Penang data safety prediction using database development and alternative road identification using Dijkstra approach.

Congestion or bottlenecks are the issues faced by drivers every day. The reason the number of accidents is keep increasing every year is the research on these issues does not have enough information which can show the historical pattern. The study aims to use the available data (POL 37) to design baseline data and using the information from the data to visualize and incorporate it into the developed database. Near Miss is an unexpected event that contributing to the root cause of the accident. The places that have a high risk of Near Miss to happen can be predicted from the historical data (2015 to 2017) through designing a database. To prevent the congestion, an alternative road is needed to determine. Dijkstra's approach is used and incorporated in Geographic Information System (GIS) and Google Maps to identify black spot (hotspot accidents occur) and alternative road. The database is designed to visualize the data which is shown in Google Maps. The database can reduce the number of accidents and help higher authorities to save time and cost. GIS identified the black spots located at Tun Dr. Lim Chong Eu Expressway in the year 2015 and North-South Expressway in the year 2016 and 2017. The alternative roads are suggested and the distance is calculated each year by using Google Maps. The real-time database can identify black spot easily from the historical data. From the black spots, the Dijkstra approach can be implemented to identify the roads. Then, Google Maps is used as a visualization method to find alternative roads to prevent congestion or bottleneck break out. [ABSTRACT FROM AUTHOR]