Browsing by Author "Kanchwala, Husain"

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    ADAMS model validation for an all terrain vehicle using test track data
    (Sage, 2019-07-15) Kanchwala, Husain; Chatterjee, Anindya
    MD ADAMS R is widely used for vehicle suspension modeling. In this paper we present modeling, simulation, and test track evaluation of an all terrain recreational vehicle. Our intention is to study the degree to which simplified ADAMS modeling actually matches human-driven vehicle response. For suspension model validation, a vehicle is generally tested on a four-post test rig and base-excitation is applied at four ground-wheel contacts. However, actual driving experience does not match idealized testing conditions. In this work the vehicle is manually driven on a variety of tracks at different speeds, and the vertical accelerations at four axle locations and four body points are measured. The same are then compared in detail against predictions from ADAMS simulation with vertical base excitation. The contribution of this paper is in identifying those aspects of the simulation results that match experiments well, and identifying possible sources for the observed mismatch, especially under more severe test conditions.
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    Autonomous navigation for mobility scooters: a complete framework based on open-source software
    (IEEE, 2019-11-28) Cecotti, Marco; Kanchwala, Husain; Aouf, Nabil
    In recent years, there has been a growing demand for small vehicles targeted at users with mobility restrictions and designed to operate on pedestrian areas. The users of these vehicles are generally required to be in control for the entire duration of their journey, but a lot more people could benefit from them if some of the driving tasks could be automated. In this scenario, we set out to develop an autonomous mobility scooter, with the aim to understand the commercial feasibility of a similar product. This paper reports on the progress of this project, proposing a framework for autonomous navigation on pedestrian areas, and focusing in particular on the construction of suitable costmaps. The proposed framework is based on open-source software, including a library created by the authors for the generation of costmaps.
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    A comparison of trajectory planning and control frameworks for cooperative autonomous driving
    (American Society of Mechanical Engineers, 2021-01-07) Bezerra Viana, Icaro; Kanchwala, Husain; Ahiska, Kenan; Aouf, Nabil
    This work considers the cooperative trajectory-planning problem along a double lane change scenario for autonomous driving. In this paper we develop two frameworks to solve this problem based on distributed model predictive control (MPC). The first approach solves a single non-linear MPC problem. The general idea is to introduce a collision cost function in the optimization problem at the planning task to achieve a smooth and bounded collision function and thus to prevent the need to implement tight hard constraints. The second method uses a hierarchical scheme with two main units: a trajectory-planning layer based on mixed-integer quadratic program (MIQP) computes an on-line collision-free trajectory using simplified motion dynamics, and a tracking controller unit to follow the trajectory from the higher level using the non-linear vehicle model. Connected and automated vehicles (CAVs) sharing their planned trajectories lay the foundation of the cooperative behaviour. In the tests and evaluation of the proposed methodologies, MATLAB-CARSIM co-simulation is utilized. CARSIM provides the high fidelity model for the multi-body vehicle dynamics. MATLAB-CARSIM conjoint simulation experiments compare both approaches for a cooperative double lane change maneuver of two vehicles moving along a one-way three-lane road with obstacles.