Smart Vehicle Automation Using Internet of Things

2020 ◽  
Vol 17 (4) ◽  
pp. 1610-1615
Author(s):  
Visnu Dharsini ◽  
V. Gireesh ◽  
S. Vimal ◽  
Yash Nair
Keyword(s):  
Vehicle Safety ◽  
System Control ◽  
Cruise Control ◽  
Driving Experience ◽  
Smart Vehicles ◽  
Braking System ◽  
Temperature Recording ◽  
Vehicle Automation ◽  
Smart Vehicle ◽  
Vehicle Status

The field of automobile automation, though relatively new, has taken over the world by storm with the advent of driverless cars and smart vehicles. While these vehicles provide various automation features like autopilot, auto cruise control and automatic braking which enhance the driving experience and ensure safety, there are not many provisions for further safety, driver protection and problem prevention. Keeping this in mind, we have proposed a very inexpensive model to monitor the driver’s state and the in-vehicle safety, with an automatic braking system, using various sensors—gas (detecting highly poisonous toxic gases), IR (seatbelts), alcohol (if the driver is drunk), temperature/flame (for fire inside and temperature recording), humidity, LDR (automatic headlights) and ZIGBEE (automatic braking). A 12 V DC motor (wheel) controlled by L298N. The vehicle status and the motor stop reason is displayed in a basic LCD display. The data collected in all these sensors is displayed in the cloud for analyses. Arduino was used for interconnection, automation and system control. NodeMCU for cloud connection. The whole system is powered by a 5 V power source.

scholarly journals AUTONOMOUS DETECTION OF VEHICULAR WHEEL ALIGNMENT PARAMETERS

2020 ◽  
Author(s):  
Aaron Ameerali ◽  
Nadine Sangster ◽  
Gerard Ragbir
Keyword(s):  
Fuel Consumption ◽  
Cruise Control ◽  
Sensors And Actuators ◽  
Smart Vehicles ◽  
The Road ◽  
Braking System ◽  
Multiple Components ◽  
Start Up ◽  
Wheel Alignment ◽  
Autonomous Detection

Vehicular technology has improved tremendously in the last few decades. Drivers and passengers are now being made more aware of their surroundings as well as the state of their cars, ergo becoming increasingly capable of making better decisions. These 'smart-vehicles' are directed by microcontrollers and microprocessors where a network of sensors and actuators provide contextual feedback for the user. Some of these features include parking and reverse assistance, collision avoidance and cruise control. In the coming years, this trend will undergo unprecedented growth as the technologies become cheaper to manufacture and implement. In fact, more advanced systems now alert the driver to realtime critical failures and problematic conditions while the simpler ones do so upon start-up. This paper provides a tested framework for a potential sensing system to alert the driver when the vehicle alignment is off. Vehicle misalignment can become an issue quickly as the following can result: Increased tire tread wear leading to reduced traction with the road's surface and ultimately higher chances of accidents as well as more frequent replacement of the tires becoming necessary. Uneven friction at contact between the road and tire can increase the resistance resulting in higher fuel consumption by the engine. Strain on multiple components within the braking system and suspension as misalignment can cause drift while in motion and additionally uneven braking. A damaged suspension is quite expensive to repair or replace. Early detection of the extent of misalignment can lead to decreased expenditure in the areas of maintenance and fuel consumption, contributing to an increase in reliability. Since many drivers, however experienced they are, may at times be ignorant of the degree of misalignment their vehicle possesses, adding this technology can serve as a potential remedy ultimately improving the user experience and vehicle longevity.

Research on Electro-Mechanical Braking System Control of EV Based on Maximum Energy Recovery Strategy

2015 ◽  
Vol 740 ◽  
pp. 196-200
Author(s):  
Qing Nian Wang ◽  
Shi Xin Song ◽  
Shao Kun Li ◽  
Wei Chen Zhao ◽  
Feng Xiao
Keyword(s):  
Control Strategy ◽  
Influence Factors ◽  
Maximum Energy ◽  
Regenerative Braking ◽  
Force Distribution ◽  
System Control ◽  
Braking System ◽  
Power Battery ◽  
Braking Force ◽  
The Ideal

With the analysis of influence factors on regenerative braking in electro-mechanical braking system, and considering the power battery charging characteristics, a regenerative braking system control strategy for electric vehicle is researched in this paper. The models of the motor and the whole vehicle are built in AMESim. The control effects and the braking force distribution on front and rear wheels of the control strategy in an FTP-72 driving cycle are simulated and analyzed. The simulation results show that the control strategy could be utilized in the 4WD electric vehicles. The ideal braking force distribution on front and rear wheels and the high amount of recovery energy could be achieved.

An Investigation into the Traction and Anti-Lock Braking System Control Design

2020 ◽  
Author(s):  
Louis Filipozzi ◽  
Francis Assadian ◽  
Ming Kuang ◽  
Rajit Johri ◽  
Jose Velazquez Alcantar
Keyword(s):  
Control Design ◽  
System Control ◽  
Braking System

scholarly journals IoT based Smart Vehicle Monitoring System : A Systematic Literature Review

2021 ◽  
pp. 12-20
Author(s):  
Tanvir Rahman
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Navigation System ◽  
Tracking System ◽  
Health And Safety ◽  
Vehicle Tracking ◽  
Safe Driving ◽  
Driving Experience ◽  
Google Map Api ◽  
Smart Vehicle

This paper provides a complete over view of the current research state of Smart vehicle tracking System with GPS and cellular network. This paper consists of several review aiming to reveal the relevance and methodologies of this research area and create a foundation for future work. In this paper an advanced vehicle observation and IOT based tracking system and autopilot navigation system based on Machine Learning and neural Networking is proposed with all possible scientific validations of the model. The primary purpose of monitoring the vehicles which are moving from one place to the other in order to provide better A.I based autopilot navigation system, safety and security. The proposed method Combined the idea of Java programming, Neural networking concept with machine learning capability processing data with MediaTek mobile processor and its sophisticated features of storing data into several databases. Google Map Engine API v3 was used to display and sense the graphical images of the map and a Vision recognition server system is used to compare and represent the map API in a more realistic look. The proposed project includes the implementation of Global Positioning System (GPS), GPRS and GSM technology for vehicle tracking and monitoring on real time basic purpose using SIM module.[3] The GPS receiver installed o tracking device provides real-time Geolocation Co-ordinate of site of the vehicle; 3 adjacent GSM cellphone tower stations will continuously broadcast co-ordinate of locations and the GPRS technology with TCP based protocol sends the tracking information to the central Monitoring and Imaging server which consist of 3 child servers i)data processing sever, ii) Image and vision based server and iii)A.I. based machine learning server calculate data and minimize the information and maps with the help of Google map API and thus an decision message for next Move/driving path is generated and transmitted to Smart Controlling Device to execute the instructions and to display it in the Monitor of car display and Integrated logged-IN andriod based Google Map API version 3 app on real time basic. Hence, this system will monitor all the driving steps of the driver and provide the real time driving suggestions and feedback to the driver to ensure smooth and safe driving experience. The sensors like temperature sensor ,altitude sensor and smoke sensor send data to the neural processing Server which diagnoses the health and safety measures of the vehicles and generates a report on Car display and andriod App interface if any risk issue is found by sensors.

scholarly journals The Effects of Vehicle Automation on Driver Engagement: The Case of Adaptive Cruise Control and Mind Wandering

2020 ◽  
pp. 001872082097485
Author(s):  
Starla M. Weaver ◽  
Stephanie M. Roldan ◽  
Tracy B. Gonzalez ◽  
Stacy A. Balk ◽  
Brian H. Philips
Keyword(s):  
Adaptive Cruise Control ◽  
Field Research ◽  
Physiological Arousal ◽  
Mind Wandering ◽  
Driving Performance ◽  
Vehicle Speed ◽  
Cruise Control ◽  
Positive Effects ◽  
And Gender ◽  
Vehicle Automation

Objective This field study examined the effects of adaptive cruise control (ACC) on mind wandering prevalence. Background ACC relieves the driver of the need to regulate vehicle speed and following distance, which may result in safety benefits. However, if ACC reduces the amount of attentional resources drivers must devote to driving, then drivers who use ACC may experience increased periods of mind wandering, which could reduce safety. Methods Participants drove a prescribed route on a public road twice, once using ACC and once driving manually. Mind wandering rates were assessed throughout the drive using auditory probes, which occurred at random intervals and required the participant to indicate whether or not they were mind wandering. Measures of physiological arousal and driving performance were also recorded. Results No evidence of increased mind wandering was found when drivers used ACC. In fact, female drivers reported reduced rates of mind wandering when driving with ACC relative to manual driving. Driving with ACC also tended to be associated with increased physiological arousal and improved driving behavior. Conclusion Use of ACC did not encourage increased mind wandering or negatively affect driving performance. In fact, the results indicate that ACC may have positive effects on driver safety among drivers who have limited experience with the technology. Application Driver characteristics, such as level of experience with in-vehicle technology and gender, should be considered when investigating driver engagement during ACC use. Field research on vehicle automation may provide valuable insights over and above studies conducted in driving simulators.

Improved Anti-Lock Braking System With Real-Time Friction Detection to Maximize Vehicle Performance

2021 ◽  
Author(s):  
Vincenzo Maria Arricale ◽  
Antonio Maiorano ◽  
Lorenzo Mosconi ◽  
Guido Napolitano Dell’Annunziata ◽  
Ernesto Rocca ◽  
...  
Keyword(s):  
Vehicle Safety ◽  
Tire Model ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Vehicle Performance ◽  
Braking System ◽  
Bicycle Model ◽  
Combined Use ◽  
Braking Distance ◽  
Assistance Systems

Abstract Nowadays, advanced driver assistance systems play a fundamental role to improve vehicle safety and drivability; their capability to reduce the accidents rate was widely demonstrated, but these systems could also be employed to improve vehicle performance if incorporated with other control logics. This work presents an evolved version of the anti-lock braking system, obtained thanks to the combined use of a bicycle model, capable to estimate the actual friction coefficient in different environmental conditions, and a potential friction estimator based on a Magic Formula tire model with a slip-slope approach. With the presented ABS, virtually tested in several conditions, it is possible to reduce the braking distance with the final aim of reducing the braking time and, in this way, improving the vehicle performance.

Hardware Design of Electronic Parking Brake System

2015 ◽  
Vol 733 ◽  
pp. 670-673
Author(s):  
Jun Jie Wu ◽  
Qian Fu Gui ◽  
Shao Hua Zhong
Keyword(s):  
Hardware Design ◽  
Control Unit ◽  
Working Life ◽  
Basic Function ◽  
Brake System ◽  
System Control ◽  
Rational Analysis ◽  
Braking System ◽  
Parking Brake ◽  
Hardware Circuit

Based on the Free scale S12 processor as the main MCU, the article have designed the hardware circuit of the electronic parking brake system control unit, and on the basis I have made the rational analysis of the control of the total the electronic parking brake system. The analysis and experiment results show that the design can realize the basic function of EPB, to a great extent, it also improve the reliability of the system, fault self-checking ability and delayed its working life and just right to satisfy the most basic and most critical requirements of the system: As part of the braking system, it should have the reliability and security.

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