Enhancements of SDR-Based FPGA System for V2X-VLC Communications

Danys, Lukáš; Martínek, Radek; Jaroš, René; Baroš, Jan; Simonik, Petr; Snåšel, Václav

doi:10.32604/cmc.2021.017333

Cited by 2 publications

(2 citation statements)

References 36 publications

(53 reference statements)

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“…Under 5G-V2X smart road infrastructure, when ICV starts autonomous driving, the global path planning module firstly utilizes GPS/INS positioning information and road network document (RND) to search vehicle position code, current road code or field driving code. Subsequently, by including a mission document (MD), this module plans a task and a series of implementable actions for traveling along this special road or field [12]. In this article, we focus on developing a cerebrum-like decision-making model for ICV self-driving system design.…”

Section: Introductionmentioning

confidence: 99%

Modeling and TOPSIS-GRA Algorithm for Autonomous Driving Decision-Making Under 5G-V2X Infrastructure

Fu¹,

Fu²

2023

Computers, Materials &Amp; Continua

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This paper is to explore the problems of intelligent connected vehicles (ICVs) autonomous driving decision-making under a 5G-V2X structured road environment. Through literature review and interviews with autonomous driving practitioners, this paper firstly puts forward a logical framework for designing a cerebrum-like autonomous driving system. Secondly, situated on this framework, it builds a hierarchical finite state machine (HFSM) model as well as a TOPSIS-GRA algorithm for making ICV autonomous driving decisions by employing a data fusion approach between the entropy weight method (EWM) and analytic hierarchy process method (AHP) and by employing a model fusion approach between the technique for order preference by similarity to an ideal solution (TOPSIS) and grey relational analysis (GRA). The HFSM model is composed of two layers: the global FSM model and the local FSM model. The decision of the former acts as partial input information of the latter and the result of the latter is sent forward to the local pathplanning module, meanwhile pulsating feedback to the former as real-time refresh data. To identify different traffic scenarios in a cerebrum-like way, the global FSM model is designed as 7 driving behavior states and 17 driving characteristic events, and the local FSM model is designed as 16 states and 8 characteristic events. In respect to designing a cerebrum-like algorithm for state transition, this paper firstly fuses AHP weight and EWM weight at their output layer to generate a synthetic weight coefficient for each characteristic event; then, it further fuses TOPSIS method and GRA method at the model building layer to obtain the implementable order of state transition. To verify the feasibility, reliability, and safety of the HFSM model as well as its TOPSIS-GRA state transition algorithm, this paper elaborates on a series of simulative experiments conducted on the PreScan8.50 platform. The results display that the accuracy of obstacle detection gets 98%, lane line prediction is beyond 70 m, the speed of collision avoidance is higher than 45 km/h, the distance of collision avoidance is less than 5 m, path planning time for obstacle avoidance is averagely less than 50 ms, and brake deceleration is controlled under 6 m/s 2 . These technical indexes support that the driving states set and characteristic events set for the HFSM model as well as its TOPSIS-GRA algorithm may 1052 CMC, 2023, vol.75, no.1 bring about cerebrum-like decision-making effectiveness for ICV autonomous driving under 5G-V2X intelligent road infrastructure.

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Section: Introductionmentioning

confidence: 99%

Modeling and TOPSIS-GRA Algorithm for Autonomous Driving Decision-Making Under 5G-V2X Infrastructure

Fu¹,

Fu²

2023

Computers, Materials &Amp; Continua

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“…An overview of related works is given in Tab. I. Software-defined radio (SDR) [19], [23]- [25] and virtual instrumentation [26], [27] are slowly gaining on importance in the VLC area. The results presented in these publications [19], [23]- [27] are based on measurements of commercial LED and automotive lights for which the luminescent layer parameters are not specified.…”

Section: Introductionmentioning

confidence: 99%

Measurement of the Effect of Luminescent Layer Parameters on Light and Communication Properties

Jargus

Tomis

Baroš

et al. 2022

IEEE Trans. Instrum. Meas.

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This publication describes the measurement of the effect of selected luminescent layer parameters on the light and communication characteristics of light generated by a luminescent layer using a light emitting diode (LED) as a radiation source. The luminescent layers were implemented based on a combination of polydimethylsiloxane (PDMS) polymer and YAG:Ce and CaS:Eu phosphors by spin coating. For the chosen weight ratios of PDMS and phosphors, a set of test samples of luminescent layers was implemented whose thicknesses differed from each other in the order of units to tens of micrometres. Experimental measurements have clearly shown that even a slightest change in the thickness of the luminescent layer has a non-negligible effect on the change of the luminous and communication parameters of the light generated by the luminescent layer. The colorimetric parameters of the colour colorimetry temperature (CCT), colour rendering index (CRI) and colour coordinates x, y (CIE 1931) were recorded for the investigated luminescent samples. The communication parameters were evaluated by measuring the error vector magnitude (EVM), modulation error ratio (MER), phase error, bit error rate (BER) and normalised signal-to-noise ratio E b /N0.

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Enhancements of SDR-Based FPGA System for V2X-VLC Communications

Cited by 2 publications

References 36 publications

Modeling and TOPSIS-GRA Algorithm for Autonomous Driving Decision-Making Under 5G-V2X Infrastructure

Modeling and TOPSIS-GRA Algorithm for Autonomous Driving Decision-Making Under 5G-V2X Infrastructure

Measurement of the Effect of Luminescent Layer Parameters on Light and Communication Properties

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