
The population of the Kingdom of Saudi Arabia is growing and is expected to reach 50 million by the year 2030. As a result, congestion and heavy traffic will get worse over time. Moreover, worldwide traffic congestion becomes more problematic and complicated to solve. These add to the existing factors that necessitate an overall solution that considers all pre-existing challenges. This research proposes a system model approach to retrieve data from various sources and model a wide range of constant solutions. The proposed system consists mainly of two sections: the first part is the reporting section, and the second part is the execution section. The implemented modeling consisted of multilayers which are 1- data input layer 2- data modeling layer 3- data output layer 4- data reporting layer.
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO] Computer Science [cs], [INFO.INFO-ES] Computer Science [cs]/Embedded Systems
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO] Computer Science [cs], [INFO.INFO-ES] Computer Science [cs]/Embedded Systems
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
