TTraffic: A Fully Integrated Accident Management System in Vehicular Networks Through Smartphones

Transcription

1 1 TTraffic: A Fully Integrated Accident Management System in Vehicular Networks Through Smartphones Sevgi Kaya, Burcu Gulfem Ozergin, Halid Ozsoy Taskin Kocak, Cagri Gungor, Department of Computer Science, ETH Zurich, 8092 Zurich, Switzerland Department of Computer Engineering, Bahcesehir University, Istanbul, Turkey Department of Computer Engineering, Abdullah Gul University, 38002, Kayseri, Turkey Abstract Recent years have witnessed new breakthroughs on emergency management systems and a reduced fatality rate caused by car accidents as a consequence of it. With the recent advances in wireless communication technologies, the trends in the automatic crash notification industry changed from individual reporting or infrastructure-based data sources to mobile data gathering devices such as smartphones. Our research primarily focuses on investigation of the most useful yet simple interfaces to develop an accurate and effective crash notification service based on detecting anomalities in the movement of the smartphone. For this purpose, a mobile application has been developed on both Android and iphone platforms to detect the accidents and gather the relative data for determining the crash severity. In this paper, the proposed system architecture along with the detailed component descriptions and technical steps of the development phase are presented in detail. Furthermore, we introduce a web server application to process and illustrate the raw data transmitted from Android/iPhone mobile client applications. The paper also presents real life scenarios to demonstrate the underlying system architecture and its efficiency in emergency cases. We show that our fully-integrated emergency management system yields very promising results in the early detection of accidents. Index Terms Real time services; Context aware service and applications; Information distribution services; Location-based services; Mobile web-based applications and services; Vehicular network applications and services I. INTRODUCTION Over the last years, many research studies have been conducted to exploit the advances in sensing, communication and dynamic adaptive technologies for coping with the traffic related issues. In fact, one of the most crucial results of traffic congestion is the delay of the emergency services such as police, fire and rescue operations and medical services which may yield to the death of crash victims and huge amounts of financial loss. Every year, nearly 20,000 crash victims lose their lives before reaching to hospital[1]. According to the experts, the main reason behind these deaths is the failure of reaching the victim throughout the so-called Golden Hour where the treatment is most effective. Despite of the recent advances in wireless communications and technological infrastructure behind emergency management systems, crash response time is extremely lengthy to provide the most effective treatment for crash victims. In the literature, there exist wide varieties of emergency management services which aim to reduce the crash response time as possible. These models can be classified as Precrash and Post-crash systems. While pre-crash models use radar, laser sensors and cameras to detect the damages caused directly by the crash, post-crash systems focus on eliminating the chances of crash injuries or fatalities due to the secondary effects of collision, such as fire. The role of emergency service models in this sense is beyond the foreseen. They play quite an important part in both determining the severity of an accident and reducing the crash response time by transmitting the crash information to concerned departments such as emergency, police and fire departments. The biggest impact of the emergency service models come from the fact that it provides the only possible way to help the crash victims and alleviate the results of a collision as effective as possible. For many years, crash response systems relied on traffic reporters, static cameras and radars to detect the accidents on roads. Although individual reporting certainly helps to find out the crash place, it may take long hours to realize an accident especially in relatively unpopulated places. Hence with the recent advances in wireless communication technologies, the trends in the automatic crash notification industry changed from individual reporting or infrastructure-based data sources to mobile data gathering devices such as smartphones. The idea behind emerging emergency management systems is to deploy smartphones on vehicles to detect the accident via a mobile application which listens for accelerometer changes. Once the accident has been detected, the application automatically notifies the emergency medical personnel by transmitting the location information and a short video of the accident for determining the severity of it. Initial estimates reveal that the fatality rate can be reduced by 30% with the usage of recently emerged crash notification systems that rely on wireless communications.[2] In this paper, we propose a mobile client application which gathers crash-related data and transmits them to a central web server for detecting accidents. In server side, we introduce our web application which detects crash location and notifies the emergency responders of accidents such as emergency service, police and fire departments in real time. Moreover, we describe the development phases of our emergency management system and evaluate its performance in different use case scenarios.

2 2 The rest of the paper is organized as follows. Section 2 describes related work. Section 3 presents a brief review of the system architecture. In Section 4, system components and development phases of the mobile application have been explained. Section 5 introduces the web server application and describes its key features. Section 6 illustrates the evaluation of our system by simulating different use cases. Finally, Section 7 concludes the paper by assessing the outcomes of our proposed system. II. RELATED WORK In the literature, there exist wide varieties of emergency management services which aim to reduce the crash response time as possible. These models can be classified as Precrash and Post-crash systems. While pre-crash models use radar, laser sensors and cameras to detect the damages caused directly by the crash, post-crash systems focus on eliminating the chances of crash injuries or fatalities due to the secondary effects of collision, such as fire. Based on this classification there are 5 different organizational categories related with our work. The first category consists of the solutions offered by top telecom companies such as China mobile, Vodafone[3-4], Verizon [5-6], etc. The second category is named as the solutions by municipalities. The third category is the solutions offered by corporations such as General Mobile[7], Toyota[8], Hyundai[9] etc. Fourth category includes the solutions developed by governments. Last category is the EU projects such as CVIS, AISE and HAVEit[10-12] which aims at providing comprehensive emergency management solutions. Contrary to the longevity experiences on this issue, most of the proposed systems do not offer fully-integrated practical and cost-effective solutions which can be directly applied to the vehicles in real time. III. THE SYSTEM OVERVIEW In this paper, we present an accurate and effective crash notification service based on detecting anomaly on the movement of the smartphone to identify the accident case. Fig.1 illustrates our proposed system architecture along with its components and key features. The system architecture consists of two key components: mobile client and web server application. The mobile application has been developed on both Android and iphone platforms to detect the accidents and gather the relative data for determining the crash severity. Once the crash has been detected, the system automatically sends accident related data to the web application. The web application processes the raw data transmitted from Android/iPhone mobile client applications and illustrates the vehicle coordinates and its associated crash video on a map along with its address information. This service is specifically designed for emergency management centers to provide instant notification and easy-to-access call mechanism to the nearest hospital, fire and police departments. The emergency management personnel can reach to user and alert concerned departments right after the crash. Figure 1: Overview of the system architecture Figure 2: Overview of the system architecture IV. THE MOBILE CLIENT APPLICATION Figure 2 illustrates the main screen of the mobile application. The application starts with the screen that shows the view of the camera. In this screen, there are some indicators regarding to accelerometer measurements. On the lower left, there is a speedometer that shows the speed of the vehicle. This data are collected using the GPS of the device. On the lower right, current G-Force of the device is shown for each axis. These values are received from the accelerometer of the device. On the top of the screen, there is a bar that holds the sensitivity slider. This sensitivity slider sets the lower limit of the sensitivity of the crash detection system. Higher slider values require more force to be applied in order to trigger the system. On the right side of the screen, there is a small control panel which consists of two control buttons. The buttons control the sensitivity bar by displaying or hiding it. In Setting section, there are three options and their submenus to allow user to choose the communication type after the crash. The system automatically sends the accident location by either SMS or messages to concerned emergency departments depending on the choice of the user. Usage When the application is started, crash detection system becomes activated. The camera immediately starts recording and the system tracks the G-Force measurements unless the user interrupts the operation. The maximum dura-

3 3 Figure 3: The flow chart of the data gathering algorithm tion for an accident video can be easily set by the user via our user interface. After maximum duration is reached during a video record, recording stops. The video is not saved and released from the memory immediately. Instead, new record starts right after that. Once an anomaly has been detected, the system collects all of the video data along with the location information and sends the data to a central server. A. Crash Detection Algorithm The data flow chart of the algorithm is illustrated in Figure 3. As it has been stated in the previous section, the whole crash detection algorithm is based on the accelerometer measurements. Each time accelerometer value is received, the values of three axis (x,y,z) are sent to the function that checks if there is a abnormal situation. In this context, the abnormal situation refers to exceeding threshold values in at least one of the three axes. If one of the values is over of the threshold value, the system is triggered. However, sudden changes in the accelerometer measurements is not solely depend on accidents. In order to avoid false positive data, an alert pops up to ask the users whether they want to cancel the data transmission operation or not. Including the user feedback to the application provides more reliable mechanism to avoid false positives. Figure 4 demonstrates the procedure in detail. After user confirms that there is an accident and need help or unable to confirm it, post accident system is being activated. The camera stops capturing video. When video is available to take actions on it, internet connection of the device is checked. If the device has an internet connection, the taken video starts to be compressed and uploaded to the servers over an FTP connection. Before all that, emergency contacts receive an with the coordinate information and emergency message for the user. After the video is uploaded to the servers successfully, another is sent with a link of the uploaded video. If the device does not have an internet connection, the video is saved to the to device s photo album. 1) Video Uploads: The videos that have been captured during the accident are uploaded to servers through cellular network connection or Wi-Fi. This operation is completed in background. We set up this connection through FTP and the connection settings (hostname, username, password, upload location, filename) are done hard-coded. The video is converted into bytes and transferred over this connection. 2) Sending After Accident: For this application, e- mail sould be sent without user interaction. In settings, there are two text fields: one for recievers and the other for the message. The coordinates and a short video of the accident are appended to the . 3) Sending SMS After Accident: Likewise sending , sending SMS without user interaction is not possible. Hence, it should be handled via a web service. In the application, settings for SMS are completed for both contact number and text message. 4) Making Emergency Call: During the first time that the application has been installed, the users can set emergency

4 4 4) Run the geocoder in the background to convert the raw coordinates to address information. 5) Provide an easy-to-access call mechanism to alert hospitals, fire and police departments in the case of emergency. Figure 4: Our mobile application allows users to cancel the sending of SMS message in 10 seconds contacts which are automatically called right after the crash. V. THE WEB SERVER APPLICATION In this phase of the project, we developed a web application which illustrates the location of the crash along with its video retrieved from our Android/iPhone mobile client applications. Client application has an underlying service for sensing an anomay in accelerometer measurements. Once an anomaly has been detected, location information and a short video which consists of the few seconds of crash views are transmitted to server application via an service for further processing. In server side, incoming s are parsed into components to reveal the location information and crash videos. Later on, the extracted data are saved to a back-end database and illustrated in a map via our web application. The web application is designed to notify emergency responders of accidents such as emergency service, police and fire departments by sending audio messages. A. Motivation The main reason that leads to the idea of a web application is to develop a framework to analyse and test our raw crash data retrieved from the test vehicles on the field that use our Android/iPhone application. The web application allows us to illustrate multiple crashes occurred simultaneously and alert concerned departments such as hospitals, fire and police departments by calling them through its interface. Hence we are able to find out the exact address information and determine the severity of the crash with its video uploaded to the server in real-time. The web application is focused on achieving several aims as listed below: 1) Illustrate the map-view of the data collected by the Android/iPhone smartphone applications. 2) Generate random crash data for various setups and find out the address information associated with each coordinate. 3) Parse the crash which consists of the coordinates and a short video of the accident to extract the location information and to save the crash video into server. B. The Interface Figure 5 depicts an accident management setup for a single crash alert. Each of the crash notifications that appear in the web application are denoted by a single marker and an information window associated with it. The marker in the figure pins the crash location. Information window is triggered when the marker is clicked and it illustrates the crash-related data to describe the crash in more detail. On the upper-left corner, information window shows the cell phone number for calling the crash victim right after it has occurred. The crash video appears in the middle of the information window to determine the severity of the crash. Finally, a fully described street address is located on the lowerleft corner of the information window. Our web application provides a fully-featured calling system via Skype API. The emergency management personnel can alert the concerned departments about the crash by simply calling them via Skype. Lower-left corner of our web page has three buttons to activate the calling procedure. The buttons trigger an interface to notify emergency, police and fire departments respectively. C. Use Case Scenario The section presents a crash scenario using our web application. In our scenario, the purpose is to simulate an ordinary traffic crash and the emergency response associated with it. The scenario starts with an incoming sent by the crash victim via our mobile application. The incoming s are parsed and inserted into the database in the format illustrated in above. Each crash is associated with an automatically generated unique identifier number and latitude/longitude pair retrieved from the subject field of the incoming . Furthermore, the video file is instantly uploaded to the server computer and the file path is stored in the database under the caption of description attribute. Once the procedure is completed, the resulting crash information is illustrated in the web interface. Our web application enables the emergency management personnel to call the concerned organizations such as emergency, police and fire departments via just clicking the buttons in the lower left corner. The buttons instantly connects with the already set Skype account and triggers a Skype interface to call the emergency personnel. Figure 6 demonstrates the triggered Skype interface right after clicking the blue button in the lower left corner. VI. CONCLUSIONS In this paper, we introduced a fully integrated emergency management system for traffic accidents. We then evaluated our model under various use case scenarios to determine its

5 5 Figure 5: The overview of the user interface Figure 6: The triggered Skype interface for calling the emergency personnel feasibility for near-future traffic flow prediction. The proposed system presents promising results in the early detection of accidents. VII. ACKNOWLEDGEMENTS This work was funded by the Turk Telekom Research & Development Center. Project: Accident Detection and Management on Vehicular Networks REFERENCES [1] Martinez, F.J., Chai-Keong Toh, Cano, J.-C., Calafate, C.T., Manzoni, P., Emergency Services in Future Intelligent Transportation Systems Based on Vehicular Communication Networks, Intelligent Transportation Systems Magazine, IEEE, vol.2, no.2, pp.6,20, 2010 [2] Japanese Government MLIT Solution, [Online] Available: [3] ITS Handbook Japan, [Online]. Available: [4] ITS US Forum Presentation, [Online]. Available: [5] 9] AIDER Final Report, [Online]. Available: _AIDER _Final%20Report.pdf [6] ATLANTIC-A thematic long-term approach to networking for the telematics and ITS community [Online]. Available: soton.ac.uk/archive/its/atlantic.htm, [7] Advanced telematics for enhancing the safety and comfort of motorcycle riders [Online]. Available: [8] Reliable application specific detection of road users with vehicle onboard sensors [Online]. Available: [9] European Union ITS Project: COOPERS, [Online]. Available: [10] H. Greenberg, An Analysis of Traffic Flow, International Journal on Operations Research and The Management Sciences,vol.7, pp.79-85, [11] PREVENT OBU, [Online]. Available: [12] R. Uzcategui, A. de Sucre, G. Acosta-Marum, Wave: A tutorial-[topics in automotive networking], IEEE Communications Magazine, vol. 47, no. 5, pp , May 2009.