Automated Driving Algorithm Engineer
CurrentVehicle State Estimation and Behavior Motion Planning
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@aptiv.com
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Dan Shen is listed as Automated Driving Algorithm Engineer at Aptiv, based in Detroit Metropolitan Area, United States. AeroLeads shows a work email signal at aptiv.com and a matched LinkedIn profile for Dan Shen.
Dan Shen previously worked as Graduate Research Assistant at Purdue University and Graduate Research Assistant at Purdue University. Dan Shen holds Doctor Of Philosophy (Ph.D.), Electrical And Computer Engineering from Purdue University.
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• Collision-free motion and path planning using predictive occupancy map and RRT*• Optimal gain-scheduling control system design based on polytopic linear parameter varying (LPV) vehicle model• Developed the robust MPC state feedback control law at each step by solving a set of matrix inequalities which are derived from Lyapunov asymptotic stability and the minimization of the worst-case infinite horizon quadratic objective function• State-Feedback switching LPV control using hybrid & switched system theoretical approach• Heterogeneous Vehicle Platoons Control Under Uncertainty• Camera & Lidar calibration and fusion, GPS & IMU sensor fusion• Hardware and software evaluation and environmental testing of ADAS modules with CAN working knowledge• Test scenarios design, data acquisition/processing & analysis• Connected Automated Vehicle (CAV) simulation software/driving simulator development• Fast learner with rigorous attitude; desire to improve and innovate
Listed skills include Matlab, Simulink, Power Electronics, Control Systems Design, and 17 others.
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Dublin, Ie
Vehicle State Estimation and Behavior Motion Planning
West Lafayette, In, Us
- Working at Transportation and Autonomous Systems Institute (TASI) for Intelligent Transportation Systems and Self-Driving Vehicles- Participate in several major research projects funded by the US DOT, INDOT, and Toyota on the development of improving safety in future automated vehicles and ADAS test methods- Research on Collision-Avoidance-Coordinated Path Following Control of Automated Vehicle Considering Model Uncertainties, External Disturbances, and Parametric VaryingProjects:1. Back of Queue Warning and Critical Information Delivery to Motorists- Investigate feasible solutions to apply end-of-queue alarms considering both in-car and road-side options and tune the alarm parameters through driver simulator-based studies- Evaluate the effectiveness of the developed prototype end-of-queue alerting system using a driving simulator-based study- Test scenarios design and data collection from both driving simulator, Flex depth camera, and Driver State Sensing (DSS) System2. Naturalistic Data Collection and Analytics for Vehicle and e-Scooter Conflicts- Investigate the moving patterns of e-scooters in different road environments and locations- Data acquisition in both vehicle-based and e-Scooter-based data collection systems and conduct system calibrations- LiDAR-Camera sensor fusion, GPS-IMU sensor fusion- Scenario reconstruction algorithms3. Development of Testing Methods for Vehicle Road Departure Warning/Assist Systems- Survey of the sensing technologies used in road departure warning/assist and their impact on the road-departure test track and equipment requirements- Identify the representative crash scenarios of road departure for the testing of vehicle Road Departure Mitigation systems (RDMSs) and develop an effective scoring method for the star-rating purpose - Develop the test equipment design, hardware/software preparation, test equipment setup, data output, and data post-processing methods for the evaluation of RDMSs
West Lafayette, In, Us
Thesis:Control technology for DC microgrids. The maximum power point tracking (MPPT) and supervisory control strategies to maximize the simultaneous energy harvested from renewable sources (Wind and Solar) with DC load and battery.Projects: - Model-based controller design of a pole-cart system on MATLAB using model predictive control (MPC) and Linear–quadratic regulator (LQR) control (Control System Toolbox)- A cascade control strategy for a DC motor drive system using Matlab and Simulink- Analysis of H Bridge Topologies for Use in Single-Phase Photovoltaic Applications
Designed and created proton exchange membrane fuel cells and designed the anode feed system for alkaline direct-ethanol fuel cells.
Tested the high-power battery pack in the simulation of actual conditions with the test platform in EV and analyzed the data.
Engaged in recording the real-time data of new energy vehicles. Analyzed and compared the relevant data for the purpose of vehicles' operations.
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Dan Shen works for Aptiv.
Dan Shen is listed as Automated Driving Algorithm Engineer at Aptiv.
AeroLeads has found 1 work email signal at @aptiv.com for Dan Shen at Aptiv.
Dan Shen is based in Detroit Metropolitan Area, United States while working with Aptiv.
Dan Shen has worked for Aptiv, Purdue University, Richard G. Lugar Center For Renewable Energy, New Energy Test Center, and Nantong City Bus Corporation.
You can use AeroLeads to view verified contact signals for Dan Shen at Aptiv, including work email, phone, and LinkedIn data when available.
Dan Shen holds Doctor Of Philosophy (Ph.D.), Electrical And Computer Engineering from Purdue University.
Dan Shen is listed with skills including Matlab, Simulink, Power Electronics, Control Systems Design, C, Renewable Energy Systems, Modeling And Stability Analysis Of Power System, and Solidworks.
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