Lateral control of autonomous vehicles based on fuzzy logic

Wang, Xinyu; Fu, Mengyin; Ma, Hongbin; Yang, Yi

doi:10.1016/j.conengprac.2014.09.015

Cited by 111 publications

(27 citation statements)

References 27 publications

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“…Atitinkamai ir šiame darbe naudojamas supaprastintas -dviratis -transporto priemonės kinematinis modelis (2 pav.). Bendruoju atveju tiek autonominės transporto priemonės tariamo realaus judėjimo vektorius, tiek pageidaujamos judėjimo trajektorijos koordinačių vektorius yra išreiškiami (Wang et al 2014…”

Section: Pirminis Ir Antrinis Matematiniai Modeliaiunclassified

“…Svarbu tai, kad padanga yra elastingas besideformuojantis kūnas, o jos ir kelio sąlyčio zonoje veikia sankybio jėgos, todėl grynojo rato riedėjimo be slydimo prielaida modeliuojant nėra racionali. Moksliniuose darbuose iš dalies ši problema sprendžiama kinematiniame modelyje įvertinant įstrižojo riedėjimo kampą transporto priemonės sunkio centre ar kitame pasirinktame taške (Rajamani 2012;Wang et al 2014). Taikant kinematinį modelį, realaus judėjimo koordinačių kitimas yra charakterizuojamos taip (Rajamani 2012): ( ) …”

Section: Pirminis Ir Antrinis Matematiniai Modeliaiunclassified

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Formulation and Theoretical Analysis of the Control Algorithm of the Autonomous Vehicle

Skačkauskas

Mejeras

Sokolovskij

2017

Science - Future of Lithuania

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2017 © Straipsnio autoriai. Leidėjas VGTU leidykla "Technika". Šis straipsnis yra atvirosios prieigos straipsnis, turintis Kūrybinių bendrijų (Creative Commons) licenciją (CC BY-NC 4.0), kuri leidžia neribotą straipsnio ar jo dalių panaudą su privaloma sąlyga nurodyti autorių ir pirminį šaltinį. Straipsnis ar jo dalys negali būti naudojami komerciniams tikslams. parametrai vis labiau nukrypsta nuo nustatytų. Remiantis šiuo apibrėžimu galima teigti, kad autonominės transporto priemonės judėjimas yra nestabilus, jeigu judėjimo metu, nustojus veikti išoriniams veiksniams, esamos realiojo judė-jimo koordinatės vis labiau nutolsta nuo pageidaujamų, t. y. didėja koordinačių nuokrypio vektoriaus elementų reikš-mės. Tokiu atveju naudojamas valdymo algoritmas turi įver-tinti nuokrypos dydį, t. y. koordinačių nuokrypio vektoriaus elementų reikšmes ir, atsižvelgiant į taikomą optimizavimo kriterijų ar jų sistemą, priimti racionalų ir patikimą valdymo sprendimą, kuris užtikrintų nuokrypos panaikinimą ar sumažinimą. Taigi yra aišku, kad, siekiant užtikrinti kuo didesnį judėjimo tikslumą ir stabilumą, veikiant įvairiems išoriniams veiksniams, autonominės transporto priemonės analizuojamos kaip tarpdisciplininis objektas, išskiriant ryšius tarp transporto priemonių dinamikos ir automatinio valdymo teorijos. MOKSLAS -LIETUVOS ATEITIS SCIENCE -FUTURE OF LITHUANIAChappell (1983) vienas pirmųjų autonominę transporto priemonę aprašė ne kaip vientisą, o kaip kompleksinį tyrimų objektą, sudarytą iš skirtingų sistemų, iš kurių kiekviena atlieka atskiras funkcijas, tačiau sąveikauja tarpusavyje. Tik matematiniu modeliavimu paremtas intelektinis valdymo algoritmas buvo pritaikytas mokslininkų Hogle ir Bonissone (1984 Reikšminiai žodžiai: autonominis automobilis, genetinis algoritmas, judėjimo trajektorijos sekimas, nuokrypis.

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Section: Pirminis Ir Antrinis Matematiniai Modeliaiunclassified

Formulation and Theoretical Analysis of the Control Algorithm of the Autonomous Vehicle

Skačkauskas

Mejeras

Sokolovskij

2017

Science - Future of Lithuania

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“…Autonomous land vehicles (ALVs) have attracted enormous attention in the past decades since the key technologies of ALVs, such as intelligent sensing, planning and control [1]- [5], can be widely applied in intelligent transportation systems, driver assistance systems, military tasks and other fields. Motion control, which mainly fulfils the tracking task of driving the vehicle to achieve the desired path and the desired speed, is an important part among the major technologies in ALVs.…”

Section: Introductionmentioning

confidence: 99%

“…In geometric methods, control rules are usually designed by studying the geometric relationship between the vehicle and the reference path. Geometric methods mainly comprise the pure pursuit, the vector pursuit and the Stanley method [1], [6]- [8]. The pure pursuit method and its variations have been widely studied and employed due to their easy implementation and robustness to larger errors.…”

Section: Introductionmentioning

confidence: 99%

“…In the pure pursuit method and its variations, a look-ahead distance to measure error ahead of the vehicle is often utilized. In [1] and [6], fixed look-ahead distances were used and in [2] and [9], look-ahead distances were dynamically tuned with the vehicle's speeds. The vector pursuit method makes use of the screw theory and is similar to the pure pursuit method [7].…”

Section: Introductionmentioning

confidence: 99%

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Lateral Control for Autonomous Land Vehicles via Dual Heuristic Programming

Huang¹,

Lian

et al. 2016

International Journal of Robotics and Automation

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A novel robust event‐triggered fault tolerant automatic steering control approach of autonomous land vehicles under in‐vehicle network delay

Zhang

et al. 2021

Intl J Robust & Nonlinear

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This paper proposes a novel robust event-triggered fault tolerant automatic steering control strategy for autonomous land vehicles to achieve path tracking and vehicle lateral motion control under in-vehicle network delay. From the practical point of view, the parameter uncertainties, time delay, and actuator fault are simultaneously introduced to make the designed controller robust to more extensive and challenging driving conditions. A novel polytope reduction and norm-bounded uncertainty reduction method is used to effectively handle the time-varying velocity and tire cornering stiffness uncertainties. Then, the uncertain vehicle model can be reconstructed as an uncertain network control system model with time delay and actuator fault. Due to the inevitable time delay and actuator fault, a new cubic absolute-value Lyapunov function is developed to guarantee the asymptotical stability of the closed control system with the H∞ performance, and the modified project-based adaptive law is applied to strengthen the fault tolerant ability. Furthermore, a progressive event-triggered mechanism is proposed for the collaborative design of robust fault tolerant automatic steering controller, which can signally improve the communication resource utilization of the limited bandwidth in-vehicle network. Finally, the performance comparisons of different controllers are presented. These results prove that the proposed controller can simultaneously guarantee the path tacking performance and lateral dynamics stability, and save the communication resource of the in-vehicle network. K E Y W O R D Sevent-triggered mechanism, fault tolerant, parameter uncertainties, robust automatic steering control, time delay INTRODUCTIONRecently, as a progressive technology of the automotive industry, autonomous land vehicles (ALVs) have attracted growing attention due to their potential applications in civilian and military fields. 1,2 The ALVs can be used to improve vehicle

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Lateral control of autonomous vehicles based on fuzzy logic

Cited by 111 publications

References 27 publications

Formulation and Theoretical Analysis of the Control Algorithm of the Autonomous Vehicle

Formulation and Theoretical Analysis of the Control Algorithm of the Autonomous Vehicle

Lateral Control for Autonomous Land Vehicles via Dual Heuristic Programming

A novel robust event‐triggered fault tolerant automatic steering control approach of autonomous land vehicles under in‐vehicle network delay

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