Driver Distraction Recognition-driven Collision Avoidance Algorithm for Active Vehicle Safety

Devika, K. B.; Bera, Asish; Yellapantula, Venkata Ramani Shreya; Behera, Ardhendu; Liu, Yonghuai; Subramanian, Shankar C.

doi:10.1109/itsc48978.2021.9564648

Cited by 1 publication

(3 citation statements)

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“…The establishment of the driving safety distance monitoring and collision avoidance control model is affected by many factors, and the establishment methods are also diverse. There are traditional models based on mathematics and practice and models based on intelligent algorithms [33], such as the stereo vision algorithm [34]. The establishment and integration of a general virtual simulation system can only verify a model related to the simulation system.…”

Section: Intelligent Driver Model-avoidance Structurementioning

confidence: 99%

“…The establishment and integration of a general virtual simulation system can only verify a model related to the simulation system. With the rapid development of intelligent technology, the establishment of smart vehicle safety distance monitoring and collision avoidance control models is also constantly updated and optimized [34]. So it is required that the safety distance monitoring and collision avoidance virtual simulation system can be embedded in multiple control models to verify the control effect under different models.…”

Section: Intelligent Driver Model-avoidance Structurementioning

confidence: 99%

“…1) Communication distance, 5G vehicle networking V2V communication maximum distance approximately 800 m, which can solve IEEE 802.11p short-lived, discontinuous connection problems in vehicle ad hoc network communications. Especially it is a non-line-of-sight (NLOS) ring that encounters large objects occlusion during communication, under the border [31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46].…”

Section: E Better Communication Qualitymentioning

confidence: 99%

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Intelligent Driver Model-Based Vehicular Ad Hoc Network Communication in Real-Time Using 5G New Radio Wireless Networks

et al. 2023

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Vehicular ad hoc networks (VANETs) are self-organizing, open-structure inter-vehicle communication networks, along with wireless communication technology and transportation. Vehicle communication aims to improve the driver's response-ability and ensure traffic safety when encountering traffic accidents. The 5G NR on V2V communication, compared to fourth-generation (4G) long-term evolution (LTE), is more sophisticated and has ultra-high reliability. This research proposes intelligent driver model-lane changes (IDM-LC) and driver model-avoidance (IDM-A) models, which enhance the performance accuracy of the V2V communication through the 5G NR system. In this case, the authenticity of the vehicle movement models is tested on different road scenarios, i.e., square, hexagon, heptagon and triangle. In these scenarios, the vehicles' movements over the 5G networks receive widespread coverage whenever the vehicles receive signals from the roadside unit (RSU). Hence, the flexibility of VANET is used to improve the device-to-device (D2D) or vehicle-to-vehicle (V2V) communication efficiency in the fifth-generation (5G) new radio (NR) system. In addition, the VANET simulation platform, i.e., simulation of urban mobility (SUMO) and network simulator-3 (NS-3), simulate and evaluate the comparison of V2V through the 5G networks, which receives widespread coverage in 15 to 20 m/s. The simulation results and analysis show that the V2V communication through the 5G system performs better on the IDM models.INDEX TERMS Vehicular ad hoc network, fifth generation, vehicle-to-vehicle, internet of vehicles, intelligent driver model, SUMO, NS-3

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Section: Intelligent Driver Model-avoidance Structurementioning

confidence: 99%

Section: Intelligent Driver Model-avoidance Structurementioning

confidence: 99%