Browsing by Author "Bichiou, Youssef"

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    A Feasible Solution for Rebalancing Large-Scale Bike Sharing Systems
    Elhenawy, Mohammed; Rakha, Hesham A.; Bichiou, Youssef; Masoud, Mahmoud; Glaser, Sebastien; Pinnow, Jack; Stohy, Ahmed (MDPI, 2021-12-04)
    City bikes and bike-sharing systems (BSSs) are one solution to the last mile problem. BSSs guarantee equity by presenting affordable alternative transportation means for low-income households. These systems feature a multitude of bike stations scattered around a city. Numerous stations mean users can borrow a bike from one location and return it there or to a different location. However, this may create an unbalanced system, where some stations have excess bikes and others have limited bikes. In this paper, we propose a solution to balance BSS stations to satisfy the expected demand. Moreover, this paper represents a direct extension of the deferred acceptance algorithm-based heuristic previously proposed by the authors. We develop an algorithm that provides a delivery truck with a near-optimal route (i.e., finding the shortest Hamiltonian cycle) as an NP-hard problem. Results provide good solution quality and computational time performance, making the algorithm a viable candidate for real-time use by BSS operators. Our suggested approach is best suited for low-Q problems. Moreover, the mean running times for the largest instance are 143.6, 130.32, and 51.85 s for Q = 30, 20, and 10, respectively, which makes the proposed algorithm a real-time rebalancing algorithm.
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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%.
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    Modeling Analysis and Control of Nonlinear Aeroelastic Systems
    Bichiou, Youssef (Virginia Tech, 2015-01-15)
    Airplane wings, turbine blades and other structures subjected to air or water flows, can undergo motions depending on their flexibility. As such, the performance of these systems depends strongly on their geometry and material properties. Of particular importance is the contribution of different nonlinear aspects. These aspects can be of two types: aerodynamic and structural. Examples of aerodynamic aspects include but are not lomited to flow separation and wake effects. Examples of structural aspects include but not limited to large deformations (geometric nonlinearities), concentrated masses or elements (inertial nonlinearities) and freeplay. In some systems, and depending on the parameters, the nonlinearities can cause multiple solutions. Determining the effects of nonlinearities of an aeroelastic system on its response is crucial. In this dissertation, different aeroelastic configurations where nonlinear aspects may have significant effects on their performance are considered. These configurations include: the effects of the wake on the flutter speed of a wing placed under different angles of attack, the impacts of the wing rotation as well as the aerodynamic and structural nonlinearities on the flutter speed of a rotating blade, and the effects of the recently proposed nonlinear energy sink on the flutter and ensuing limit cycle oscillations of airfoils and wings. For the modeling and analysis of these systems, we use models with different levels of fidelity as required to achieve the stated goals. We also use nonlinear dynamic analysis tools such as the normal form to determine specific effects of nonlinearities on the type of instability.
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    Steady-State Car-Following Time Gaps: An Empirical Study Using Naturalistic Driving Data
    Loulizi, Amara; Bichiou, Youssef; Rakha, Hesham A. (Hindawi, 2019-05-13)
    The time gap is defined as the time difference between the rear of a vehicle and the front of its follower, which affects both safety and the saturation flow rate of a roadway segment. In this study, naturalistic driving data were examined to measure time gaps from seven different drivers in a car-following scenario within steady-state conditions. The measurements were taken from a 13-km section of a Dulles Airport access road in Washington, DC. In total, 168,053 time gap samples were obtained covering seven speed intervals. Analysis of the data revealed a large variation in time gaps within individual drivers’ driving data, with coefficients of variation as high as 63.8% observed for some drivers. Results also showed that the variability within drivers was more significant at speeds higher than 54 km/h. In addition, there was a large variability between drivers. At speeds above 108 km/h, minimum time gaps left by some drivers could be 1.6 times longer than those left by others. Several statistical distributions were used to fit the data of the seven drivers as well as the data for all drivers combined for each speed interval. The selected distributions passed the goodness-of-fit (Kolmogorov-Smirnov, Chi-square, and Anderson-Darling) criteria only when the number of samples was reduced. Data reduction was not performed randomly, but rather in a manner intended to maintain the same observed distribution when all the samples were used. It is therefore recommended that empirical measures of distributions be used in traffic microsimulation software rather than theoretically fit distributions obtained based on statistical tests. This will lead to better naturalistic traffic behavior simulations, resulting in more precise predicted measures of performance (travel time, fuel consumption, and gas emissions).
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    Use of Life Cycle Cost Analysis and Multiple Criteria Decision Aid Tools for Designing Road Vertical Profiles
    Loulizi, Amara; Bichiou, Youssef; Rakha, Hesham A. (MDPI, 2019-12-12)
    The current design practice for the vertical profile of roads in rolling and mountainous terrains is to follow the existing grades in order to minimize earthwork costs. This means that the only criterion considered during the design phase is the initial cost. It would be preferable to include other criteria that are directly related to sustainability, particularly fuel consumption and CO2 emissions. Therefore, this paper describes a proposed design procedure that starts by finding feasible alternatives with different grades. Then, a microsimulation traffic tool is used to simulate the movement of predicted vehicles (volume and type) over the different alternatives. The microsimulation tool provides reliable estimates of travel times, fuel consumption, and CO2 emissions for the different alternatives. With these data, it is possible to use life cycle cost analysis (LCCA) or multiple criteria decision aid (MCDA) tools to select the “optimal” alternative. The proposed procedure was used on a case study involving a 6-km highway section with different proposed grades ranging from 2% to 8%. Using LCCA and an MCDA tool, it was revealed that the current design alternative is not the optimal alternative in most considered scenarios (various fuel values for LCCA and different “Cost” weights for MCDA).