Tuning of Look-ahead Cruise Control in HIL Vehicle Simulator

Mihály, András; Baranyi, Márk; Németh, Balázs; Gáspár, Péter

doi:10.3311/pptr.9897

Cited by 5 publications

(2 citation statements)

References 8 publications

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“…Cost-effectiveness is a major driving force in both development and production. A considerable part of the development and testing of autonomous functions are done in simulated environments [ 3 , 4 ]. For vehicular applications, it is an essential requirement to run an algorithm in real time.…”

Section: Introductionmentioning

confidence: 99%

PHD Filter for Object Tracking in Road Traffic Applications Considering Varying Detectability

Törő

Bécsi

Gáspár

2021

Sensors

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This paper considers the object detection and tracking problem in a road traffic situation from a traffic participant’s perspective. The information source is an automotive radar which is attached to the ego vehicle. The scenario characteristics are varying object visibility due to occlusion and multiple detections of a vehicle during a scanning interval. The goal is to maintain and report the state of undetected though possibly present objects. The proposed algorithm is based on the multi-object Probability Hypothesis Density filter. Because the PHD filter has no memory, the estimate of the number of objects present can change abruptly due to erroneous detections. To reduce this effect, we model the occlusion of the object to calculate the state-dependent detection probability. Thus, the filter can maintain unnoticed but probably valid hypotheses for a more extended period. We use the sequential Monte Carlo method with clustering for implementing the filter. We distinguish between detected, undetected, and hidden particles within our framework, whose purpose is to track hidden but likely present objects. The performance of the algorithm is demonstrated using highway radar measurements.

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Section: Introductionmentioning

confidence: 99%

PHD Filter for Object Tracking in Road Traffic Applications Considering Varying Detectability

Törő

Bécsi

Gáspár

2021

Sensors

Self Cite

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“…It supports the development process (V-model) with the application of Model in the Loop (MIL) and Hardware in the Loop (HIL) environments. MIL environments can be used to determine the system specifications based on the given requirements, such as in (Kako et al, 2007) and controller algorithms can also be designed and tested through MILs as it can be seen in (Németh and Gáspár, 2010;Ohata, 2009;Santillan-Galvan et al, 2004), then they can be tested in HILs (Deng et al, 2008;Mihály et al, 2017;Rabinovici et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Measurement Based Validation of an Electro-Pneumatic Gearbox Actuator

Szabo

Bécsi

Aradi

2019

Period. Polytech. Transp. Eng.

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The objective of the research is to analyze the behavior of the developed electro-pneumatic actuator model and compare it to the behavior of the real system. The actuator achieves the requested gear changes by moving the two pistons inside the cylinder and it is operated by three-way two-position solenoid valves. Since not all model parameters are exactly known, such as contraction coefficients and friction parameters, they can be estimated based on literature then they can be further tuned to minimize the error of the simulation. The developed nonlinear model is capable of describing the dynamic behavior of the gearbox actuator, thus it can be used to analyze the effects of constructional modifications and it can serve as Model in the Loop (MIL) environment for controller testing.

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