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Drive Assist. A Smart Driving Assistance System to Elevate the Driving Experience of Drivers in Sri Lanka. Group : 18-018 Supervisor : Mr. Nuwan Kodagoda. Speed Analysis. M.R. Aaquiff Ahnaff IT15048738. IT15048738. Problem and Solution. Problem:
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Drive Assist A Smart Driving Assistance System to Elevate the Driving Experience of Drivers in Sri Lanka Group : 18-018 Supervisor : Mr. Nuwan Kodagoda
Speed Analysis M.R. AaquiffAhnaff IT15048738
IT15048738 Problem and Solution Problem: • Not adhering to appropriate speeds lead to traffic accidents. • No indication of appropriate speeds while driving. Solution: • Present average speeds around certain roads to the driver. • Classify and score the user on how well they adhere to it.
IT15048738 Knowledge Gap and Comparison • Driving Coach[1] - Evaluate efficient driving patterns(Android). • Driver behavior profiling[2]– Compares sensors in smartphones and learning algorithm. • DriveScribe[3] – Provides feedback to adhere to speed limit. • Based on speed limits rather than appropriate speeds. • No social comparison between users to reward good behavior. • No commercial product available. [1] R. Araújo, Â. Igreja, R. de Castro and R. Araújo, "Driving Coach: a Smartphone Application to Evaluate Driving Efficient Patterns", Intelligent Vehicles Symposium, 2018. [2] J. Ferreira, E. Carvalho, B. Ferreira, C. de Souza, Y. Suhara, A. Pentland and G. Pessin, "Driver behavior profiling: An investigation with different smartphone sensors and machine learning", PLOS ONE, vol. 12, no. 4, p. e0174959, 2017. [3] R. Scott, "Review: Drivescribe, The App That Will Improve Your Driving (Video) – TechGuySmartBuyTechGuySmartBuy", TechGuySmartBuy, 2018. [Online]. Available: http://techguysmartbuy.com/2014/04/review-drivescribe-the-app-thatwill-improve-your-driving-video.html. [Accessed: 12- Feb- 2018].
IT15048738 Research Area and Technologies
IT15015754 Commercialization User Benefits • Maintain safe speeds and avoid nervousness on new roads • Reduce time of journey • Encourage drivers to maintain safe speeds, thus make the roads safer.
IT15048738 Work Breakdown Structure (WBS)
Pedestrian Crossing Detection M. M. M. Munsif IT15015754
IT15015754 Problem and Solution Problem: • One of the most ignored road regulation in Sri Lanka • Caused substantial amounts of tragedies Solution: • Forewarn the driver of an oncoming crossing to take required safety measures
IT15015754 Knowledge Gap and Comparison Existing Evidence • Bipolarity Feature [1] – BW • ZebraRecognizer [2] – White Cane Cam • Self-Similarity [3] – Autonomous Cars Knowledge Gap (mostly): • Dedicated Hardware • Pedestrian’s Point-of-View • No Commercial Products • No Geospatial Data [1] M. S. Uddin and T. Shioyama, “Detection of Pedestrian Crossing Using Bipolarity Feature—An Image-Based Technique,” IEEE Trans. Intell. Transp. Syst., vol. 6, no. 4, pp. 439–445, Dec. 2005. [2] D. Ahmetovic, C. Bernareggi, A. Gerino, and S. Mascetti, “ZebraRecognizer: Efficient and Precise Localization of Pedestrian Crossings,” in 2014 22nd International Conference on Pattern Recognition, 2014, pp. 2566–2571. [3] C. Wang, C. Zhao, and H. Wang, “Self-Similarity based Zebra-crossing Detection for Intelligent Vehicle,” Open Autom. Control Syst. J., vol. 7, pp. 974–986, 2015.
IT15015754 Research Area and Key Pillars • Comes under different domains • Image Processing • Cloud Computing • Software Engineering (Mobile Development)
IT15015754 Technologies
IT15015754 Commercialization User Benefits • Pedestrian decides to step in suddenly • Driver is already alerted • Driver can act smart and safely maneuver
IT15015754 Work Breakdown Structure (WBS)
IT15015754 Self-Evaluation Plan
Road Signboard Detection M. Saranki IT15101266
IT15101266 Problem and Solution Problem: • Identifying and following the road signboards • Visibility constraints Solution: • Alert the drivers of oncoming road signboards on appropriate time
IT15101266 Knowledge Gap and Comparison Knowledge Gap (mostly): • Dedicated for sole purpose • Halted at statistics • Less Commercial Products • Constraint with time Existing Evidence • Traffic Sign Recognition [1] • TSR based on SVM [2] • aCoDriver [3] [1] R. Laguna, R. Barrientos, L. Felipe Blázquez, and L. J. Miguel, “Traffic sign recognition application based on image processing techniques.,pp.104-109, Aug.2014.” [2] S. Maldonado-Bascón, S. Lafuente-Arroyo, P. Gil-Jiménez, H. Gómez-Moreno, and F. López-Ferreras, “Road-Sign Detection and Recognition Based on Support Vector Machines,” IEEE Trans. Intell. Transp. Syst., vol. 8, no. 2, 2007. [3]aCo Driver 5. EvoTegra GmbH, 2013.
IT15101266 Research Area and Key Pillars • Comes under different domains • Image Processing • Cloud Computing • Software Engineering (Mobile Development)
IT15101266 Technologies
IT15101266 Commercialization User Benefits • Applicable for any scenario • No need of special devices to receive alerts
IT15101266 Work Breakdown Structure (WBS)
IT15101266 Self-Evaluation Plan
Lane Detection B. Kiruthiga IT15135308
IT15135308 Problem and Solution Problem: • Discriminating a road lane for its external factors Solution: • Alert the driver on lane departure
IT15135308 Knowledge Gap and Comparison Knowledge Gap (mostly): • No fair accuracy • Lack of communication • Less commercial products Existing Evidence • iOnRoad [1] • aCoDriver 5 [2] • Adjacent Lane Detection [3] [1] iOnRoad Augmented Driving Lite. iOnRoad, 2011. [2] aCo Driver 5. EvoTegra GmbH, 2013. [3] C. F. Wu, C. J. Lin, H. Y. Lin and H. Chung, “Adjacent Lane Detection and Lateral Vehicle Distance Measurement Using Vision-Based Neuro-Fuzzy Approaches”, Journal of Applied Research and Technology, vol. 11, Apr., pp. 251-258, 2013.
IT15135308 Research Area and Key Pillars • Core domain • Image Processing • Software Engineering (Mobile Development) • Android Native Development
IT15135308 Technologies
IT15135308 Commercialization User Benefits • Easy to identify the path • Helps to avoid collisions
IT15135308 Work Breakdown Structure (WBS)
IT15135308 Self-Evaluation Plan
Business Plan • Drive Assist • Regular Commuters • Revenue Model • Break-even Point