About auction strategies for intersection management when human-driven and autonomous vehicles coexist

Cabri, Giacomo; Gherardini, Luca; Montangero, Manuela; Muzzini, Filippo

doi:10.1007/s11042-020-10222-y

Cited by 13 publications

(3 citation statements)

References 21 publications

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“…In contrast, in this paper we study the impact of the coexistence of next-generation vehicles with traditional vehicles, and propose approaches that are able to support both types of vehicles. Such a scenario was first addressed in the milestone paper [6], and subsequently in [17]. Here, however, we exploit already existing city infrastructure and take into consideration all vehicles in the lanes, not only the first ones approaching an intersection.…”

Section: Related Workmentioning

confidence: 99%

Exploiting Traffic Light Coordination and Auctions for Intersection and Emergency Vehicle Management in a Smart City Mixed Scenario

Muzzini,

Montangero

2024

Sensors

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IoT (Internet-of-Things)-powered devices can be exploited to connect vehicles to smart city infrastructure, allowing vehicles to share their intentions while retrieving contextual information about diverse aspects of urban viability. In this paper, we place ourselves in a transient scenario in which next-generation vehicles that are able to communicate with the surrounding infrastructure coexist with traditional vehicles with limited or absent IoT capabilities. We focus on intersection management, in particular on reusing existing traffic lights empowered by a new management system. We propose an auction-based system in which traffic lights are able to exchange contextual information with vehicles and other nearby traffic lights with the aim of reducing average waiting times at intersections and consequently overall trip times. We use bid propagation to improve standard vehicle trip times while allowing emergency vehicles to free up the way ahead without needing ad hoc system for such vehicle, only an increase in their budget. The proposed system is then tested against two baselines: the classical Fixed Time Control system currently adopted for traffic lights, and an auction strategy that does not exploit traffic light coordination. We performed a large set of experiments using the well known MATSim transport simulator on both a synthetic Manhattan map and on a map we built of an urban area located in Modena, Northern Italy. Our results show that the proposed approach performs better than the classical fixed time control system and the auction strategy that does not exploit coordination among traffic lights.

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Section: Related Workmentioning

confidence: 99%

Exploiting Traffic Light Coordination and Auctions for Intersection and Emergency Vehicle Management in a Smart City Mixed Scenario

Muzzini,

Montangero

2024

Sensors

Self Cite

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“…These methods either control the vehicles in a centralized manner, or establish a cooperative mechanism among vehicles for fully autonomous vehicles flow. Intersection management for mixed traffic flow is considered by Arvin et al [14] and Cabri et al [15] etc. These researches propose a negotiation or coordination mechanism for the vehicles group, either between CAVs or between CAV and HDV.…”

Section: Literature Reviewmentioning

confidence: 99%

“…[14] and Cabri et al. [15] etc. These researches propose a negotiation or coordination mechanism for the vehicles group, either between CAVs or between CAV and HDV.…”

Section: Introductionmentioning

confidence: 99%

Deadlock detection, cooperative avoidance and recovery protocol for mixed autonomous vehicles in unstructured environment

Song

Huang

et al. 2023

IET Intelligent Trans Sys

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Deadlock is an extreme traffic flow operational state during rush hours. Many literatures have studied autonomous vehicle coordination under the umbrella of deadlock‐free conditions. These researches either assume the trajectories are fixed or state spaces are discrete and limited on structured road spaces or don't consider the influence of human‐driven vehicles (HDV), which are not controllable from the system's viewpoint. This manuscript relaxes the above limitations and proposes a method to detect, avoid, and recover from deadlock for mixed autonomous vehicles flow. Firstly, two types of deadlocks, weak and strong , are defined based on deadlock properties. Next, two detection algorithms based on evasion distance propagation are proposed. After that, we present a cooperative control method to avoid deadlock based on chain‐spillover‐free and loop‐free strategies. If a deadlock has already happened, cooperative protocols based on re‐routing and backward‐forward strategies are designed. The proposed model is tested in Carla. The results show that the deadlocks can be detected 13 seconds earlier than their occurrence, and it takes about 6 seconds to unlock the existing deadlock. The results also show that with the proposed deadlock avoidance algorithm, the traffic throughput can be increased by 35.7%, and with the proposed deadlock recovery protocol, the traffic throughput can be increased by another 18%.

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Study of the Hazard Perception Model for Automated Driving Systems

Wang,

Tian

2022

HCI in Mobility, Transport, and Automotive Systems

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About auction strategies for intersection management when human-driven and autonomous vehicles coexist

Cited by 13 publications

References 21 publications

Exploiting Traffic Light Coordination and Auctions for Intersection and Emergency Vehicle Management in a Smart City Mixed Scenario

Exploiting Traffic Light Coordination and Auctions for Intersection and Emergency Vehicle Management in a Smart City Mixed Scenario

Deadlock detection, cooperative avoidance and recovery protocol for mixed autonomous vehicles in unstructured environment

Study of the Hazard Perception Model for Automated Driving Systems

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