Adaptive Headlight System for accident prevention

Shreyas, S; Raghuraman, Kirthanaa; Ap, Padmavathy; Prasad, S.; Devaradjane, G.

doi:10.1109/icrtit.2014.6996191

Cited by 19 publications

(6 citation statements)

References 4 publications

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“…6. SSEV Hardware adaptive Headlight system the matrix is adjusted as per the movement of the car in front the moment of the headlight while steering is optimal to cover blind spots [10]. When the Fig.…”

Section: Resultsmentioning

confidence: 99%

Semi-Autonomous Smart Electric Vehicle with AI based Drive Assistance

Sonar

2024

IJSREM

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In our research, we propose a practical methodology design and implementation of a semi-autonomous smart electric vehicle (EV) equipped with advanced features such as AI-based pothole detection, a robust battery management system (BMS), self-parking capability, and intelligent headlight intensity control. The primary objective of this research is to enhance the safety, efficiency, and user experience of electric vehicles through the integration of cutting-edge technologies.The AI-based pothole detection system utilizes sensors and machine learning algorithms to continuously monitor the road surface for hazards such as potholes, cracks, or debris. By analyzing real-time sensor data, the system can accurately identify potential road hazards and provide timely warnings to the driver or take proactive measures to mitigate their impact on vehicle performance and passenger comfort. The battery management system plays a critical role in optimizing the performance and longevity of the vehicle’s battery pack. Through advanced algorithms and predictive analytics, the BMS monitors various parameters such as temperature, voltage, and current to ensure safe and efficient operation of the battery. By dynamically adjusting charging rates and load distribution, the system maximizes the battery’s lifespan while ensuring sufficient energy availability for propulsion and onboard systems. Self-parking technology enables the vehicle to autonomously navigate parking spaces and execute precise maneuvers without human intervention.

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Section: Resultsmentioning

confidence: 99%

Semi-Autonomous Smart Electric Vehicle with AI based Drive Assistance

Sonar

2024

IJSREM

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“…These parameters include ambient or vehicle lights [23,24], as well as weather conditions. It needs to be pointed out that there is a feedback between vehicle lights and street or road lighting, which results in complex interactions between them [25][26][27]. The main challenge is to obtain reliable data.…”

Section: Discussionmentioning

confidence: 99%

Empirical Study of How Traffic Intensity Detector Parameters Influence Dynamic Street Lighting Energy Consumption: A Case Study in Krakow, Poland

Wojnicki

Kotulski

2018

Sustainability

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Abstract:The deployment of dynamic street lighting, which adjusts lighting levels to fulfill particular needs, leads to energy savings. These savings contribute to the overall lighting infrastructure maintenance cost. Yet another contribution is the cost of traffic intensity data. The data is read directly from sensor systems or intelligent transportation systems (ITSs). The more frequent the readings are, the more costly they become, because of hardware capabilities, data transfer and software license costs, among others. The paper investigates a relationship between the frequency of readings, in particular the averaging window size and step, and achieved energy savings. It is based on a simulation, taking into account a representative part of a city and traffic intensity data, which span over a period of one year. While the energy consumption reduction is simulated, all data, including each luminaire power setting, induction loop locations and street characteristics, come from a representative sample of the city of Krakow, Poland. Controlling the power settings complies with the lighting standard CEN/TR 13201. Analysis of the outcomes indicates that the shorter the window size or step are, the more energy saving that is available. In particular, for the previous standard CEN/TR 13201 2004, having the window size and step at 15 min results in 26.75% of energy saving, while reducing these values to 6 min provides 27%. Savings are more profound for the current standard (CEN/TR 13201 2014), assuming a 15 min size and step results in 47.43%, while having a 6 min size and step provides 47.69%. The results can serve as a guideline for identifying the economic viability of dynamic lighting control systems. Additionally, it can be observed that the current lighting standard provides far greater potential for dynamic control then the previous standard.

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“…Due to use of such sophisticated devices in these high end cars the cost of this simple module is as high as $1000. For instance following table shows cost of Adaptive headlight system in various cars [2]. From above table it is clear that cost of this module is very expensive in high-end vehicles due to use of sophisticated devices, whereas according to our proposed system it will cost much less.…”

Section: Literature Surveymentioning

confidence: 99%

“…A vehicle with normal headlights sends the light rays tangential to curves; this reduces the ability of driver to see the blind spots. These blind spots can be eliminated for safe driving using adaptive headlight system [2].…”

Section: Literature Surveymentioning

confidence: 99%

Embedded Based Smart, Secured and Safe Vehicle System

Moje¹,

Bannatwale²,

Jamdade³

et al. 2016

International Journal of Innovative Research in Electrical, Ele

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In today's fast and crowded world, road accident is a major concern. The highest fatal traffic accidents occur on the curved roads at night time. Also the glare problem due to focus of headlight is dangerous. Even the improper indications given to the nearby vehicle increases chances of fatal accidents. These facts indicate the importance of advancement in conventional vehicle systems. This paper explains the prototype model of vehicle system consisting of intelligent headlight intensity control, adaptive headlights, auto indicator-off system, anti-collision system and vehicle to vehicle communication. Proposed system is very cost efficient and reliable and can be mounted on any vehicle, it is specially focused to increase the safety and security of low-end vehicles.

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Adaptive Headlight System for accident prevention

Cited by 19 publications

References 4 publications

Semi-Autonomous Smart Electric Vehicle with AI based Drive Assistance

Semi-Autonomous Smart Electric Vehicle with AI based Drive Assistance

Empirical Study of How Traffic Intensity Detector Parameters Influence Dynamic Street Lighting Energy Consumption: A Case Study in Krakow, Poland

Embedded Based Smart, Secured and Safe Vehicle System

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