Self-Enabling Vehicular Agent using Cloud and Massive Data

  • Shahid Naseem NCBA&E, Lahore, Pakistan
  • Muhammad Shabbir UET, Taxila, Pakistan
  • Fahad Ahamd NCBA&E, Lahore, Pakistan
Keywords: cloud, massive data, self-enabling, memories, vehicular agent.


Since last some decades, the autonomous technology in the vehicles was used to help the drivers to voyage effortlessly along the highways and to avoid road accidents. In this duration, a number of high-end vehicles was built-in electronic secureness mechanism, adaptive voyage mechanism, lane departure warnings and city safety system. Approximately, 95% of the road accidents were caused by the wrong behavior, careless, focus less and tiredness of the drivers. Even with the attractiveness of recent traffic control applications, a lack of dynamic information about roads and weather conditions was more than an infuriation. For this purpose, we developed a self-enabling vehicular agent in which cloud and Massive data is used. The cloud and massive data enabled the agent to see around corners or even miles down the road and to drive itself more carefully. The parameters enabled the agent to keep the driver informed on the road conditions ahead. The vehicular agent would be enable to process the appropriate data from this massive data, send it via cloud to forecasts of the traffic situation, the road conditions, the cars are ahead of it and the weather in the real time.

How to Cite
Shahid Naseem, Muhammad Shabbir, & Fahad Ahamd. (2017). Self-Enabling Vehicular Agent using Cloud and Massive Data. Lahore Garrison University Research Journal of Computer Science and Information Technology, 1(2), 10-25.