Autonomous collision avoidance system based on accurate knowledge of the vehicle surroundings

Jiménez, Felipe; Naranjo, José Eugenio; Gómez, Óscar

doi:10.1049/iet-its.2013.0118

Cited by 38 publications

(20 citation statements)

References 29 publications

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“…Sensor assembly co mprises of infrared sensors for path finding and an ultrasonic sensor for avoiding collision. [9] The sensors obtain necessary data concerning the working conditions, position, and posture. They give certain data for the direction, positioning, and obstacle avoidance of the vehicle to achieve the purpos e of regulating its movements.…”

Section: Sensor Assemblymentioning

confidence: 99%

Design and Implementation of Automatic Guided Vehicle for Hospital Application

Antony¹,

Parameswaran²,

Mathew³

et al. 2020

2020 5th International Conference on Communication and Electronics Systems (ICCES)

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With the advancements of robotic technologies, the medical environments are adopting more and more as pects of automation to enhance the services in hos pitals. In pandemic conditions such as COVID 19, direct contact with patients may result in the s preadi ng of disease. Hence the health community finds difficulty in distri buting medicines and disposal of waste. The design and development of an automatic gui ded vehicle for hos pital applicati ons, which can be controlled remotely is specified here. AGV is a line follower robot, powered by a battery that can be charged from solar energy. It has infrared sensors at the bottom for path i dentification and an ultrasonic sensor hel d i n front of the vehicle for obstacle detection. It collects medicines from the nurse's station and follows the path provi ded to reach the suppl y point, which is the patient's bed. The sensors provi ded will detect the bed and opens the correspondi ng box of medicine. In addi tion to this, it hel ps i n real-time monitoring of patient's parameters such as temperature, pulse rate, etc. and sends informati on to the doctor through the internet. AGV also collects waste from the bi n and dump it to a proper place.

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Section: Sensor Assemblymentioning

confidence: 99%

Design and Implementation of Automatic Guided Vehicle for Hospital Application

Antony¹,

Parameswaran²,

Mathew³

et al. 2020

2020 5th International Conference on Communication and Electronics Systems (ICCES)

View full text Add to dashboard Cite

show abstract

“…Numerous studies indicate that if a complete representation of the environment or an increase in the confidence level in detection is required, it is essential to use sensor fusion from multiple information sources [ 18 – 21 ]. This sensor fusion supports safety applications such as Adaptive Cruise Control based on any of the three technologies mentioned [ 22 , 23 ], pre-crash collision avoidance systems integrating computer vision and laser [ 24 ] and autonomous driving systems merging several technologies [ 22 , 25 , 26 ], etc.…”

Section: Related Workmentioning

confidence: 99%

“…Thus, the primary environment detection sensor consists of the laser scanner on the front. Specifically, the Sick LRS 1000 sensor is used, whose performance with revised obstacle identification algorithms has been satisfactory proven in [ 24 , 42 ].…”

Section: System Layoutmentioning

confidence: 99%

Vehicle Tracking for an Evasive Manoeuvres Assistant Using Low-Cost Ultrasonic Sensors

Jiménez¹,

Naranjo²,

Gómez³

et al. 2014

Sensors

Self Cite

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Many driver assistance systems require knowledge of the vehicle environment. As these systems are increasing in complexity and performance, this knowledge of the environment needs to be more complete and reliable, so sensor fusion combining long, medium and short range sensors is now being used. This paper analyzes the feasibility of using ultrasonic sensors for low cost vehicle-positioning and tracking in the lane adjacent to the host vehicle in order to identify free areas around the vehicle and provide information to an automatic avoidance collision system that can perform autonomous braking and lane change manoeuvres. A laser scanner is used for the early detection of obstacles in the direction of travel while two ultrasonic sensors monitor the blind spot of the host vehicle. The results of tests on a test track demonstrate the ability of these sensors to accurately determine the kinematic variables of the obstacles encountered, despite a clear limitation in range.

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“…With respect to road safety, the mutual cooperation helps to solve the traffic problems caused by the driving errors, insufficient visibility distance [15][16][17]. In terms of traffic efficiency, vehicles could form platoon through cooperation to reduce headways and increase road capacity [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Traffic Control Models Based on Cellular Automata for At-Grade Intersections in Autonomous Vehicle Environment

Liu

et al. 2017

Journal of Sensors

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Autonomous vehicle is able to facilitate road safety and traffic efficiency and has become a promising trend of future development. With a focus on highways, existing literatures studied the feasibility of autonomous vehicle in continuous traffic flows and the controllability of cooperative driving. However, rare efforts have been made to investigate the traffic control strategies in autonomous vehicle environment on urban roads, especially in urban intersections. In autonomous vehicle environment, it is possible to achieve cooperative driving with V2V and V2I wireless communication. Without signal control, conflicted traffic flows could pass intersections through mutual cooperative, which is a remarkable improvement to existing traffic control methods. This paper established a cellular automata model with greedy algorithm for the traffic control of intersections in autonomous vehicle environment, with autonomous vehicle platoon as the optimization object. NetLogo multiagent simulation platform model was employed to simulate the proposed model. The simulation results are compared with the traffic control programs in conventional Synchro optimization. The findings suggest that, on the premises of ensuring traffic safety, the control strategy of the proposed model significantly reduces average delays and number of stops as well as increasing traffic capacity.

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Autonomous collision avoidance system based on accurate knowledge of the vehicle surroundings

Cited by 38 publications

References 29 publications

Design and Implementation of Automatic Guided Vehicle for Hospital Application

Design and Implementation of Automatic Guided Vehicle for Hospital Application

Vehicle Tracking for an Evasive Manoeuvres Assistant Using Low-Cost Ultrasonic Sensors

Traffic Control Models Based on Cellular Automata for At-Grade Intersections in Autonomous Vehicle Environment

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