Autonomous Vehicle Decision-Making and Control in Complex and Unconventional Scenarios—A Review

Sana, Faria; Azad, Nasser L.; Raahemifar, Kaamran

doi:10.3390/machines11070676

Cited by 12 publications

(6 citation statements)

References 110 publications

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“…In [16], Sana et al show that the use of machine learning and graphs in the synthesis of autonomous vehicle control ensures the safety of the vehicle's movement in unfavorable weather conditions, intersections without signals, pedestrian crossings, roundabouts, and various situations in which there is a threat of collisions.…”

Section: State Of Knowledgementioning

confidence: 99%

Computational Intelligence Supporting the Safe Control of Autonomous Multi-Objects

Lisowski

2024

Electronics

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The essence of this work, which is an extension of the author’s previous research, is an analysis of computational intelligence algorithms that the support safe control of an autonomous object moving in a large group of other autonomous objects. Linear and dynamic programming methods with neural constraints on the process state, as well as positional and matrix game methods, were used to synthesize computational algorithms for the safe trajectory of one’s own object. The aim of the comparative analysis of intelligent computational methods for the safe trajectory of an object was to show, through their use, the possibility of taking into account the risk of collision resulting from both the degree of cooperation of objects while observing traffic laws and the impact of the environment in the form of visibility and the complexity of the situation. Simulation tests of the algorithms were carried out on the example of a real navigation situation of several dozen objects passing each other at sea.

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Section: State Of Knowledgementioning

confidence: 99%

Computational Intelligence Supporting the Safe Control of Autonomous Multi-Objects

Lisowski

2024

Electronics

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“…However, navigating these vehicles in complex and unconventional scenarios is still a major challenge. The most difficult scenarios for AV algorithms, as well as human drivers, to react to were found to be harsh weather conditions, unsignalized intersections, traversing crosswalks, navigating roundabouts, and near-accident situations [36].…”

Section: Technological Overview Of Autonomous Vehiclesmentioning

confidence: 99%

Driving Sustainability: Carbon Footprint, 3D Printing, and Legislation concerning Electric and Autonomous Vehicles

Jovanović,

Mateo Sanguino,

Damjanović

et al. 2023

Sensors

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In recent years, there has been a remarkable development in the technology and legislation related to electric and autonomous vehicles (i.e., EVs/AVs). This technological advancement requires the deployment of the most up-to-date supporting infrastructure to achieve safe operation. Further infrastructure is needed for Level 5 vehicles, namely the introduction of super-fast wireless 5G technology. To achieve harmony between the rapid technological advancement of EVs/AVs and environmental preservation, enacting legislation related to their sustainable use is vital. Thus, this manuscript provides a review of the technological development of EVs/AVs, with a special focus on carbon footprints and the implementation of additive manufacturing using recycled materials. While EVs have a 12.13% increased carbon footprint compared to conventional vehicles, AVs with basic and advanced intelligence features have an increased carbon footprint of 41.43% and 99.65%, respectively. This article emphasizes that the integration of 3D-printed components has the potential to offset this impact with a substantial 60% reduction. As a result, custom-made solutions involving 3D printing are explored, leading to greater speed, customization, and cost-effectiveness for EVs/AVs. This article also lists the advantages and disadvantages of the existing legislation in Spain, the United Kingdom, and the western Balkans, demonstrating various approaches to promoting electric mobility and the development of autonomous vehicles. In Spain, initiatives like the MOVES program incentivize EV adoption, while the UK focuses on expanding the EV market and addressing concerns about EVs’ quiet operation. In the western Balkans, the adoption of legislation lags behind, with limited incentives and infrastructure for EVs. To boost sales, legal mechanisms are necessary to reduce costs and improve accessibility, in addition to offering subsidies for the purchase of EVs. To this end, an analysis of the incentive measures proposed for the development and use of renewable power sources for the supply of energy for EVs/AVs is presented.

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“…Decision trees were used in [20] to model human decision-making in handling round intersections. However, handling round intersections is not very easy for human drivers either, according to [21]. This is due to the difficulty in detecting and tracking the other vehicles in the round intersection due to the round geometry and occlusions of view [22,23].…”

Section: Related Workmentioning

confidence: 99%

Autonomous Vehicle Decision-Making with Policy Prediction for Handling a Round Intersection

Li,

Guvenc,

Aksun-Guvenc

2023

Electronics

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Autonomous shuttles have been used as end-mile solutions for smart mobility in smart cities. The urban driving conditions of smart cities with many other actors sharing the road and the presence of intersections have posed challenges to the use of autonomous shuttles. Round intersections are more challenging because it is more difficult to perceive the other vehicles in and near the intersection. Thus, this paper focuses on the decision-making of autonomous vehicles for handling round intersections. The round intersection is introduced first, followed by introductions of the Markov Decision Process (MDP), the Partially Observable Markov Decision Process (POMDP) and the Object-Oriented Partially Observable Markov Decision Process (OOPOMDP), which are used for decision-making with uncertain knowledge of the motion of the other vehicles. The Partially Observable Monte-Carlo Planning (POMCP) algorithm is used as the solution method and OOPOMDP is applied to the decision-making of autonomous vehicles in round intersections. Decision-making is formulated first as a POMDP problem, and the penalty function is formulated and set accordingly. This is followed by an improvement in decision-making with policy prediction. Augmented objective state and policy-based state transition are introduced, and simulations are used to demonstrate the effectiveness of the proposed method for collision-free handling of round intersections by the ego vehicle.

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Autonomous Vehicle Decision-Making and Control in Complex and Unconventional Scenarios—A Review

Cited by 12 publications

References 110 publications

Computational Intelligence Supporting the Safe Control of Autonomous Multi-Objects

Computational Intelligence Supporting the Safe Control of Autonomous Multi-Objects

Driving Sustainability: Carbon Footprint, 3D Printing, and Legislation concerning Electric and Autonomous Vehicles

Autonomous Vehicle Decision-Making with Policy Prediction for Handling a Round Intersection

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