On the Control of Vehicle Dynamics for Partial Automation for Consumer Vehicles

The automotive industry has seen an extensive push to provide Connected and Automated Vehicles (CAV) technologies to consumer vehicles in order to improve energy efficiency, reduce traffic congestion, improve driver safety, and increase driver comfort. Rollout of CAV technologies to consumer vehicles has been approached via two methods: driver assistance/partial autonomy (Society of Automotive Engineers (SAE) Levels 1, 2 and 3) and high/full autonomy (SAE Levels 4 and 5) [1]. Full autonomy has proven to be difficult to completely realize and is still years, maybe decades, away from widespread acceptance. Driver assistance/partial autonomy, on the other hand, has been included in consumer vehicles for decades, with the introduction of Anti-Lock Braking System (ABS) in the 1970s. The EcoCAR Electric Vehicle Challenge (EVC) tasks teams to develop longitudinal and lateral control systems. These control systems enable SAE Level 2 CAV features, including Eco-Cooperative Adaptive Cruise Control (Eco-CACC), Eco-Approach and Departure (EAD), Lane Centering Control (LCC), Automatic Intersection Navigation (AIN), and Automatic Parking System (APS). Together, these features have the following potential benefits: • Improve energy efficiency during highway driving and intersection traversal (Eco CACC and EAD). • Reduce traffic congestion during highway driving and intersection traversal (Eco CACC and EAD). • Improve driver safety during highway driving and intersection traversal (Eco-CACC and LCC). Year 2 of the competition (2023-2024) focuses on functional Eco-CACC, EAD, and LCC in simulation. This thesis compiles the design, implementation, and demonstrational simulation of the supporting planning and control subsystems for these features, including the longitudinal controller, longitudinal heuristic planner, lateral controller, and lane centering planner. The research in this thesis provides future EcoCAR team members necessary knowledge of vehicle dynamics and controller design to continue the team’s CAV feature development in Years 3 and 4. This research is funded by the EcoCAR EVC, which is sponsored by the U.S. Department of Energy, General Motors, and MathWorks.

Level thesis:degree_level

Masters

Department dc:contributor.department

Electrical and Computer Engineering

Grantor dc:publisher

Georgia Institute of Technology

Year dc:date.issued

2024

Author dc:creator

• Leon, Laurence

Advisor dc:contributor.advisor

• Taylor, David G.

Committee members dc:contributor.committeemember

• Verriest, Erik I.
• Vela, Patricio

• CAV
• control
• Automotive
• Automation
• Adaptive cruise control
• Lane centering control.

Language dc:language.iso

en_US

Handle dc:identifier.uri

https://hdl.handle.net/1853/75309

OAI identifier oai:identifier

oai:repository.gatech.edu:1853/75309