Multi-Agent Safety Book 2 - Automated Vehicle Safety

2019 ◽  

A smart helmet is a kind of defensive headgear utilized by the rider which makes bike driving more secure than previously. The principle reason for this keen protective cap to give well being to rider.Here I proposed a work which is endeavor to plan a propelled vehicle’s security framework which utilizes GSM to avert burglary and to decide the area of vehicles. Now a daysburglary is going on the stopping or in some shaky spots. The wellbeing of the vehicles is incredibly fundamental. The point of the vehicles security framework is used to utilizes the remote communication innovatively for the car situations. The principle focal point of this undertaking is to ensure the stealing of vehicle. This is finished with the assistance of GSM modem and circuit which comprises of ARM 7 TDMI microcontroller, transfer and venture down transformer. The framework will be enacted simply in the wake of wearing the head protector or else the client can't ready to get to the vehicle. To achieve Automated Vehicle Location our system uses to transmit the area data continuously, Active systems are produced. Progressing vehicular after system joins a gear device introduced in the vehicle and a remote Tracking servers. The infowas conveyed to Tracking server utilizing GSM/GPRS modem on GSM mastermind by using SMS or utilized direct TCP/IP association with Tracking servers thruGPRS. Following servers in like way has GSM/GPRS modem that gets vehicle region data by techniques for GSM system and stores info into databases. This info is available to embraced clients of the systems by techniques for sites over the web.


Author(s):  
Fengchen Wang ◽  
Yan Chen

Abstract Considering the application of flocking control on connected and automated vehicle (CAV) systems, the persistent interactions between CAVs (flocking agents) and road boundaries (permanent obstacles) are critical, due to flocking behaviors in a strictly confined environment. However, the existing flocking theories attempt to model and animate natural flocks by only considering temporary obstacles, which only describe interactions between agents and obstacles that will eventually disappear during flocking. This paper proposes a novel flocking control algorithm to extend existing flocking theories and guarantee the desired flocking coordination of multi-agent systems (e.g., CAV systems) with permanent obstacles (constraints). By analyzing comprehensive behaviors of flocks via Hamiltonian functions, a zero-sum obstacle condition is developed to ensure the satisfaction of permanent obstacle avoidance. Then, an additional control term representing the resultant forces of permanent obstacles is introduced to tackle interactions between agents and permanent obstacles. Demonstrated and compared through simulation results, a CAV system steered by the proposed flocking control protocol can successfully achieve the desired flocking behaviors with permanent obstacles avoidance in a three-lane traffic environment, which is failed by existing flocking control theories solely considering temporary obstacles.


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