17-09-2014, 03:36 PM
Mobile phone based drunk driving detection
[attachment=68068]
ABSTRACT
Drunk driving, or officially Driving Under the Influence (DUI) of alcohol, is a major cause of traffic accidents throughout the world.
In this paper , we propose a highly efficient system aimed at early detection and alert of dangerous vehicle maneuvers typically related to drunk driving. The entire solution requires only a mobile phone placed in vehicle and with accelerometer and orientation sensor.
A program installed on the mobile phone computes accelerations based on sensor readings, and compares them with typical drunk driving patterns extracted from real driving tests.
Once any evidence of drunk driving is present, the mobile phone will automatically alert the driver or call the police for help well before accident actually happens. We implement the detection system on Android G 1 phone and have it tested with different kinds of driving behaviours. The results show that the system achieves high accuracy and energy efficiency.
INTRODUCTION
Drunk drivers continue to plague in American highways. They crash, they injure, and they kill. In 2000, 16,653 traffic fatalities — 40 percent of all highway deaths —involved at least one drinking driver, pedestrian, or bicyclist. Of all drivers involved infatal crashes, 10,408 had a blood alcohol level of 0.10 or above – a level that is illegal without any further evidence in every state except Massachusetts.
Drunk driving has dropped substantially over the past two decades. Traffic fatalities involving alcohol decreased by 37 percent between 1982 and 1999, and the number of drunk drivers in these crashes who had a blood alcohol level of 0.10 or higher decreased by 42 percent.
World Health Organization’s , first ever Global Status Report on Road Safety reveals that 90% of deaths on the world's roads occur in low and middle income countries (21.5 and 19.5 per lakh of population, respectively) though they have just 48% of all registered vehicles. India has the second largest road network in the world with over 3 million km of roads of which 60% are paved. These roads make a vital contribution to the India's economy.
According to a government report, road accidents in India killed 1,34,000 people in 2010 (an average of 336 a day).
Accidents due to drunken driving are a major problem in India. The problem is unrecognized and hidden due to lack of good quality research data. A study conducted by Alcohol & drug Information Centre (AIDC), India revealed that around 40% of the road accidents have occurred under the influence of alcohol.
MOBILE PHONE TO PREVENT DRUNK DRIVING
In this paper, we propose utilizing mobile phones as the platform for drunk driving detection system development, as they naturally combine the detection and communication functions.
To the best of our knowledge, we are the first to do so. As a self-contained device, mobile phone presents a mature hardware and software environment for the development of active drunk driving monitoring system. The system based on mobile phone can function effectively on its own because mobile phones are highly portable, all necessary components are already integrated there in, and their communication service shave vast coverage. The minimum requirement for such a mobile phone platform is the presence of simple sensors, e.g., accelerometer and orientation sensor. Currently, many phones, especially smartphones, meet this requirement. They contain multiple types of sensors, including accelerometers and orientation sensors. And their communication module and speakers are naturally good enough for alerting. Such phones are very popular and widely accepted in our society. Over 120 million smartphones were sold in 2008, and their popularity is projected to continuously increase in the near future due to decreasing price. Recently, several leading telecommunication companies such as AT&T have made available affordable smartphones, whose features are similar to those of highend models, in addition to cheaper service plans.
We summarize the contributions of this paper as follows.We propose utilizing mobile phones as the platform for drunk driving detection.To the best of our knowledge, we are the first to introduce mobile phones in the area of drunk driving detection. We design the algorithm for detecting drunk driving in real time using mobile phones. We analyze the drunk driving related behaviours and extract its fundamental cues based on lateral and longitudinal accelerations of vehicle, which are determined by accelerometer and orientation sensor readings in mobile phones. We design and implement the drunk driving detection system on mobile phones. The system is reliable, non-intrusive, lightweight and power-efficient. And it requires no extra hardware and service cost.
We conduct real driving tests to evaluate the performance of our system. During these tests, we drive regularly or simulate the drunk driving related behaviours. We also vary the position and orientation of mobile phones in the vehicle for the purpose of validation. The results show that our detection system achieves good performance in terms of false negative and false positive.
There are some existing research on the development and validation of technological tools for driving monitoring. Some of them are known under the name of driver vigilance monitoring, and they focus on monitoring and preventing driver fatigue.
Other work focus on real-time driving pattern recognition. In detail, they use various methodologies and techniques described as follows.
CONCLUSION
In this paper, we present a highly efficient mobile phone based drunk driving detection system. The mobile phone, which is placed in the vehicle, collects and analyzes the data from its accelerometer and orientation sensor to detect any abnormal or dangerous driving maneuvers typically related to driving under alcohol influence.
Experiments show that our solution sees very low false negative and false positive rates, as well as tolerable energy consumption. In our future work, we plan to improve our detection system by integrating all available sensing data on a mobile phone, e.g. , GPS data and camera image
[attachment=68068]
ABSTRACT
Drunk driving, or officially Driving Under the Influence (DUI) of alcohol, is a major cause of traffic accidents throughout the world.
In this paper , we propose a highly efficient system aimed at early detection and alert of dangerous vehicle maneuvers typically related to drunk driving. The entire solution requires only a mobile phone placed in vehicle and with accelerometer and orientation sensor.
A program installed on the mobile phone computes accelerations based on sensor readings, and compares them with typical drunk driving patterns extracted from real driving tests.
Once any evidence of drunk driving is present, the mobile phone will automatically alert the driver or call the police for help well before accident actually happens. We implement the detection system on Android G 1 phone and have it tested with different kinds of driving behaviours. The results show that the system achieves high accuracy and energy efficiency.
INTRODUCTION
Drunk drivers continue to plague in American highways. They crash, they injure, and they kill. In 2000, 16,653 traffic fatalities — 40 percent of all highway deaths —involved at least one drinking driver, pedestrian, or bicyclist. Of all drivers involved infatal crashes, 10,408 had a blood alcohol level of 0.10 or above – a level that is illegal without any further evidence in every state except Massachusetts.
Drunk driving has dropped substantially over the past two decades. Traffic fatalities involving alcohol decreased by 37 percent between 1982 and 1999, and the number of drunk drivers in these crashes who had a blood alcohol level of 0.10 or higher decreased by 42 percent.
World Health Organization’s , first ever Global Status Report on Road Safety reveals that 90% of deaths on the world's roads occur in low and middle income countries (21.5 and 19.5 per lakh of population, respectively) though they have just 48% of all registered vehicles. India has the second largest road network in the world with over 3 million km of roads of which 60% are paved. These roads make a vital contribution to the India's economy.
According to a government report, road accidents in India killed 1,34,000 people in 2010 (an average of 336 a day).
Accidents due to drunken driving are a major problem in India. The problem is unrecognized and hidden due to lack of good quality research data. A study conducted by Alcohol & drug Information Centre (AIDC), India revealed that around 40% of the road accidents have occurred under the influence of alcohol.
MOBILE PHONE TO PREVENT DRUNK DRIVING
In this paper, we propose utilizing mobile phones as the platform for drunk driving detection system development, as they naturally combine the detection and communication functions.
To the best of our knowledge, we are the first to do so. As a self-contained device, mobile phone presents a mature hardware and software environment for the development of active drunk driving monitoring system. The system based on mobile phone can function effectively on its own because mobile phones are highly portable, all necessary components are already integrated there in, and their communication service shave vast coverage. The minimum requirement for such a mobile phone platform is the presence of simple sensors, e.g., accelerometer and orientation sensor. Currently, many phones, especially smartphones, meet this requirement. They contain multiple types of sensors, including accelerometers and orientation sensors. And their communication module and speakers are naturally good enough for alerting. Such phones are very popular and widely accepted in our society. Over 120 million smartphones were sold in 2008, and their popularity is projected to continuously increase in the near future due to decreasing price. Recently, several leading telecommunication companies such as AT&T have made available affordable smartphones, whose features are similar to those of highend models, in addition to cheaper service plans.
We summarize the contributions of this paper as follows.We propose utilizing mobile phones as the platform for drunk driving detection.To the best of our knowledge, we are the first to introduce mobile phones in the area of drunk driving detection. We design the algorithm for detecting drunk driving in real time using mobile phones. We analyze the drunk driving related behaviours and extract its fundamental cues based on lateral and longitudinal accelerations of vehicle, which are determined by accelerometer and orientation sensor readings in mobile phones. We design and implement the drunk driving detection system on mobile phones. The system is reliable, non-intrusive, lightweight and power-efficient. And it requires no extra hardware and service cost.
We conduct real driving tests to evaluate the performance of our system. During these tests, we drive regularly or simulate the drunk driving related behaviours. We also vary the position and orientation of mobile phones in the vehicle for the purpose of validation. The results show that our detection system achieves good performance in terms of false negative and false positive.
There are some existing research on the development and validation of technological tools for driving monitoring. Some of them are known under the name of driver vigilance monitoring, and they focus on monitoring and preventing driver fatigue.
Other work focus on real-time driving pattern recognition. In detail, they use various methodologies and techniques described as follows.
CONCLUSION
In this paper, we present a highly efficient mobile phone based drunk driving detection system. The mobile phone, which is placed in the vehicle, collects and analyzes the data from its accelerometer and orientation sensor to detect any abnormal or dangerous driving maneuvers typically related to driving under alcohol influence.
Experiments show that our solution sees very low false negative and false positive rates, as well as tolerable energy consumption. In our future work, we plan to improve our detection system by integrating all available sensing data on a mobile phone, e.g. , GPS data and camera image