Development and Verification of Infrastructure-Assisted Automated Driving Functions

Abstract

Automated vehicles we have on public roads today are capable of up to SAE Level-3 conditional autonomy according to the SAE J3016 Standard taxonomy, where the driver is the main responsible for the driving safety. All the decision-making processes of the system depend on computations performed on the ego vehicle and utilizing only on-board sensor information, mimicking the perception of a human driver. It can be conjectured that for higher levels of autonomy, on-board sensor information will not be sufficient alone. Infrastructure assistance will, therefore, be necessary to ensure the partial or full responsibility of the driving safety. With higher penetration rates of automated vehicles however, new problems will arise. It is expected that automated driving and particularly automated vehicle platoons will lead to more road damage in the form of rutting. Inspired by this, the EU project ESRIUM investigates infrastructure assisted routing recommendations utilizing C-ITS communications. In this respect, specially designed ADAS functions are being developed with capabilities to adapt their behavior according to specific routing recommendations. Automated vehicles equipped with such ADAS functions will be able to reduce road damage. The current paper presents the specific use cases, as well as the developed C-ITS assisted ADAS functions together with their verification results utilizing a simulation framework.

Development, Verification and KPI Analysis of Infrastructure-Assisted Trajectory Planners

“…The solution used in this paper for the trajectory planning problem was introduced in a recent paper by the authors [5]. The developed trajectory planner (TP) is designed for driving on highway with well defined lane-markings and it steers the vehicle to the middle of the rightmost lane unless external lane-change or in-lane offset recommendation is received.…”

“…The algorithm utilized in this case was a rule based trajectory planner adapted to utilize C-ITS messages such as the in-lane offset recommendation and the lane change recommendation (see Fig. 1 as well as the detailed description of the use cases in [5]). There, the lane change curves were constructed utilizing two quadratic Bezier curves connected by a straight line.…”

“…The Bezier curve from P 1 to P 2 (red) is connected via the straight line from P 2 to Q 1 (magenta) to the second Bezier curve from Q 1 to Q 2 (blue). This specific approach is also described in detail in [5]. It is motivated due to the lack of the ability to provide trustworthy lane information from the lane detection sensor on the actual test vehicle (which is a Mobileye intelligent camera).…”

“…As a follow-up paper to [5], the current paper presents the comparison of three alternative transition curves for a rule-based trajectory planner. A set of performance indicators serves as a basis for their selection for the described infrastructure-assisted routing recommendations for the corresponding scenarios.…”

Feasible, Robust and Reliable Automation and Control for Autonomous Systems

“…In 'Development and Verification of Infrastructure-Assisted Automated Driving Functions' [9], Rudigier et al extensively discussed the autonomous driving and ADAS applications of control systems. Their paper presents specific use cases in the said context, and the verification results for a proposed system utilizing a simulation framework are reported.…”