Traffic flow

Adaptive cruise control (ACC) system is the first widely offered automated functionality that regulates the longitudinal movement of the vehicle using onboard radar sensors, and they can maintain a safe following distance with the preceding vehicle. In most of the field experiments with ACC-equipped vehicles conducted with internal combustion engine vehicles, there is still a gap in research on how the automation systems such as ACC combined with electric powertrains will influence the traffic flow be examined.
This study refined and recalibrated an ACC car-following model for EVs and integrated it into AIMSUN to realistically simulate ACC-equipped vehicles and their impact on the fundamental diagram of traffic flow. Simulations were conducted for various ACC market penetrations, and fundamental diagrams were constructed for those market penetrations using detector measurements at various locations along the simulated segment. Overall, the capacity and the jam density increase as the EV with ACC market penetration rises. EVs with ACC can achieve higher capacities compared to ICEs with ACC.

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.

Automated vehicles (AVs) are becoming more common each day as car manufacturers have started to include advanced driving assistant systems (ADAS) in trendline models. The most basic level of vehicle automation includes Adaptive Cruise Control (ACC) can disrupt and change traffic flow. The current study proposes the development of controlled experiments to obtain traffic flow properties for vehicles equipped with ACC in different scenarios. As part of this dissertation, the effects of ACC on capacity are quantified at steady state conditions, meaning cruising speeds or free flow, and at bottlenecks, where speed fluctuations occur. The effects of ACC on traffic flow properties are also assessed by the construction and study of the Fundamental Diagram. Lastly, the vehicles are submitted to less predictable deceleration scenarios that involve a leading vehicle driven in ACC mode and a leading vehicle driven manually. The reaction of ACC for these cases is documented.

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.

Implementation of the Optimized Policies for Adaptive Control (OPAC) strategy in conjunction with a vehicle velocity controller offers the potential for significantly improving the control strategies used at isolated intersections with respect to measured vehicle delays. The exhaustive sequential search procedure by OPAC provides the optimal switching policies for the intersection while the vehicle velocity controller varies vehicle velocities to reduce vehicle stopping delays. The OPAC algorithm implemented with the vehicle velocity controller was found to have substantially lower delays than OPAC alone.