No Human Vehicle Tolling System

Kanishk Chhabra
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Abstract

The prototype aims to minimize the number of Accidents occurring on roads due to Red-light Jumping, over speeding and Drunk and Drive cases. In addition, it would address the issues such as Emergency Lanes Misuse, Deaths in Ambulance due to traffic related delays.Road accidents is the 8th leading cause of human death per annum. Day to day observations indicate, Indians in particular follow traffic rules not because of safety but out of fear of being penalized. E.g. people avoid red light jumping if they see a cop stationed right next to traffic signal.“NO HUMAN VEHICLE TOLL SYSTEM” prototype utilizes Radio Frequency Identification (RFID) Technology and camera projections. It detects the RFID tags via radio waves pre-installed in vehicles. RFID readers installed on the roads would read RFID tags using radio waves, the moment a vehicle passes through it. The signal would then be send to the microcontroller for further processing. Arduino Mega microcontroller is utilized in the prototype. The microcontroller connected to internet commands the server to search for unique RFID tag in the database and advances the process per protocol. To make the system more robust, AI cameras are being utilized to take pictures of the registration plates for reconfirmation before ticket issuance.Based on the above, the prototype would potentially address issues such – Traffic Signal Jumping, Over speeding, Intentional hindrance of Emergency Vehicles, tracking lost vehicle(s), Fake Registration Plate Detection, Driving without Seatbelt and Helmet, Drinking and Driving .In terms of numbers, it may result in 80% reduction in road accidents.
没有人车收费系统
这款原型车的目的是尽量减少因闯红灯、超速驾驶和酒后驾车而导致的道路交通事故。此外,它还将解决诸如紧急车道误用、因交通延误导致的救护车死亡等问题。道路交通事故是每年人类死亡的第八大原因。日复一日的观察表明,印度人特别遵守交通规则,不是因为安全,而是因为害怕被处罚。如果人们看到警察就在交通信号旁边,他们就会避免闯红灯。“无人车辆收费系统”原型利用无线射频识别(RFID)技术和摄像头投影。它通过预先安装在车辆上的无线电波检测RFID标签。安装在道路上的RFID读取器将在车辆通过的那一刻使用无线电波读取RFID标签。然后信号将被发送到微控制器进行进一步处理。原型采用Arduino Mega微控制器。与互联网连接的单片机命令服务器在数据库中搜索唯一的RFID标签,并按协议推进处理。为了使该系统更加健壮,正在利用人工智能相机在开票前对车牌进行拍照,以便重新确认。在此基础上,该原型车可能会解决以下问题:跳红灯、超速、故意阻碍紧急车辆、追踪丢失车辆、假车牌检测、不系安全带和头盔驾驶、酒后驾驶。从数量上看,它可能会使道路交通事故减少80%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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