Blackspot Warning System Identification and Analysis

Transcription

1 Blackspot Warning System Identification and Analysis Ajinkya Patankar, Prof.S.G Walunj, Anand Pimple, Darshan Kadhane, Vishwakarma Institute of Information Technology, Pune Abstract In today s world, road and transport has become an integral part of every human being. An injury severity based and a normal black spot identification have been performed and the number and severity of accidents on the identified locations have been compared. By identifying the spot and further processing on hot spot data through clustering where clustering is the process of making a group of abstract objects into classes of similar objects. Geo- fencing is use to define the geographical boundaries.geo-fences when crossed by an equipped vehicle or person can trigger a warning to the user or operator via notification so that driver is aware the possibilities of accident and according to it can change driving method. Index Terms Android,Database Analysis,Dependency Analysis,Real-Time Application,Scenario Analysis and Blackspots I. INTRODUCTION ROADWAYS are the most important mode of transport and mobility in the 21st century. But because of the excessive population and ever-increasing number of vehicles on the road, it has become difficult even for civic authorities to stop and control accidents. Accident-Hotspot warning application will alert and guide the travellers to drive safely and avoid accidents. This app is mainly developed in Android which will focus on searching, alert, notification about the accident-prone area( and the available emergency services nearby). Also, the accessibility of the users is not restricted, so it will be increase the scope of project. This project is intended for making use of todays technology of Android Development, Database management, Map extraction. Currently, there are many open-source and commercial tools available for Android Development, Database Management and Maps Extraction. So, evaluation of tools is an important job in order to find more efficient tool. Android Studio is a tool which basically used for preparing software emulation to the apps. II. STUDY AREA If the accident percentage is more on upcoming spot then one could by pass the road by taking left or right turn which is before the hot-spot and again connect to previous road. If user required some services like nearby hospital, petrol pump, hotels etc. is provided on map. For accessing current accidental data the database will connect to a particular newspaper. So that the driver will get an idea about recent accidents.so updated information will help a lot and a driver will aware of it. For analysing a data, we are using clustering. We are using clustering for data analysis. Important points of project are Google Maps API and Database Management. Start from Android App Development with the help of Android Studio, then extract Google Maps API and prepare their database with respect to location of Hotspot, time of alert notification, provision for the user to input the information, etc. Users of this product environment are developers, end-users, customers, public authorities. So, it is reasonable to assume that an average developer has knowledge about functionalities and usage of cloud tools. For other users detail documentation and tutorials will be provided. Apps are portable means running on most number of different platforms without additional efforts. For tools operations, we can develop an app using various tools like android studio, eclipse, etc. So, our app uses a combination of database development and management, android app development, and Google Maps API. III. LITERATURE SURVEY We went through a couple of Research papers by international University students and found the following methods as useful for a low budget country like India. Because road safety and Identification is the sole prerogative 201

2 of the Ministry of National Highways and Road Transport, Government of India, citizens and civilians can only suggest ways to curtail road accidents. They are: 1) Safety Auditing: A basic premise in accident remedial work is that engineering safety principles are adhered to at all times and it is a necessary exercise to ensure that no adverse features are unwittingly introduced at a treatment site. By making extensive use of check lists, safety auditing aims at providing guidance on how to cater for the safety needs of the road user. Objectives of safety auditing include ensuring that all highway schemes operate as safely as possible and that accident producing elements are not present in any completed scheme. It is essential that safety auditing is carried out independently of the remedial measure design team. Figure 1: Expressway Accidents. Figure 2: Reasons of Accidents 2) Analysis and Determination using WSI Method: Yearly accident data (secondary data) for the Pune district were collected from Ministry of Highways, Government of India. The top ranked six accident black spots in Pune were identified using Weighted Severity Index Method (WSI) by assigning scores based on the number and severity of accidents in that particular location during the las year. Weighted Severity Index, (WSI) = (41 x K) + (4 x GI) + (1 x MI) Where, K is the number of persons killed; GI is the number of grievous injuries; and MI is the number of minor injuries. s.no. Location People Killed Grevious Injuries Minor Injuries WSI 1 Wadgaon Sheri Tilak Road Chowk Katraj Dehu Road Nanded City Chowk Bangalore Highway Chandni Chowk

3 Table I: WSI Method Results. 3) Geo-Referencing and Digitising Method: Scanned maps usually do not contain information as to where the area repre-sented on the map fits on the surface of the earth. To establish the relationship between an image co ordinate system and a map(x, y) coordinate system e need to align or geo reference the raster data. Digitizing is the process of encoding the geographic features in digital form as x, y co ordinates. It was carried out to create spatial data from existing hard copy maps and documents. The step involved in this method are as follows. Determination of the locations crash rate: It is determined on the basis of exposure data, such as traffic volume and the length of road section being considered. Rate per 100 million vehicle kilometers (RMV) is the number of crashes per 100 million vehicle kilometers of travel. It is obtained from expression RMV = A * /VT A= No: of crashes, total at the study location during a given Period VT= vehicle kilometers of travel during the given period. IV. PROPOSED ARCHITECTURAL DESIGN Important points of project are Google Maps API and Database Management. Start from Android App Development with the help of Android Studio, then extract Google Maps API and prepare their database with respect to location of Hotspot, time Figure 3: City-wise identified blackspot locations Figure 4: State-wise Road Accidental Data of alert notification, provision for the user to input the information, etc. 203

4 A. RELEVANT TECHNOLOGIES USED 1) Android Studio: It uses gradle-based build support to determine the order in which tasks can be run. It provides the facility to execute the codes in any language suitable to the user be it JAVA,C++, Python, etc. It uses Android-specfic refactoring and quick fixes. It is based on JetBeans s IntelliJ IDEA software. Android Studio is designed specifically for Android development. It allows the programmer to develop a android code in it s IDE and then boot it on simple mobile phone for trial run. 2) Geo-Fencing: Geo-fencing (geofencing) is a feature in a software program that uses the global positioning system (GPS) or radio frequency identification (RFID) to define geographical boundaries. A geo-fence is a virtual barrier. It allows the user to create a standard programs that allows the administrator to set up triggers, so when a device enters (or exits) the boundaries defined by the administrator, a text message or alert is sent. B. ARCHITECTURE The Flow of the diagram is a three-way process. Data will be accessed first in the form of User-related Information which will authorise the user to use the app.this process will be followed in module 1. The next step will be collecting information which the user will give in real-time. This information will be user s location and destination that will be dispalayed on the map with two different connotations. In the next module, the blackspots will appear on the route and as the user changes his position, it will give notification to the user via an HTTP protocol. This will be a form of audio message indicating the user of the nearby blackspot. All this will be covered in the third module. We will examine the features of the system in detail by categorizing them according to their functionality. For each of the feature, we will give an introduction, purpose, diagram and a stimulus/response sequence. C. ARCHITECTURAL IMPLEMENTATION Setup a main Activity.MainActivity is the first step in android development and involves later modifications. It includes the very basic classes, that are required for development. It is one of the most important features of the app. It has Highest priority. It is an open-source operating system emulator. Figure 5: Proposed Architecture Diagram 204

5 url:developer.google.org is the main website that will support the developers whle developing the application. There is the need to download Android-Studio with the latest version of JAVA. There will be the need of an Internet Connection. This shall support a web browser. There will also be the need of significant memory space Database will contain all the information which may be used by the developer. It is equally important aspect to any Android app. It allows classification of data into individual or related aspects and the app can be programmed accordingly. Figure 6: Geo-Fencing Implementation example on a map The weak points to be focused on are a proper database setup download, and installation of software. The Software configuration need to be accurate as there are chances of connection failure or application crashing, in case the support is not firm. There has to be an active monitoring and Continuous monitoring of hotspot data. We will also require to Support the changes like add/remove resources such as storage, software in environment as needed. The beginning of the data flow will start with module 1. This will be the plane User-Interface which will access the personal user information. This data will be stored in the local Firebase server, google server which will be the authentication source. Also, this will be the first screen page of the app. Next, the app will take the user to the second screen. This will be the part of Module 2, which will be a Google Maps API page. The User will be required to update his present location and the destination, on the Map. Immediately, blackspots around the user s current location will pop up in black colour. This information will be accessed from the local database. No communication will be received bu the user in this regard. After this, the next part will be popping of the Blockspots which lie on the User s route. They will be marked in red colour. This data will also be in the database. In the last module, the user will receive a notification as to the approaching blackspot, when he is 1 km away from the Blackspot. It will be an audio message telling the user, about the blackspot. The notification will be delivered via an HTTP protocol. Figure 7: Geo-Fencing 205

6 Also, the user will have the permission to report an on the spot accident, in case they encounter one, and once it will have more than a few reporting, it will become the part of the database. V. RESULTS We have concluded the following methods as suitable for the process of Black-spot Identification, and any one of the following can be used. All of the above methods have been tested and tried, and only then the most prominent ones WSI and Indexing methods areb suggested for the official government usage. As mentioned before, the policy implementation, and design is a governmental work, and so in private capacity, we cannot implement any of these on an official platform, but will cdertaily suggest the government to adopt them. Even the smallest of the errors can lead to big disasters, so we have realised that even the smallest of the information collected like Drivers education, road condition have been the causes of accidents. So, we suggest that the government and department carry out more tests, awareness drives and inspection to avoid such incidents. Furthermore, bad infrastructure is also a problem such as damaged roads, insufficient sign-boards, which will reduce the contraction speed of vehicles during fast driving. Hence, proper care has to be taken regarding the allocation of road contracts. VI. CONCLUSION We have concluded that out of the many methods of Blackspot Identification available, The Safety Auditing Method : which involves proper implementation of the data collected by the police, and is not done many times. The WSI Method : which takes into consideration, various factors like fatality rate, grevious injuries and minor injuries. The Geo-Referencing and Indexing Method : which takes into consideration the quality of road and vehicle travel ACKNOWLEDGMENT The authors would like to thank Prof. Leena A Deshpande, Prof. Laxmi A Bewoor and Prof. Snehal R Rathi for their enduring guidance and support during the course of information gathering and subsequent implementation. REFERENCES [1] Apparao. G, P. Mallikarjunareddy Dr. SSSV Gopala Rau, Identification Of Accident Black Spots For National Highway Using GIS, 3rd ed. pp.1-10, [2] Reshma, E. K., and Sheikh, U. S., Prioritization of accident black spots using GIS, International Journal of Emerging Technology and Advanced Engineering, ISSN , Vol.2 (9), pp , 2012 [3] LIANG, L. U., MASOME, D. M., HUA, L. T., Traffic Accident Application Using Geographic Information System, Journal of the Eastern Asia Society for Transportation Studies, Vol. 6, pp , [4] Pillai, B. B. and Joseph, K., Causes and Consequences of Road Accidents in Kerala, International Journal of Research in IT and Management, Vol. 1, pp.83-95, [5] Rao, B. S., Madhu., E., Jalihal, S., Reddy, T. S., Accident Study on National Highway 5 Between Anakapalli to Visakhapatnam, Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 5, pp [6] Bhuyan, P.K, 2002,Accidents Analysis on Two-Lane Roads, Unpublished Seminar Report, Department of Civil Engineering, Indian Institute of Technology Roorkee. [7] Garber, N.J., Hoel, L.A., 2002, Traffic and Highway Engineering, Third Edition, Thomson Publishing Company, New York, pp [8] Jain, S.S., Parida, M., Chauhan, M.P.S. and Landge, V.S., 2004, Identification of Hazardous Locations on National Highways, International Conference on Transportation Systems Planning and Operation (TRANSPO 2004), Chennai. [9] Gopala Raju SSSV., 2012, Identification of black spots and junction improvements in Visakhapatnam City, Indian Journal of Innovations and Development, Vol.1, No.6, pp [10] Jain, S.S., Parida, M., Chauhan, M.P.S. and Landge, V.S., 2004, Development of an Alternative Method for Identification of Hazardous Location, National Seminar on Strategies in Traffic [11] Z. Jiang and Q. Li, Research on the Applications of Geocoding Geography and Geo-Information Science, Vol. 19, No. 3, 2003, pp [12] Q. Hu, J. H. Xu and Z. H. Wang, Study on the Method of Address Automatically Matching in GIS Database, Geomatics and Spatial Information Technology, Vol. 31, No. 6, 2008, pp [13] X. M. Hu, T. Liu, T. H. Zhang, Y. Huang, H. W. Xie and T. Yu, Highway Black Spot Recognition and Improve- ment Journal of Traffic and Transportation Engineering, Vol. 4, No. 1, 2004, pp