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Reducing Driver Distraction Using Integrated Smart Sensors.

INTRODUCTION

As mobile phones provide connectivity throughout the world, it plays an important role in everyone's life. In recent years, the usage of mobile phones are drastically increased in calling, texting, internet surfing, entertainment, etc. Though mobile phone takes the human lives to next sophisticated level, it has several risk factors. One of the major problems of mobile phone usage is distraction while driving. Driver Distraction is mainly caused by the usage of mobile phones. Distracted Driving is dangerous and leads to several road accidents. In the year 2015, it killed 3,477 people and 391,000 were injured [1]. Popularity of Smart phones inspired people to use other applications in addition to basic features like calling and texting. In 2014, 18% of drivers used e-mails and 20% of drivers checked social media updates while driving [2]. Google conducted a survey "Our Mobile Planet" in 2013 [3]. The survey reports 93% of smart phone users used their phones on road. Another mobile phone usage while driving survey was conducted in Israel [4] (700 people) and it reports that 81% of people are not texting, 48% ignoring the received message, 13% immediately reads the received message and 39% reads the message when the vehicle is stopped. For calling, 44% of people calls and 19% of people calls frequently. Additionally, 28% of people make calls to others. Several studies reveals that the usage of smart phones while driving significantly increases the road accidents [5]. Smart phones has been used for various purposes: calling, texting, maps and parking, news, social media, searching and services, aid, games, safety and entertainment. A survey [6] conducted for smart phone usage over 757 drivers and the results are shown in Fig 1. From Fig 1, it is clear that majority of the driver's use mobile phones for calling purposes only. Around 2,000 peoples are losing their life by texting in driving over a year [7]. While driving engrossed interest towards media causes several car crashes [8]. A study reveals that mobile phone users cause more road accidents when compared to drunk drivers [9]. To reduce the risk of road accidents, a new technique is needed to avoid mobile phone usage. Nowadays, government agencies and mobile industries are also focused to prevent road accidents [10].

Many governments introduced law against mobile phone usage while driving and they declared it as illegal. Some countries banned mobile phones while driving are Australia, Belgium, Brazil, Malaysia, Mexico, India, Israel and so on. In United States, not all states ban cell phone usage for all types of drivers. 36 states in U.S and Washington D.C. banned mobile phones for new drivers. 19 states and Washington D.C. prohibits all kinds of mobile phone usage by school bus drivers [11]. Mobile industries are also taken various initiative measures to avoid road accidents caused by mobile phones. Mobile applications (app) were developed to prevent driver distraction. Some of the apps silences the incoming text message, silences the calls, block calls, etc. [12]. Vehicle dynamics is important to identify the usage of driver's mobile. Embedded sensors like accelerometers and gyroscopes are used to measure the difference in centripetal acceleration which is caused by vehicle dynamics. This measure is used to identify the speed and orientation of the vehicle (whether the vehicle is static or dynamic). In this paper, a new mobile application is developed to manage driver distraction. This will be helpful to reduce risks of road accidents and improves safety while driving.

This paper proposes automatic blocking of incoming calls and manual operation is fully avoided. It uses integrated sensors (accelerometer, gyroscope) in smart phones and Bluetooth radio. At the end, improved safety is achieved. The main contributions of the paper are listed below.

* A mobile application named "Safety Driver" app is developed to manage incoming calls of the driver. The app will be enabled automatically based on the accelerometer reading. When the accelerometer reading exceeds threshold value (>5kmph), the app will be turned on.

* Bluetooth auto-pairing is introduced to differentiate the mobile user between passenger and driver.

* The app can be customizable by the mobile user using 4 modes of operation.

* When am incoming call is blocked 3 times continuously, a preset alert SMS will be sent to the caller.

The rest of the paper is organized as follows. Section 2 gives the related work. Proposed method is explained in Section 3. The implementation results are discussed in Section 4. The paper is concluded in Section 5.

Related Work:

Reducing risks of mobile phone usage remains an active research and more researchers are carried out in this area. Some of the relevant and recent works are explained here. Quiet Calls [13] is an earlier technique which allows the mobile user to answer the incoming calls silently. It uses three buttons to and sends a voice mail directly to the phone. It does not provide any priority among the incoming calls. Blind Sight [14] is an application which enables the user to access the stored data in mobile during a conversation. It provides stored data without disturbing the conversation and eliminates the need of visual interface. The mobile user gives input by keypad and Blind Sight uses authority feedback which can be heard only by the user. Undistracted driving [15] is an application where context awareness is employed to develop burden-shifting, time-shifting, and activity-based sharing. The context awareness collects information about the location and movement of the call recipient, and the identity of the caller. This information is useful to send default message to caller automatically and share arrival time of the user. Driver Detection System (DDS) [16] is developed to identify the user is the driver or passenger based on the phone based sensing system. This method differentiates the passenger and driver by various micro-movements of them. Some of the micro-movements include: based on the side the user enter, based on the leg the user enter into the car, leg presses the pedal, seatbelt, etc. These movements can be used to identify the driver from the passenger. AT&T Drive Mode [17] is also an anti-texting mobile application which automatically replies to the received message when the vehicle is moving. Initially, the speed of the vehicle is monitored. When the speed exceeds 25kmph, the app will turn on and reply automatically. When the speed of the vehicle becomes less than 25kmph and the speed is maintained for more than 5minutes, the app will be turned off and the user can able to view the calls. The app directs all calls to voicemail immediately. Additional allow list is presented, which allows the user to enter 5 contacts. Music and navigation setting enables one music and navigation app while AT&T Drive Mode app is running. TXT Blocker [18] is an online text blocking service which requires online subscription. It uses velocity and geographic algorithms to determine whether the user is driving or not. It disables texting; block calling, permits to call numbers from safe lists and emergency number. It is fully customizable by user; the user can enable or disable the options. Key2SafeDriving is a product used to manage mobile phones while driving [19]. It redirects incoming calls and incoming messages. It also blocks dialing and texting. It is fully customizable by the user. Drive smart Plus [20] is also another app to reduce mobile usage risk while driving. Another approach to differentiate the passenger and driver of a moving vehicle is proposed [21]. Vehicle dynamics and embedded sensors in the mobile phone are utilized. It does not require Bluetooth module to be present inside the car. It needs the embedded sensor (accelerometer, gyroscope, etc.) and plug-in reference module for the cigarette lighter or OBD-II port. This method is evaluated with two mobile models and two different cars in different cities over a period of one month. The experimental results shows that the proposed method is precise. In order to provide effective solution for driver distraction by mobile phone usage, a new integrated smart sensor method based mobile app named "Safety Driver" is proposed. This method utilizes accelerometer to block incoming calls while driving. It also differentiates the passenger and driver by the use of Bluetooth pairing. This method performs well and produces better results that state of art approaches.

Proposed Work:

In order to provide effective solution for driver distraction by mobile phone usage, a new integrated smart sensor method based mobile app named "Safety Driver" is proposed. The proposed method uses vehicle dynamics to manage incoming calls while driving. The difference between passenger and driver is determined by Bluetooth pairing technology.

It requires a Bluetooth radio to be implemented in the vehicle. In recent years, cars are coming with inbuilt wireless Bluetooth facility. In case of two-wheelers, Bluetooth module needs to be fixed manually. The operation of the proposed method is shown in Fig 2. The proposed method operates in four phases. They are:

A. Sensor value reading:

The proposed method uses accelerometer to measure the speed of moving vehicle. It is an inbuilt electronic component in the Smartphone and used to measure tilt and movement. It is used to measure the speed and identifies the mobile phone is stationary or moving. When the accelerometer values in zero, the mobile phone is not moving. The accelerometer value changes according to the movement of the vehicle. The Safety Driver app will be initiated when the speed of the vehicle crosses 5kmph.

B. Bluetooth Auto-pairing phase:

In this phase, auto-pairing between Bluetooth devices takes place. The proposed method requires a Bluetooth device in the vehicle. The user's mobile is already paired with the vehicle via Bluetooth. For identifying the user driving in the own vehicle or a passenger of the other moving vehicle, simple verification technique is needed. To achieve this, Bluetooth Auto-pairing should be done. When the accelerometer value crosses the threshold limit, the vehicle is considered as moving. Then, Safety Driver app is initialized and Bluetooth will be enabled automatically by the app. Now, the user mobile automatically starts pairing with the Bluetooth device in the vehicle. When auto-pairing fails, the app considers the mobile phone user as passenger and turns off the Safety Driver app. When auto-pairing is complete, the app decides the mobile phone user is driving. Then, it goes to next phase.

C. Call Blocking phase:

When auto-pairing is succeeded, call blocking phase will be initiated. Call blocking will be done continuously till the Safety Driver is disabled. This is the important phase and operates in 4 modes. This app is fully customizable by the user. By default, Mode 1 will be selection. The user can also select any other modes based on the situation.

* Mode 1--Block all calls

* Mode 2--Block unsaved contacts

* Mode 3--Block from list

* Mode 4--Cancel All Block

1) Mode 1--Block all calls:

By default, Mode 1 will be selected. After auto-pairing, the app will block all incoming calls automatically. When an incoming call is coming three times from same number, a preset alert SMS will be sent to the caller. This process continues till the vehicle stops moving. The app will be disabled when the accelerometer value becomes less than threshold limit.

2) Mode 2--Block unsaved contacts:

The mobile phone user/ driver can customize the setting of the app based on the requirement. In mode 2, the app will block all the incoming calls from any unsaved numbers. When an incoming call is coming continuously three times from unknown number, preset alert SMS will be sent to the caller. In this mode, the mobile phone user/ driver can receive calls from the contacts saved in the mobile phone.

3) Mode 3--Block from list:

The Safety Driver app is fully user-profile based. The mobile phone user/ driver can create a block list which contains the list of mobile numbers. The app will block incoming calls only the incoming call number is present in the block list. When the incoming call number is not available in the block list, the call will be received by the driver.

4) Mode 4--Cancel All Block:

This mode is useful for mobile phone users while traveling in own vehicle as passenger. As mentioned earlier, Bluetooth auto-pairing will be done once the vehicle starts moving. When the mobile phone user is not driving, the user can turn on mode 4. This mode will cancel all blocks and all incoming calls will be received by the user.

D. Auto-texting phase:

In this phase, a preset alert SMS will be sent to the caller from the driver mobile phone. Once the app turned on, it starts to block all incoming calls. When an incoming call is coming three times from same number, a preset alert SMS will be sent to the caller. This is done with the help of telephone manager. The telephone manager identifies the last blocked number. Then, it gain access to send message to the caller. Finally, an alert SMS will be sent to the caller.

The alert SMS is predefined by the mobile phone user/driver of the Safety Driver app. Example of alert SMS: "I am in driving, Avoid phone calls while driving".

Implementation Results:

The proposed method is implemented with accelerometer sensor collected data on Android Smart phones. The 'Safety Driver' app is developed in Android platform. The Smartphone have an accelerometer sensor to measure the speed of the vehicle. Both Smartphone and vehicle have Bluetooth radio for identifying driver from the passenger. When the accelerometer value crosses the threshold limit, the 'Safety Driver' will be turned on and automatically enable the Bluetooth. Next, Bluetooth auto-pairing will be done between Smartphone and vehicle. Once the pairing is done, the app starts working in the background. When the pairing is unsuccessful, the app will be turned off automatically. The home screen of Safety driver app is shown in Fig 3(a).

The four modes are displayed in the screen and mode 1 is selected automatically. From Fig 3(b), it is clear that the app is fully customizable and the user can select any one of the modes based on their requirement. The snapshot of Mode 1 is shown in Fig 3(b). It is clearly shown in figure that the Bluetooth is enabled after the app is turned on. The block all calls mode will block all incoming calls. When the caller calls continuously 3 times, an alert SMS will be sent to the caller. As shown in Fig, the user can modify the message also. The snapshot of Mode 2 is shown in Fig 3(c). The block unsaved contacts mode will block all incoming calls from unknown numbers. The incoming calls from saved contacts will not be blocked and the user can receive the call. In this mode also, an alert SMS setting is presented. Shown in Fig, the user can modify the message as "Hi... don't call me while I'm driving" at any time alert SMS setting is presented.

Conclusion:

In this paper, a mobile application named 'Safety Driver' app is implemented in Android platform. The app is developed to reduce driver distractions and avoid road accidents caused by mobile phone usage. The proposed application uses sensors in the Smartphone and Bluetooth module. The app will turned on when the accelerometer value exceeds the threshold limit. Bluetooth auto-pairing is done to improve the usability of mobile phone user/driver. The app is fully customizable by the user and it can operate in four modes. By default, the app will block all incoming calls automatically. When an incoming call is blocked continuously from same number, the app will send an alert SMS to the blocked number. This Safety Driver APP is developed using Android platform. This app is very useful to manage incoming calls while driving. This results to improved road safety and reduces the risks of road accident by the usage of mobile phones.

REFERENCES

[1.] Distracted Driving, 2016. https://www.nhtsa.gov/risky-driving/distracted-driving.

[2.] State Farm, Distracted Driving, 2014. http://www.multivu.com/players/English/7292854-state-farmdistracted-driving-survey-cellphone-use/links/7292854-2014-Distracted-Driving-Report-Final.pdf

[3.] Ipsos Media, C.T., 2013. "Our Mobile Planet: Israel. Understanding the Mobile Consumer", Google.

[4.] Tomer-Fishman, T., 2010." Distraction in Driving by the Use of Electronic Communication Devices", The Israeli Road Safety Authority.

[5.] Asbridge, M., J.R. Brubacher, H. Chan, 2013. "Cell phone use and traffic crash risk: aculpability analysis," Int. J. Epidemiol., 42(1): 259-267.

[6.] Musicant, O. et al., 2015. "Do we really need to use our smartphones while driving?" Accident Analysis and Prevention, 85: 13-21.

[7.] Hanowski, Richard, 2009 "Driver Distraction in Commercial Vehicle Operations".

[8.] Valencia, Milton, 2010. "The Boston Globe MBTA: Conductor in Boston trolley crash was texting his girlfriend".

[9.] Strayer, David; Drews, Frank; Crouch, Dennis, 2003. "Fatal Distraction? A Comparison of the CellPhone Driver and The Drunk Driver" (PDF). University of Utah Department of Psychology.

[10.] Distracted driving and driver, roadway, and environmental Factors, 2010. http://www.distraction.gov/download/research-pdf/Distracted-Driving-and-Driver-RoadwayEnvironmental-Factors.pdf.

[11.] Yang, J., S. Sidhom, G. Chandrasekaran, T. Vu, H. Liu, N. Cecan, Y. Chen, M. Gruteser and R. Martin, 2011. "Detecting driver phone use leveraging car speakers," in Proc. ACM 17th Annu. Int. Conf. Mobile Comput. Netw., pp: 97-108.

[12.] Nelson, L., S. Bly and T. Sokoler, 2001. "Quiet calls: Talking silently on mobile phones," in Proc. SIGCHI Conf. Human Factors Comput. Syst., pp: 174-181.

[13.] Li, K.A., P. Baudisch and K. Hinckley, 2008. "Blindsight: Eyes-free access to mobile phones," in Proc. ACM SIGCHI Conf. Human Factors Comput. Syst., pp: 1389-1398.

[14.] Lindqvist, J. and J. Hong, 2011. "Undistracted driving: A mobile phone that doesn't distract," in Proc. 12th Workshop Mobile Comput. Syst Appl., pp: 70-75.

[15.] Chu, H., V. Raman, J. Shen, R. Choudhury, A. Kansal and V. Bahl, 2011. "Poster: You driving? talk to you later," in Proc. ACM 9th Int.Conf. Mobile Syst., Appl. Services, pp: 29-39.

[16.] AT&T driver safety app 2012. http://www.theverge.com/2012/8/15/3243963/att-texting-driving-safety-app.

[17.] Txtblocker, 2008. http://www.txtblocker.com/

[18.] Key2safedrivingapp, 2012. http://www.key2safedriving.com/

[19.] Drivesmart plus, 2014 http://tinyurl.com/4v7oygy.

[20.] Musicant, O et al., 2015. "Do we really need to use our smartphones while driving?" Accident Analysis and Prevention, 85: 13-21.

(1) V. Arulalan, (2) Dr. K. Suresh Joseph, (3) G. Balamurugan

(1,3) Assistant Professor, Department of Computer Science and Engineering, Christ College of Engineering and Technology, Pondicherry University, Pondicherry-605010, India.

(2) Associate Professor, Department of Computer Science and Engineering, School of Engineering and Technology, Pondicherry University, Puducherry. India.

Received 14 September 2017; Accepted 15 October 2017; Available online 30 October 2017

Address For Correspondence:

V. Arulalan, Assistant Professor, Department of Computer Science and Engineering, Christ College of Engineering and T echnology, Pondicherry University,Pondicherry-605010, India.

E-mail: arulalan@christcet.edu.in

Caption: Fig. 1: Usage of Smart phones in general and driving

Caption: Fig. 2: High Level Diagram of Proposed System

Caption: Fig. 3: (a) Snapshot of the app home screen, (b) Snapshot of Mode 1, (c) Snapshot of Mode 2

Caption: Fig. 4: (a) Cancel all block, (b) Snapshot of the alert SMS
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Author:Arulalan, V.; Joseph, K. Suresh; Balamurugan, G.
Publication:Advances in Natural and Applied Sciences
Article Type:Report
Date:Oct 1, 2017
Words:3177
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