Intelligent systems which could assist the driver and reduce their total workload are the popular research topic nowadays. These intelligent systems are the advanced driver assistance system (ADAS), which are being researched intensively to provide a better driving experience, increased road safety, and better comfort during the journey. Most of these systems aim to provide partial or full driver assistance, such as longitudinal control, parking assistance, and lane keeping. Among these systems, the longitudinal control is often known as adaptive cruise control (ACC). The ACC adjusts its speed autonomously according to the traffic conditions, to keep a safe distance behind the lead vehicle. The proposed model of ACC uses constant time gap and ego velocity to calculate safe distance and provides two modes of control—speed control and spacing control. The vehicle dynamics model is designed using the MathWorks Simulink, the road scene is generated using the MathWorks Roadrunner software, scenario generation is done using the driving scenario designer app, and the virtual 3D simulation is done with the Unreal engine editor, thus the system works in co-simulation of the MathWorks and Unreal engine editor. The validation of the developed algorithm is also detailed in the paper.


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    Titel :

    Development and Validation of Adaptive Cruise Control Algorithm for ADAS Applications


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Kumar, Sandeep (Herausgeber:in) / Balachandran, K. (Herausgeber:in) / Kim, Joong Hoon (Herausgeber:in) / Bansal, Jagdish Chand (Herausgeber:in) / Hari Priyadharshini, A. (Autor:in) / Khan, Jihas (Autor:in) / Sreedharan, Pramod (Autor:in)

    Kongress:

    Congress on Intelligent Systems ; 2023 ; Bengaluru, India September 04, 2023 - September 05, 2023



    Erscheinungsdatum :

    31.03.2024


    Format / Umfang :

    16 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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