Applying a Functional Neurofuzzy Network to Real-Time Lane Detection and Front-Vehicle Distance Measurement

Wu, Chi-Feng; Lin, Cheng‐Jian; Lee, Chi-Yung

doi:10.1109/tsmcc.2011.2166067

Cited by 60 publications

(5 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It does not warn the driver if he or she intentionally crosses the lane (by turning on the turn signal) [36]. As in [37], the information about the surrounding lane is detected by sector detection, and the degree of deviation is calculated using an angular relationship to judge the degree of lane deviation, and at the same time the distance to the vehicle in front is determined by identifying the shadow and tail lights of the vehicle in front. The purpose of lane change overtaking warning is to assist the driver in making a safe lane change through additional technical means, the core of which is blind spot detection [38].…”

Section: Intelligent Decision Making Of Intelligent Connected Vehiclesmentioning

confidence: 99%

Recent Progress on Digital Twins in Intelligent Connected Vehicles: A Review

Chai,

Yan,

Zhang

et al. 2024

ELEKTRON ELEKTROTECH

View full text Add to dashboard Cite

As an important enabling technology in the era of Industry 4.0, the intelligent connected vehicle (ICV) facilitates robust data interaction with the outside through sensors and communication technologies, ultimately making scientific decisions based on environmental perception information. However, due to constraints such as limited communication bandwidth and computing resources, the influx of data simultaneously impedes the sustainable optimisation of the vehicle decision making process at the same time. As a novel technology that effectively connects physical and virtual space, the special ability of the digital twin (DT) is to identify characteristics within a certain lifecycle, thereby garnering widespread attention across various industries. The purpose of this paper is to review the contribution of digital twins in the application field of intelligent vehicles and explore its potential for development. First, the key technologies of ICV provide a basis for the embedding of digital twins. Then, by analysing the development process and technical composition of digital twins, readers can better understand the concept of digital twins. Finally, the application of DTs in ICV is reviewed from the perspective of vehicles, traffic facilities, and occupants. Future challenges and opportunities in this direction are described at the same time.

show abstract

Section: Intelligent Decision Making Of Intelligent Connected Vehiclesmentioning

confidence: 99%

Recent Progress on Digital Twins in Intelligent Connected Vehicles: A Review

Chai,

Yan,

Zhang

et al. 2024

ELEKTRON ELEKTROTECH

View full text Add to dashboard Cite

show abstract

“…In [32] the relative positions of vehicles are determined using a fuzzy NN. The network receives processed data from a camera and from a scanner.…”

Section: Driver Behaviour and Autonomous Vehiclesmentioning

confidence: 99%

Neural Networks in Transportation Research – Recent Applications

Pamuła¹

2017

Transport Problems

View full text Add to dashboard Cite

Summary. Neural networks' (NNs) capability of mapping the nonlinear functions of variables describing the behaviour of objects and the simplicity of designing their configuration favours their applications in transport. This paper presents representative examples in the scope of prediction of road traffic parameters, road traffic control, measurement of road traffic parameters, driver behaviour and autonomous vehicles, and transport policy and economics. The features of the solutions are examined. The review shows that feedforward multilayer neural networks are the most often utilised configurations in transportation research. No systematic approach is reported on the optimisation of the NN configurations to achieve a set level of performance in solving modelling tasks. ZASTOSOWANIE SIECI NEURONOWYCH W BADANIACH W TRANSPORCIE -OSTATNIE OPRACOWANIAStreszczenie. Zdolność sieci neuronowej do odwzorowania nieliniowych zależności między zmiennymi, które opisują zachowanie obiektów, oraz łatwość opracowania efektywnej konfiguracji sprzyjają zastosowaniom ich w transporcie. W artykule przedstawiono reprezentatywne przykłady z zakresu: predykcji parametrów ruchu drogowego, sterowania ruchem drogowym, pomiarów parametrów ruchu, zachowania kierowców i prowadzenia autonomicznych pojazdów, ekonomii i polityki transportowej, oraz omówiono własności proponowanych rozwiązań. Przegląd wskazuje, że najczęściej wybieranymi sieciami neuronowymi są sieci jednokierunkowe wielowarstwowe. Brak jest systematycznego podejścia do optymalizacji konfiguracji sieci w celu osiągnięcia zadanego poziomu dokładności w zadaniach modelowania.

show abstract

“…Some researches [15][16][17] used a similar quantization approach to merge vicinal lines. The approach used in [15][16][17] computed dis1 and dis2, then according to threshold for discretizing dis.…”

Section: Fitting Lanementioning

confidence: 99%

“…The approach used in [15][16][17] computed dis1 and dis2, then according to threshold for discretizing dis. This procedure is similar to the quantization of q in our approach.…”

Section: Fitting Lanementioning

confidence: 99%