Traffic estimation

In recent years, Florida State recorded thousands of abnormal traffic flows on highways that were caused by traffic incidents. Highway traffic congestion costed the US economy 101 billion dollars in 2020. Therefore, it is imperative to develop effective real-time traffic flow prediction schemes to mitigate the impact of traffic congestion. In this dissertation, we utilized real-life highway segment-based traffic and incident data obtained from Florida Department of Transportation (FDOT) for real-time incident prediction.
We used eight years of FDOT real-life traffic and incident data for Florida I-95 highway to build prediction models for traffic accident severity. Accurate severity prediction is beneficial for responders since it allows the emergency center to dispatch the right number of vehicles without wasting additional resources.

At most of the US signal, pedestrian walk timings run in concurrence with relevant
vehicular traffic signal phases which means that major-street coordinated operations can
be interrupted by a pedestrian call. Such interruption may increase delays and stops for
major traffic flows. An alternative to this design is to increase the cycle length and embed
pedestrian timings within the ring-barrier structure of the prevailing coordination plan.
Both approaches have advantages and disadvantages. This study attempts a novel approach
to address this situation by a comprehensive experimental evaluation of traffic performance
under various pedestrian signal timing strategies. Findings show that either
abovementioned approach works well for very low traffic demands. When the traffic
demand increases findings cannot be generalized as they differ for major coordinated
movements versus overall network performance. While coordinated movements prefer no
interruption of the coordinated operations, the overall network performance is better in the
other case.

Traffic congestion is one of the most concerning issues in the transportation system. Recurrent congestion and non-recurrent congestion are explored in this research. This research will investigate one of the most concerning issues with the transportation system, congestion, using an overall delay analysis study. A developed fused database program was used to access and analyze the complete database data. Two online databases were used for obtaining traffic, incident and weather data. Eleven different scenarios such as peak-hours, rain scenario, incidents scenario, and work zone scenario were developed for the analysis. An overall delay study was performed on all
scenarios to find the impact recurring and non-recurring congestion on the highway. The results of this research were interesting for future adjustment and improvements on the two segments of highways selected.

Nowadays it is very hard to find available spots in public parking lots and even harder at facilities such as universities and sports venues. A system that provides drivers with parking availability and parking lot occupancy will allow users find a parking space much easier and faster. This thesis presents a system for automatic parking lot occupancy computation using motion tracking. The use of computer vision techniques and low cost video sensors makes it possible to have an accurate system that allows drivers to find a parking spot. Video bitrate and quality reduction and its impact on performance were studied. It was concluded that high quality video is not necessary for the proposed algorithm to obtain accurate results. The results show that relatively inexpensive and low bandwidth networks can be used to develop large scale parking occupancy applications.