Abstract
Research and/or Engineering Questions/Objective
To define an optimized dynamic speed trajectory for an automated driving demonstrator vehicle, to achieve optimal energy consumption yet not increasing the overall travel time.
Methodology
With the support of V2X information and on board sensors, dynamic speed limitation in 3D (distance, time and velocity) can be generated in real time. The optimization is conducted with the algorithm “Dynamic Programming”, which is newly defined for the dynamic 3D speed limit application. In the algorithm, the state of the vehicle will be continuously compared with the dynamically changing boundary conditions from dynamic speed limit. The functionalities are realized in simulations at the first step to show required information and impact to the observed consumption versus travel time. In the next step feasibility and consumption benefits are validated by demonstrator vehicle measurements.
Results
In this paper the aggregation of optimized speed profile will be investigated for certain representative test cases. Through simulation parameter studies and vehicle tests potential of energy reduction while not sacrificing overall travel time. This knowledge is used in a next step to introduce a new function structure in the FEV demonstrator vehicle controller. In this structure, inputs and control modules are implemented in different layers. Dynamic speed limit can be utilized as one layer of input, together with other layers of inputs such as elevation and temperature information from map data, etc., to generate an optimized speed trajectory in the optimization layer. The optimized speed profile will be constrained by the safety layer, which monitors instantaneous incidents in the near field detected by board sensors.
Limitations of this study
Due to safety concern, the vehicle will not be able to be tested in real traffic circumstances. The real world performance will be tested on test track with a battery electric vehicle. Furthermore rapid control hardware is used, what makes further code optimization for series hardware necessary. What does the paper offer that is new in the field including in comparison to other work by the authors? Currently, 2D drive tube which only considers speed limit over distance is widely utilized. However, the dimension of time, which is vitally important for timely dependent events cannot to be considered. Additionally, implementing the result into a demonstrator vehicle to check the real world performance is also a step forward.
Conclusions
Simulation and test track tests results show the potential of the energy consumption reduction by speed optimization. Results can be extended to hybrid and conventional vehicles as well. By combining the system in the next step with cooperative driving functionalities, tradeoff between energy consumption and traffic flow can be resolved.
KEYWORDS : 3D dynamic speed limit, speed trajectory optimization, V2X, Dynamic Programming, real world consumption