Browsing by Author "Hassan, Abdallah A."

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    A Fully-Distributed Heuristic Algorithm for Control of Autonomous Vehicle Movements at Isolated Intersections
    Hassan, Abdallah A.; Rakha, Hesham A. (Elsevier, 2014)
    Optimizing autonomous vehicle movements through roadway intersections is a challenging problem. It has been demonstrated in the literature that traditional traffic control, such as traffic signal and stop sign control are not optimal especially for heavy traffic demand levels. Alternatively, centralized autonomous vehicle control strategies are costly and not scalable given that the ability of a central controller to track and schedule the movement of hundreds of vehicles in real-time is questionable. Consequently, in this paper a fully distributed algorithm is proposed where vehicles in the vicinity of an intersection continuously cooperate with each other to develop a schedule that allows them to safely proceed through the intersection while incurring minimum delay. Unlike other distributed approaches described in the literature, the wireless communication constraints are considered in the design of the control algorithm. Specifically, the proposed algorithm requires vehicles heading to an intersection to communicate only with neighboring vehicles, while the lead vehicles on each approach lane share information to develop a complete intersection utilization schedule. The scheduling rotates between vehicles to identify higher traffic volumes and favor vehicles coming from heavier lanes to minimize the overall intersection delay. The simulated experiments show significant reductions in the average delay using the proposed approach compared to other methods reported in the literature and reduction in the maximum delay experienced by a vehicle especially in cases of heavy traffic demand levels.
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    Intersection Management Using In-Vehicle Speed Advisory/Adaptation
    Rakha, Hesham A.; Bichiou, Youssef; Hassan, Abdallah A.; Zohdy, Ismail H. (Connected Vehicle/Infrastructure University Transportation Center, 2016-08-30)
    In recent years, connected vehicles (CVs) and automated vehicles (AVs) have emerged as a realistic and viable transportation option. Research centers and companies have dedicated substantial efforts to the technology, motivated largely by the potential safety benefits that can be realized through the elimination of human error, the enhancement of mobility via reduction of congestion and optimization of trips, and the associated positive environmental impacts. Both sensors and control mechanisms are needed for this technology to succeed. The goal of this study is to make use of vehicle connectivity via vehicle-to-vehicle (V2V) (i.e., exchanging information between vehicles) and vehicle-to-infrastructure (V2I) (i.e., exchanging information with the infrastructure, including intersection controllers) features, leveraging both connected and automated capabilities, to develop control algorithms/systems that deliver solutions/recommendations for connected automated vehicles (CAVs) [1] as they proceed through intersections. The algorithms developed in this report deliver optimal and/or near-optimal solutions, which required extensive simulations and field experiments for validation. In the work described in this report, the research group combined mathematical modeling, optimal control theory, and optimization into a simulation framework that allows vehicles to cross an intersection safely, while incurring the least amount of delay. These models feature kinematic, dynamic and static constraints. Different versions of the model were developed, ranging from exact solutions that cannot be implemented in real-time to heuristic solutions that are computationally efficient. The results of the final proposed model were compared to other control techniques already implemented in the field, and demonstrated that a reduction of at least 50% in delay was achievable. An interesting byproduct of this model was the reduction in fuel consumption, and thus emissions, by more than 10%.