Design of Lane Keeping Algorithm of Autonomous Vehicle

Törő, Olivér; Bécsi, Tamás; Aradi, Szilárd

doi:10.3311/pptr.8177

Cited by 40 publications

(20 citation statements)

References 14 publications

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“…This algorithm can be applied to AV’s operation on various roads, including unpainted roads and roads with slight curves. Using both a linear algorithm and a non-linear algorithm, Töro et al. (2016) present the lane-keeping design and implementation of an automated and electric go-cart.…”

Section: Resultsmentioning

confidence: 99%

Mind the gap: Developments in autonomous driving research and the sustainability challenge

Mora

Guo

Panori³

2020

Journal of Cleaner Production

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Scientific knowledge on autonomous-driving technology is expanding at a faster-than-ever pace. As a result, the likelihood of incurring information overload is particularly notable for researchers, who can struggle to overcome the gap between information processing requirements and information processing capacity. We address this issue by adopting a multi-granulation approach to latent knowledge discovery and synthesis in large-scale research domains. The proposed methodology combines citation-based community detection methods and topic modelling techniques to give a concise but comprehensive overview of how the autonomous vehicle (AV) research field is conceptually structured. Thirteen core thematic areas are extracted and presented by mining the large data-rich environments resulting from 50 years of AV research. The analysis demonstrates that this research field is strongly oriented towards examining the technological developments needed to enable the widespread rollout of AVs, whereas it largely overlooks the wide-ranging sustainability implications of this sociotechnical transition. On account of these findings, we call for a broader engagement of AV researchers with the sustainability concept and we invite them to increase their commitment to conducting systematic investigations into the sustainability of AV deployment. Sustainability research is urgently required to produce an evidence-based understanding of what new sociotechnical arrangements are needed to ensure that the systemic technological change introduced by AV-based transport systems can fulfill societal functions while meeting the urgent need for more sustainable transport solutions.

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Section: Resultsmentioning

confidence: 99%

Mind the gap: Developments in autonomous driving research and the sustainability challenge

Mora

Guo

Panori³

2020

Journal of Cleaner Production

View full text Add to dashboard Cite

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“…Progress in the construction of means of transport depends on the increased requirements for road safety, especially where there is high traffic. Road safety is a complex issue related to the development of technical and IT measures [1][2][3] logistics and management [4,5] and legal regulations [6][7][8]. There are strong efforts on an EU level towards harmonizing the European vision on connected and automated vehicles for the following decades like the Gear 2030 initiative that technical, legislation and financing challenges [9].…”

Section: Introductionmentioning

confidence: 99%

“…Despite many years of research into the autonomy of vehicles, there are still various problems to be solved. On the technical side the lack of precise solutions for locating the vehicle position is a problem [7]. New solutions are sought, based e.g.…”

Section: Introductionmentioning

confidence: 99%

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Autonomous vans - the planning process of transport tasks

et al. 2020

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AbstractAutonomous vehicles are gaining more and more followers and are becoming a reality. Although the total change of the transport system to an autonomous one still remains a big challenge, the development of navigation, control and supervision systems for vehicles gives hope for an autonomous future. The article describes the rules for choosing a route and the process of outsourcing transport tasks. The formulas for calculating the values of indicators characterizing the transport process are provided in the simple case when vehicles move along a fixed route where there are no disturbances. Additionally, the theory of Markov random systems was used to determine the system capacity, average queue length for servicing and the average number of requests.

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“…In (Gietelink et al 2007) a HIL environment served for the development of intelligent driver assistant systems, while in (Deng et al, 2008) a laboratory environment has been developed to test and verify autonomous vehicle functions. In (Aradi et al, 2014) and (Törő et al, 2016) camera related autonomous vehicle functions have been tested in HIL environment with the intention of applying the developed algorithm on go-cart vehicle.…”

Section: Introductionmentioning

confidence: 99%