![5
6.FUTURE IMPLEMENTATION
Will provide us with shortest time routing based on road
conditions changing because of weather and traffic,
information about the cars on the route, destination
requirement.
7.CONCLUSION
Method for monitoring driver alertness sufficient time to avert
an accident. Successful implementation of Artificial
Passenger would allow use of various services in car like
reading emails, navigation, downloading music files, voice
games etc. compromising on driver safety. We suggested that
such important issues related to a driver safety, such as
controlling telematics devices and drowsiness can be
addressed by a special speech interface. This interface
requires interactions with workload, dialog, event, privacy,
situation and other modules. We showed that basic speech
interactions can be done in a low-resource embedded
processor and this allows a development of a useful local
component of Safety Driver Manager. The reduction of
conventional speech processes to low – resources processing
was done by reducing a signal processing and decoding load
in such a way that it did not significantly affect decoding
accuracy and by the development of quasi-NLU principles.
8.ACKNOWLEDGMENTS
I would like to Thank my guide respected B.Satish sir Assoc.
Professor, Dept. of CSE who had supported meand guided
me for doing this paper.
9.REFERENCES
[1].http://www.Google.com
[2].http://www.Wikipedia.org/wiki/Artificial_Passenger
[3].https://www.scribd.com/document/Artificial-Passenger
[4].http://www.springerlink.com/content/passenger](https://image.slidesharecdn.com/technicalseminarartificialpassengernew-180130191119/85/Technical-seminar-artificial-passenger-in-ieee-format-5-320.jpg)
Technical seminar artificial passenger in ieee format
- 1. 1 Artificial Passenger P.Manideep B.tech 4th year Cse. Kamala Institute of Technology &Science Singapuram,Huzurabad manideep.padakanti@gmail.com B.Satish Assoc.Professor, Dept. of CSE Kamala Institute of Technology & Science Singapuram,Huzurabad saisujith2003@gmail.com ABSTRACT IBM (International Business Machines Corporation, NY) has developed software that holds a conversation with the driver to determine whether the driver can respond alertly enough, called “Artificial Passenger”.This was designed to make long solo journeys safer and more bearable. The Artificial Passenger is an Artificial Intelligence based companion that will be resident in software and chips embedded in the automobile dashboard. The system has a conversation planner that holds a profile of you, including details of your interests and profession. A microphone picks up your answer and breaks it down into separate words with speech-recognition software. A camera built into the dashboard also tracks your lip movements to improve the accuracy of speech recognition. A voice analyzer then looks for signs of tiredness by checking to see if the answer matches your profile. Slow responses and lack of attention are signs of fatigue. General Terms Natural language e-companion.Sleep preventive device in cars to overcomedrowsiness. Life safety system Keywords Condition Sensor, Mobile Indicator Device. 1.INTRODUCTION The international business machines has developed a software that holds a conversation with the driver to determine whether the driver can respond alertly enough, called “Artificial Passenger”This was designed in such a way that make long solo journeys safer and more bearable. 2.BACKGROUND OF THE INVENTION 2.1Why Such System According to a national survey in UK and USA, it is observed that the driver fatigue annually is observed that the driver fatigue annually cause: • 10000 crashes • 1500 deaths • 7100 injuries Majority of off-road accidents observed, were caused by eye closure of half and even 2-3 caused by eye closure of half and even 2-3 seconds, where the normal human eye blinks at seconds, where the normal human eyeblinks at 0.2-0.3 seconds. 2.2 What is an Artificial Passenger? Natural language e-companion. Sleep preventive device in cars to overcome drowsiness. Life safety system. 2.3 What Does It Do Detects alarm conditions through sensors. Broadcasts pre- stored voice messages over the speakers. Captures images of the driver. 2.4 About Artificial Passenger The AP is an Artificial Intelligence based companion that will be resident in software and chips embedded in the automobile dashboard. The system has a conversation planner that holds a profile of you, including details of your interests and profession. A microphone picks up your answer and breaks it down into separate words with speech-recognition software. A camera built into the dashboard also tracks your lip movements to improve the accuracy of speech recognition. A camera built into the dashboard also tracks your lip movements to improve the accuracy of speech recognition. A voice analyzer then looks for signs of tiredness by checking to see if the answer matches your profile. Slow responses and lack of attention are signs of fatigue. If you reply quickly and clearly, the system judges you to be alert and tells the conversation planner to continue the line of questioning. If your response is slow or doesn’t make sense, the voice analyzer assumes you are dropping off and acts to get your attention. If driver displays signs of fatigue, the artificial passenger might be programmed to open all the windows, sound a buzzer, increase background music volume, or even spray the driver with ice water. 2.5 Devices Usedin Artificial Passenger Eye tracker Voice recognizer or speech recognizer Natural language processor Driver analyzer Conversational planner Alarm Microphone Camera 2.5.1 Working Components Eye-Tracker Collecting eye movement data requires both hardware and software.
- 2. 2 Figure: 1 Hardware: Head-Mounted Systems or Remote Systems. Both systems measure the corneal reflection of the infrared LED which illuminates and generates a reflection off the surface of the eye. This action causes the pupil to appear as a bright disk in contrast to surrounding iris and creates a small glint underneath the pupil which is used for calibration and tracking. Head mounted systems: Use multiple data points to record eye movement and measures pupil glint from multiple angles. Remote systems: In contrast, measure the orientation of the eye relative to a fixed unit such as cameras. Software: Data collection and analysis is handled by eye- tracking software. Software catalogs eye-tracking in one of the two ways. ERICA’s Eye Gaze software uses a small red x to represent eye movement. In other, data is stored as a series of x/y coordinates related to specific grid points on the computer screen. Automatic Speech Recognition There are two ASRs used in the system: First one is “Speaker Independent” and used for decoding voice signals of the driver.Second one operates with voice car media and decodes tapes, audio, telephones, mails etc. Natural Language Processor Processes the decoded signals of voice or text data provided from the ASR. Identifies related meanings from the contents of the decoded messages. Produces variant of responses. This output goes to the driver analyzer as an input. Driver Analyzer Receives the textual data and voice data. Measures the time response using a clock. Time responses, conclusions about driver’s alertness will be passed on to the conversational planner. Conversational Planner It is the heart of the system. Instructs thelanguage generator to producethe response. If the driver is in perfect condition CP instructs the language generator to continue the conversation otherwise it will be instructed to change the conversation. The following is a typical scenario involving Artificial Passenger. Imagine, driver “Mani” returning home after late nights. His head starts to nod. AP: HeyMani, what did you get your daughter for her birthday? Mani: It’s not her birthday! AP: You seem a little tired. Want to play a game? Mani: Yes. AP: You were a wiz at “Name that Tune” last time. I was impressed. Want to try your hand at trivia? Mani: ok. AP: Pick a category: Hollywood Stars, Magic Moments or Hall of Fame? Mani: Hall of Fame. Alarm If the CP (conversational planner) receives information that the driver is about to fall asleep an alarm system is activated. Microphone For picking up words and separate them by some internally used software for conversation. Camera This will track the lip movements of the driver. Used to improve the accuracy of the speechrecognition. Figure: 2
- 3. 3 1.6 Steps Involved in Tracking Automatically initialize lips and eyes using color predicates and connected components. Track lip corners using dark line between lips and color predicate even through largemouth movement like yawning. Construct a bounding box of the head. Determine rotation using distances between eye and lip feature points and sides of the face. Determine eye blinking and eye closing using the number and intensity of pixels in the eye region. Determine driver vigilance level using all acquired information. 1.7 Detecting Driver Vigilance Aiming a single camera at a head of the driver. Detecting frequency of up and down nodding and left to right rotations of the head within a selected time period with the camera. Determining frequency of eye blinking and eye closing. Determining frequency of yawning of the driver within the selected time period with the camera. Generating an alarm signal in real time if the frequency value of the up and down nodding, the left to right rotations, the eye blinking, the eye closings, the yawning exceeds a selected threshold value. 1.8 Applications Interface withNeighboring Cars -Determines if a driver presents a high safety risk for ex. falling asleep, tired, inexperienced or under the influence of alcohol and signals the cars nearby to be careful of the driver. Medical Application -The system can monitor a driver and detect if they are sick ,for ex. having a stroke or heart attack. In any problem it alerts the vehicles nearby , so the driver there can become alert. Opens and closes the doors and windows of the car automatically. It is also used for the entertainment. Also used in cabins in airplanes, trains, boats etc. 1.9 Features of Artificial Passenger IBM’s Artificial Passenger is like having a butler in your car- someone who looks after you, takes care of your every need, is bent on providing service, and has enough intelligence to anticipate your needs. This voice-actuated telematics system helps you perform certain actions within your car hands-free: turn on the radio, switch stations, make a cell phone call, and more. It provides uniform access to devices and networked services in and outside your car. It reports car conditions and external hazards with minimal distraction. Plus, it helps you stay awake with some form of entertainment when it detects you’re getting drowsy. 3.WORKLOAD MANAGEMENT In this section we provide a brief analysis of the design of the workload management that is a key component of driver Safety Manager. An object of the workload manager is to determine a moment-to-moment analysis of the user's cognitive workload. It monitoring local and remote events, andprioritizingmessagedelivery.There is rapid growth in the u se of sensory technology in cars. These sensors allow for the monitoring of driver actions (e.g. application of brakes, changing lanes), provide information about local events (e.g. heavy rain), and provide information about driver characteristics (e.g. speaking speed, eyelid status)There is also growing amount of distracting information that may be presented to the driver (e.g. phone rings, radio, music, e-mail etc.) and actions that a driver can perform in cars via voice control. The relationship between a driver and a car should be consistent with the information from sensors. The workload manager should be designed in such a way that it can integrate sensor information and rules on when and if distracting information is delivered. This can be designed as a “workload representational surface”. One axis of the surface would represent stress on the vehicles and another, orthogonally distinct axis, would represent stress on the driver. Values on each axis could conceivably run from zero to one. Maximum load would be represented by the position where there is both maximum vehicle stress and maximum driver stress, beyond which there would be “overload”. Workload manager is closely related to the event manager that detects when to trigger actions and/or make decisions about potential actions. The system uses a set of rules for starting and stopping the interactions (or interventions).It controls interruption of a dialog between the driver and the car dashboard (for example, interrupting a conversation to deliver an urgent message about traffic conditions on unexpected driver route).It can use answers from the driver and/or data from the workload manager relating to driver conditions, like computing how often the driver answered correctly and the length of delays in answers, etc. It interprets the status of a driver’s alertness, based on his/her answers as well as information from the workload manager. It will make decisions on whether the driver needs additional stimuli and on what types of stimuli should be provided (e.g. verbal stimuli via speech applications or physical stimuli such as a bright light, loud noise, etc.)And whether to suggest to a driver to stop for rest. The system permits the use and testing of different statistical models for interpreting driver answers and information about driver conditions. The driver workload manager is connected to a driving risk evaluator that is an important component of the Safety 4.Privacy Aspects Addressingprivacy concerns:Thesafety driver manager framework should be designed such that it will be straightforward for the application designers to protect theend user’s privacy. This should include encryption of themessage traffic from thevehicle, through carrier’s network, and into the service provider’s secure environment, such that the driver’s responses cannot be intercepted.This can be achieved through the use of IBM Web Sphere Personalization Server or Portal Server, allowing the end user an interface to select options and choices about the level of privacy and/or the types of content presented. An example of such an option is the opportunity for drivers to be informed about theexistence of the Artificial Passenger capability, with clear instructions about how to turn it off if they opt not to use it.
- 4. 4 5. The working of Artificial Passenger Figure: 3 Figure: 4
- 5. 5 6.FUTURE IMPLEMENTATION Will provide us with shortest time routing based on road conditions changing because of weather and traffic, information about the cars on the route, destination requirement. 7.CONCLUSION Method for monitoring driver alertness sufficient time to avert an accident. Successful implementation of Artificial Passenger would allow use of various services in car like reading emails, navigation, downloading music files, voice games etc. compromising on driver safety. We suggested that such important issues related to a driver safety, such as controlling telematics devices and drowsiness can be addressed by a special speech interface. This interface requires interactions with workload, dialog, event, privacy, situation and other modules. We showed that basic speech interactions can be done in a low-resource embedded processor and this allows a development of a useful local component of Safety Driver Manager. The reduction of conventional speech processes to low – resources processing was done by reducing a signal processing and decoding load in such a way that it did not significantly affect decoding accuracy and by the development of quasi-NLU principles. 8.ACKNOWLEDGMENTS I would like to Thank my guide respected B.Satish sir Assoc. Professor, Dept. of CSE who had supported meand guided me for doing this paper. 9.REFERENCES [1].http://www.Google.com [2].http://www.Wikipedia.org/wiki/Artificial_Passenger [3].https://www.scribd.com/document/Artificial-Passenger [4].http://www.springerlink.com/content/passenger