Platoon forming algorithms for intelligent street intersections

Timmerman, Rik W.; Boon, Marko

doi:10.1080/23249935.2019.1692962

Cited by 26 publications

(8 citation statements)

References 31 publications

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“…Besides, Timmerman and Boon [191] investigated different platooning algorithms for vehicles that could minimize mean delay, provide fairness and safety. Guney and Raptis [192] harvested the optimal heuristic-based coordination solution for AVs using an particle swarm optimization (PSO) algorithm and FCFS policy to remove collisions and diminish the delay at the intersection.…”

Section: Safety and Efficiencymentioning

confidence: 99%

A Comprehensive Survey on Cooperative Intersection Management for Heterogeneous Connected Vehicles

Gholamhosseinian

Seitz

2022

IEEE Access

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Nowadays, with the advancement of technology, world is trending toward high mobility and dynamics. In this context, intersection management (IM) as one of the most crucial elements of the transportation sector demands high attention. Today, road entities including infrastructures, vulnerable road users (VRUs) such as motorcycles, moped, scooters, pedestrians, bicycles, and other types of vehicles such as trucks, buses, cars, emergency vehicles, and railway vehicles like trains or trams are able to communicate cooperatively using vehicle-to-everything (V2X) communications and provide traffic safety, efficiency, infotainment and ecological improvements. In this paper, we take into account different types of intersections in terms of signalized, semi-autonomous (hybrid) and autonomous intersections and conduct a comprehensive survey on various intersection management methods for heterogeneous connected vehicles (CVs). We consider heterogeneous classes of vehicles such as road and rail vehicles as well as VRUs including bicycles, scooters and motorcycles. All kinds of intersection goals, modeling, coordination architectures, scheduling policies are thoroughly discussed. Signalized and semi-autonomous intersections are assessed with respect to these parameters. We especially focus on autonomous intersection management (AIM) and categorize this section based on four major goals involving safety, efficiency, infotainment and environment. Each intersection goal provides an in-depth investigation on the corresponding literature from the aforementioned perspectives. Moreover, robustness and resiliency of IM are explored from diverse points of view encompassing sensors, information management and sharing, planning universal scheme, heterogeneous collaboration, vehicle classification, quality measurement, external factors, intersection types, localization faults, communication anomalies and channel optimization, synchronization, vehicle dynamics and model mismatch, model uncertainties, recovery, security and privacy.INDEX TERMS Vehicular ad-hoc networks (VANETs), intersection management (IM), vehicle-tovehicle (V2V), vehicle-to-infrastructure (V2I), trajectory planning (TP), spatio-temporal (ST), connected autonomous vehicles (CAVs), vulnerable road users (VRUs), connected vehicles (CVs), autonomous vehicle (AVs). II. INTERSECTION MANAGEMENT (IM) FUNDAMENTALS A. ARCHITECTURE ALTERNATIVESASHKAN GHOLAMHOSSEINIAN (Graduate Student Member, IEEE) received the bachelor's degree in computer engineering-software in Iran, the M.Sc. degree in computer network engineering from Halmstad University, Sweden, and the Post master's degree in communications for intelligent transport systems from Eurecom, France. He is currently pursuing the Ph.D. degree in electrical engineering and information technology with the Communication Networks Group, Technische Universität Ilmenau, Germany. His research interests include vehicular networks, intelligent transport systems, computer networks, and wireless and mobile networks and communications. JOCHEN...

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Section: Safety and Efficiencymentioning

confidence: 99%

A Comprehensive Survey on Cooperative Intersection Management for Heterogeneous Connected Vehicles

Gholamhosseinian

Seitz

2022

IEEE Access

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“…For example, when an AV needs to decelerate the system will first check if there is enough distance between this vehicle and the vehicle behind it to avoid sudden braking. If there is not enough distance for the AV to slow down, then the following AV needs to slow down too according to Equation (7). This logic flowchart is then converted to include mathematical symbols so that the system (in our case the simulation software) can read and apply it, as shown in Figure 6.…”

Section: Case (Ii) Av/ov Payoff Matrixmentioning

confidence: 99%

“…By using vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) technology an approaching AV is able to share information with a roadside unit (RSU) so that its speed can be controlled to avoid conflict as it safely goes through the intersection [5,6]. Depending on the vehicle and field conditions, the decision process may need to take into consideration factors such as approaching speed, distance and relative position to other vehicles and turning movement and dimensions of each vehicle [7]. Since this decision process is similar to strategy generations in game theory, we have followed this method to build the payoff matrix for each different combination of factors.…”

Section: Introductionmentioning

confidence: 99%

Intersection Control and Delay Optimization for Autonomous Vehicles Flows Only as Well as Mixed Flows with Ordinary Vehicles

Baz

Qurashi

2020

Vehicles

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The rapidly improving autonomous vehicle (AV) technology will have a significant impact on traffic safety and efficiency. This study introduces a game-theory-based priority control algorithm for autonomous vehicles to improve intersection safety and efficiency with mixed traffic. By using vehicle-to-infrastructure (V2I) communications, this model allows an AV to exchange information with the roadside units (RSU) to support the decision making of whether an ordinary vehicle (OV) or an AV should pass the intersection first. The safety of vehicles is taken in different stages of decisions to assure collision-free intersection operations. Two different mathematical models have been developed, where model one is for an AV/AV situation and model two is when an AV meets an OV. A simulation model was developed to implement the algorithm and compare the performance of each model with the conventional traffic control at a four-legged signalized intersection and at a roundabout. Three levels of traffic volume and speed combinations were tested in the simulation. The results show significant reductions in delay for both cases; for case (I), AV/AV model, a 65% reduction compared to a roundabout and 84% compared to a four-legged signalized intersection, and for case (II), AV/OV model, the reduction is 30% and 89%, respectively.

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“…Other examples are using approximations for the mean queue length (see e.g. [5] and [6] for such a strategy applied to respectively railway systems and platoon forming algorithms for selfdriving vehicles); the use of Markov decision theory, see e.g. [7], [8]; direct use of (micro-)simulations, see e.g.…”

Section: Introductionmentioning

confidence: 99%

New vehicle-actuated access algorithms for intersections close to oversaturation

Timmerman¹,

Boon²

2020

Preprint

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Optimal traffic-light settings are generally hard to obtain, certainly for actuated access control of an intersection. Typically, computationally expensive (microscopic) simulations or complicated optimization schemes are required to find those optimal settings. Based on recent developments regarding the Fixed-Cycle Traffic-Light (FCTL) queue, we propose a new allocation scheme for actuated access control at isolated intersections. Our scheme allows for very easy computations and an intuitive explanation, which are both based on the Central Limit Theorem, a key tool in probability theory. The desirable properties observed for the FCTL queue can also be achieved in case of actuated access control of an intersection. We show this by means of simulation of the underlying queueing model, because the actuated control defies an exact analysis so far. We also observe the same type of results employing the microscopic traffic simulator SUMO. The intuition and insights obtained might also open up new possibilities for obtaining optimal actuated access control for a network of intersections.

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Platoon forming algorithms for intelligent street intersections

Cited by 26 publications

References 31 publications

A Comprehensive Survey on Cooperative Intersection Management for Heterogeneous Connected Vehicles

A Comprehensive Survey on Cooperative Intersection Management for Heterogeneous Connected Vehicles

Intersection Control and Delay Optimization for Autonomous Vehicles Flows Only as Well as Mixed Flows with Ordinary Vehicles

New vehicle-actuated access algorithms for intersections close to oversaturation

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