Online Optimization of Gear Shift and Velocity for Eco-Driving using Adaptive Dynamic Programming

In this paper a learning-based optimization method for online gear shift and velocity control is presented to reduce the fuel consumption and improve the driving comfort in a car-following process. The continuous traction force and the discrete gear shift are optimized jointly to improve both the powertrain operation and the longitudinal...

Connected variable speed limits control and car-following control with vehicle-infrastructure communication to resolve stop-and-go waves

The vision of intelligent vehicles traveling in road networks has prompted numerous concepts to control future traffic flow, one of which is the in-vehicle actuation of traffic control commands. The key of this concept is using intelligent vehicles as actuators for traffic control systems. Under this concept, we design and test a control...

The effects of driving with different levels of unreliable automation on self-reported workload and secondary task performance

Until automated cars function perfectly, drivers will have to take over control when automation fails or reaches its functional limits. Two simulator experiments (N = 24 and 27) were conducted, each testing four automation levels ranging from manual control (MC) to highly automated driving. In both experiments, participants about once every 3...

Adaptive Cruise Control for a SMART Car: A Comparison Benchmark for MPC-PWA Control Methods

The design of an adaptive cruise controller for a SMART car, a type of small car, is proposed as a benchmark setup for several model predictive control methods for nonlinear and piecewise affine systems. Each of these methods has been already applied to specific case studies, different from method to method. This paper has therefore the purpose...

Modeling driver behavior with different degrees of automation: a hierarchical decision framework of interacting mental models