scholarly journals Real-Time Driver Alert System Using Raspberry Pi

2019 ◽  
Vol 17 (2) ◽  
pp. 193-203 ◽  
Author(s):  
Jie Yi Wong ◽  
Phooi Yee Lau
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Economic Losses ◽  
Raspberry Pi ◽  
Alert System ◽  
Driving Experience ◽  
The Road ◽  
Car Accidents ◽  
Passenger Safety ◽  
On The Road

Malaysia has been ranked as one of the country in the world with deadliest road. Based on the statistic, there are around 7000 to 8000 people in the country died on the road among the population of 31 million Malaysians every year. In general, Advances Driver Assistance System (ADAS) aims to improve not only the driving experience but also consider the overall passenger safety. In recent years, driver drowsiness has been one of the major causes of road accidents, which can lead to severe physical injuries, deaths and significant economic losses. In this paper, a vison-based real-time driver alert system aimed mainly to monitor the driver’s drowsiness level and distraction level is proposed. This alert system could reduce the fatalities of car accidents by detecting driver’s face, detecting eyes region using facial landmark and calculating the rate of eyes closure in order to monitor the drowsiness level of the driver. Later, the system is embedded into the Raspberry Pi, with a Raspberry Pi camera and a speaker buzzer, and is used to alert the driver in real-time, by providing a beeping sound. Experimental results show that proposed system is practical and low-cost which could (1) embed the drowsiness detection module, and (2) provide alert notification to the driver when the driver is inattentive, using a medium loud beeping sound, in real-time.

scholarly journals Raspberry Pi-Based Low-Cost Connected Device for Assessing Road Surface Friction

Electronics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 341 ◽  
Author(s):  
Miha Ambrož ◽  
Uroš Hudomalj ◽  
Alexander Marinšek ◽  
Roman Kamnik
Keyword(s):  
Traffic Safety ◽  
Road Network ◽  
Low Cost ◽  
Measurement Data ◽  
Automatic Measurement ◽  
Raspberry Pi ◽  
Measuring Device ◽  
The Road ◽  
Measuring Devices ◽  
On The Road

Measuring friction between the tyres of a vehicle and the road, often and on as many locations on the road network as possible, can be a valuable tool for ensuring traffic safety. Rather than by using specialised equipment for sequential measurements, this can be achieved by using several low-cost measuring devices on vehicles that travel on the road network as part of their daily assignments. The presented work proves the hypothesis that a low cost measuring device can be built and can provide measurement results comparable to those obtained from expensive specialised measuring devices. As a proof of concept, two copies of a prototype device, based on the Raspberry Pi single-board computer, have been developed, built and tested. They use accelerometers to measure vehicle braking deceleration and include a global positioning receiver for obtaining the geolocation of each test. They run custom-developed data acquisition software on the Linux operating system and provide automatic measurement data transfer to a server. The operation is controlled by an intuitive user interface consisting of two illuminated physical pushbuttons. The results show that for braking tests and friction coefficient measurements the developed prototypes compare favourably to a widely used professional vehicle performance computer.

scholarly journals Low-Cost Real-Time PPP/INS Integration for Automated Land Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4896 ◽  
Author(s):  
Mohamed Elsheikh ◽  
Walid Abdelfatah ◽  
Aboelmagd Nourledin ◽  
Umar Iqbal ◽  
Michael Korenberg
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Estimation Algorithm ◽  
Satellite System ◽  
Single Frequency ◽  
The Road ◽  
Land Vehicles ◽  
On The Road ◽  
Vehicle Automation ◽  
Global Navigation Satellite

The last decade has witnessed a growing demand for precise positioning in many applications including car navigation. Navigating automated land vehicles requires at least sub-meter level positioning accuracy with the lowest possible cost. The Global Navigation Satellite System (GNSS) Single-Frequency Precise Point Positioning (SF-PPP) is capable of achieving sub-meter level accuracy in benign GNSS conditions using low-cost GNSS receivers. However, SF-PPP alone cannot be employed for land vehicles due to frequent signal degradation and blockage. In this paper, real-time SF-PPP is integrated with a low-cost consumer-grade Inertial Navigation System (INS) to provide a continuous and precise navigation solution. The PPP accuracy and the applied estimation algorithm contributed to reducing the effects of INS errors. The system was evaluated through two road tests which included open-sky, suburban, momentary outages, and complete GNSS outage conditions. The results showed that the developed PPP/INS system maintained horizontal sub-meter Root Mean Square (RMS) accuracy in open-sky and suburban environments. Moreover, the PPP/INS system could provide a continuous real-time positioning solution within the lane the vehicle is moving in. This lane-level accuracy was preserved even when passing under bridges and overpasses on the road. The developed PPP/INS system is expected to benefit low-cost precise land vehicle navigation applications including level 2 of vehicle automation which comprises services such as lane departure warning and lane-keeping assistance.

scholarly journals An UAV scheduling and planning method for post-disaster survey

2014 ◽  
Vol XL-2 ◽  
pp. 169-172 ◽  
Author(s):  
G. Q. Li ◽  
X. G. Zhou ◽  
J. Yin ◽  
Q. Y. Xiao
Keyword(s):  
Real Time ◽  
High Efficiency ◽  
Population Distribution ◽  
Low Cost ◽  
Economic Losses ◽  
The Real ◽  
The Road ◽  
Scheduling Method ◽  
High Flexibility ◽  
Post Disaster

Annually, the extreme climate and special geological environments lead to frequent natural disasters, e.g., earthquakes, floods, etc. The disasters often bring serious casualties and enormous economic losses. Post-disaster surveying is very important for disaster relief and assessment. As the Unmanned Aerial Vehicle (UAV) remote sensing with the advantage of high efficiency, high precision, high flexibility, and low cost, it is widely used in emergency surveying in recent years. As the UAVs used in emergency surveying cannot stop and wait for the happening of the disaster, when the disaster happens the UAVs usually are working at everywhere. In order to improve the emergency surveying efficiency, it is needed to track the UAVs and assign the emergency surveying task for each selected UAV. Therefore, a UAV tracking and scheduling method for post-disaster survey is presented in this paper. In this method, Global Positioning System (GPS), and GSM network are used to track the UAVs; an emergency tracking UAV information database is built in advance by registration, the database at least includes the following information, e.g., the ID of the UAVs, the communication number of the UAVs; when catastrophe happens, the real time location of all UAVs in the database will be gotten using emergency tracking method at first, then the traffic cost time for all UAVs to the disaster region will be calculated based on the UAVs’ the real time location and the road network using the nearest services analysis algorithm; the disaster region is subdivided to several emergency surveying regions based on DEM, area, and the population distribution map; the emergency surveying regions are assigned to the appropriated UAV according to shortest cost time rule. The UAVs tracking and scheduling prototype is implemented using SQLServer2008, ArcEnginge 10.1 SDK, Visual Studio 2010 C#, Android, SMS Modem, and Google Maps API.

CASA: An Alternative Smartphone-Based ADAS

2021 ◽  
pp. 1-41
Author(s):  
Manolo Dulva Hina ◽  
Hongyu Guan ◽  
Assia Soukane ◽  
Amar Ramdane-Cherif
Keyword(s):  
Low Cost ◽  
Electronic System ◽  
Time Data ◽  
Case Scenario ◽  
Safe Driving ◽  
The Road ◽  
Driving Assistance ◽  
Alternative Means ◽  
On The Road ◽  
Driving Assistance System

Advanced driving assistance system (ADAS) is an electronic system that helps the driver navigate roads safely. A typical ADAS, however, is suited to specific brands of vehicle and, due to proprietary restrictions, has non-extendable features. Project CASA is an alternative, low-cost generic ADAS. It is an app deployable on smartphone or tablet. The real-time data needed by the app to make sense of its environment are stored in the vehicle or on the cloud, and are accessible as web services. They are used to determine the current driving context, and, if needed, decide actions to prevent an accident or keep road navigation safe. Project CASA is an undertaking of a consortium of industrial and academic partners. A use case scenario is tested in the laboratory (virtual) and on the road (actual) to validate the appropriateness of CASA. It is a contribution to safe driving. CASA’s contribution also lies in its approach in the semantic modeling of the context of the environment, the vehicle and the driver, and on the modeling of rules for fusion of data and fission process yielding an action to be implemented. In addition, CASA proposes a secured means of transmitting data using light, via light fidelity (LiFi), itself an alternative means of wireless vehicle–smartphone communication.

Real-Time V2V Communication With a Machine Learning-Based System for Detecting Drowsiness of Drivers

2021 ◽  
Vol 13 (4) ◽  
pp. 35-50
Author(s):  
Ahmed Y. Awad ◽  
Seshadri Mohan
Keyword(s):  
Machine Learning ◽  
Traffic Accidents ◽  
Ad Hoc ◽  
Economic Losses ◽  
Drowsy Driving ◽  
The Road ◽  
V2v Communication ◽  
Physical Injuries ◽  
On The Road ◽  
The U.S

This article applies machine learning to detect whether a driver is drowsy and alert the driver. The drowsiness of a driver can lead to accidents resulting in severe physical injuries, including deaths, and significant economic losses. Driver fatigue resulting from sleep deprivation causes major accidents on today's roads. In 2010, nearly 24 million vehicles were involved in traffic accidents in the U.S., which resulted in more than 33,000 deaths and over 3.9 million injuries, according to the U.S. NHTSA. A significant percentage of traffic accidents can be attributed to drowsy driving. It is therefore imperative that an efficient technique is designed and implemented to detect drowsiness as soon as the driver feels drowsy and to alert and wake up the driver and thereby preventing accidents. The authors apply machine learning to detect eye closures along with yawning of a driver to optimize the system. This paper also implements DSRC to connect vehicles and create an ad hoc vehicular network on the road. When the system detects that a driver is drowsy, drivers of other nearby vehicles are alerted.

Low-Cost Smart Heads-Up Display Assist System for Automobiles

2021 ◽  
Vol 7 (2) ◽  
Author(s):  
Gautham G ◽  
Deepika Venkatesh ◽  
A. Kalaiselvi
Keyword(s):  
Fuel Economy ◽  
Low Cost ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Raspberry Pi ◽  
Worst Case ◽  
The Road ◽  
Traffic Conditions ◽  
Metropolitan Cities ◽  
Ingenious Method

In recent years, due to the increasing density of traffic every year, it is been a hassle for drivers in metropolitan cities to maintain lane and speeds on road. The drivers usually waste time and effort in idling their cars to maintain in traffic conditions. The drivers get easily frustrated when they tried to maintain the path because of the havoc created. Transportation Institute found that the odds of a crash(or near crash) more than doubled when the driver took his or her eyes off the road formore than two seconds. This tends to cause about 23% of accidents when not following their lane paths. In worst case the fuel economy often drops and tends to cause increase in pollution about 28% to 36% per vehicle annually. This corresponds to the wastage of fuel. Owing to this problem, we proposed an ingenious method by which the lane detection can be made affordable and applicable to existing automobiles. The proposed prototype of lane detection is carried over with a temporary autonomous bot which is interfaced with Raspberry pi processor, loaded with the lane detection algorithm. This prototype bot is made to get live video which is then processed by the algorithm. Also, the preliminary setups are carried over in such a way that it is easily implemented and accessible at low cost with better efficiency, providing a better impact on future automobiles.

A study on Private Car Accidents

2021 ◽  
Vol 11 (1) ◽  
pp. 10-24
Author(s):  
Abdulmajeed Alamri ◽  
Tarek M. Esmael ◽  
Sami Fawzy ◽  
Hany Hosny ◽  
Saleh Attawi ◽  
...  
Keyword(s):  
Road Traffic Accident ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Road Traffic Injury ◽  
Economic Losses ◽  
Moving Vehicle ◽  
The Road ◽  
Lost Productivity ◽  
On The Road

In this study, road traffic injury (RTI) was defined as any injury resulting from a road traffic accident irrespective of severity and outcome. Road traffic accident (RTA) was defined as any crash on the road involving at least one moving vehicle, irrespective of it resulting in an injury. This could include collision with a vehicle or any non`moving object while driving/riding a vehicle, collision with a moving vehicle while walking/running/standing/ sitting on the road, or fall from a moving vehicle. The burden of road traffic accidents (RTA) is a leading cause of all trauma admissions in hospitals worldwide. Road traffic injuries cause considerable economic losses to victims, their families, and to nations as a whole. These losses arise from the cost of treatment (including rehabilitation and incident investigation) as well as reduced/lost productivity (e.g. in wages) for those killed or disabled by their injuries and for family members who need to take time off work (or school) to care for the injured. Road traffic fatality in the Kingdom of Saudi Arabia (KSA) is the highest, accounts for 4.7% of all mortalities. Road injuries also are reported to be the most serious in this country, with an accident to injury ratio of 8:6. In this study, we try to focus on some causes of the accidents in KSA, so we can implement the prevention plan.

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