and position [12]. The inter-vehicular communication system also helps the vehicle in a platoon to calculate its constant distance (CD) or constant time headway (CTH) [13]. The set distance between two neighbouring vehicles is known as the CD policy, and it can be measured in metres or inches.…”

Section: Introductionmentioning

confidence: 99%

An adaptive fuzzy control technique for a high‐speed vehicular platoon experiencing communication delays

Li,

Wu,

Gulati

et al. 2023

IET Intelligent Trans Sys

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Vehicle platooning is seen as an enabler to improve driving safety, traffic congestion and stress‐free driving. A platoon is a highly non‐linear system and fuzzy control is able to deal with those systems. This paper presents a pioneering solution to the complex problem of vehicle platooning. Our adaptive controller seamlessly integrates fuzzy logic with conventional PID control technology, thereby ensuring safe and efficient travel for vehicles within a platoon. The key objectives of this controller encompass the maintenance of a consistent inter‐vehicle time gap and the consideration of time‐varying parameter uncertainties and communication delays between vehicles. It provides mathematical proof of the stability of the platoon formation using the Routh–Hurwitz theorem and a set of equations that describe the platoon's overall performance. Simulation results show that the proposed controller is effective in controlling vehicle platoons, even in the presence of random communication delays, resulting in improved driving safety and reduced traffic congestion.

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Spacing Allocation Method for Vehicular Platoon: A Cooperative Game Theory Approach

Cited by 8 publications

References 36 publications

How Do Autonomous Vehicles Decide?

How Do Autonomous Vehicles Decide?

Optimized Control of Virtual Coupling at Junctions: A Cooperative Game-Based Approach

An adaptive fuzzy control technique for a high‐speed vehicular platoon experiencing communication delays

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