Infrastructure Supported Automated Driving in Transition Areas – a Prototypic Implementation

Schindler, Julian; Markowski, Robert; Wesemeyer, Daniel; Coll-Perales, Baldomero; Böker, Clarissa; Khan, Saifullah

doi:10.1109/cavs51000.2020.9334555

Cited by 5 publications

(3 citation statements)

References 2 publications

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“…Next, job-level dependencies within a single sub DAG, (i.e., other than dependencies between tail node jobs and join node jobs), are stored in JLD (Algorithm 3, line 6). Finally, the dependencies between the tail node job and the join node job are determined based on the calculated reference start and finish times (Algorithm 3, lines [14][15][16][17][18]. The job level dependencies in EG after applying Algorithm 3 to EG when α = 1.7 in Eq.…”

Section: : End Formentioning

confidence: 99%

“…To guarantee safety in emergencies, a minimum risk maneuver (MRM) mode is implemented in self-driving systems [13], [14]. In the self-driving industry, the risk avoidance state in the event of a deadline miss is called a minimum risk condition (MRC), and the steering wheel operation and brake control until the vehicle moves to MRC is called MRM.…”

Section: Introductionmentioning

confidence: 99%

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Deadline Miss Early Detection Method for Mixed Timer-Driven and Event-Driven DAG Tasks

Yano

Azumi

2023

IEEE Access

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Self-driving systems have a hard real-time nature, and the control commands of the vehicle must be output before the end-to-end deadline using sufficiently new data. It must also have the functionality to quickly shift to a safe state in the event of a deadline miss. However, the current self-driving system can only detect a deadline miss at the end of the process. To further improve safety, a method for detecting the possibility of a deadline miss in the middle of the process is required. Therefore, we represent such a real-time system as a mixed timer-driven and event-driven directed acyclic graph (DAG) and propose an early detection method for deadline misses by deriving a time constraint for each node. The experimental evaluation shows that the proposed method can detect deadline misses early for various scheduling algorithms. It also shows that the deadline miss ratio can be reduced by prioritizing the scheduling of jobs with a small margin to the time constraint determined using the proposed method for each job.INDEX TERMS DAG, deadline miss early detection, event-driven task, self-driving system, timer-driven task

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Section: : End Formentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Deadline Miss Early Detection Method for Mixed Timer-Driven and Event-Driven DAG Tasks

Yano

Azumi

2023

IEEE Access

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“…In situations where MRMs are performed, each HAV needs to communicate its intentions with passengers and surrounding road users comprehensively (Karakaya et al, 2020;Nyberg et al, 2021). Other connected AVs could receive such information via V2V communication protocols (Schindler et al, 2020b). However, non-connected road users and especially following manual drivers have to be informed, too.…”

Section: Minimal Risk Maneuvermentioning

confidence: 99%

Promoting trust in HAVs of following manual drivers through implicit and explicit communication during minimal risk maneuvers

Hess

Lau

Wilbrink

et al. 2023

Front. Comput. Sci.

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The successful integration of highly automated vehicles (HAV) in future mixed traffic environments will depend, among other things, on their seamless, safe, and accepted interaction with other road users. Therefore, appropriate combination of light signals, as external human-machine interface (eHMI), and driving behavior, as dynamic human-machine interface (dHMI), is required consistently in order to develop trust of following manual drivers in HAVs. Especially, in borderline traffic scenarios where HAVs are confronted with challenges, such as loss of connectivity, so-called minimal risk maneuvers (MRMs) are performed abruptly. Here, understanding communication via eHMI and dHMI is crucial for road safety, as drivers need to prepare for maneuvers themselves. Therefore, two consecutive, explorative online video studies were conducted. Firstly, the appropriate braking dynamics for an MRM were evaluated. Secondly, insights into the eHMI communication strategy of an HAV during an MRM were gained. The overall aim of this work is to present strategies for implicit and explicit communication channels of an HAV in order to promote learned trust during MRMs from the perspective of drivers who follow them. The results show that adding novel eHMI designs (e.g., warning sign, 360° LED light-band) to conventional light signals positively affects the user experience in a first contact interaction. The findings could have a positive impact on the development of trust in HAVs. In conclusion, specific eHMI communication strategies can be highly supportive for following manual drivers in MRM scenarios, which may lead to legislative considerations in the future.

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Demonstrating a V2X Enabled System for Transition of Control and Minimum Risk Manoeuvre When Leaving the Operational Design Domain

Schulte-Tigges

Matheis

Reke

et al. 2023

Lecture Notes in Computer Science

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Infrastructure Supported Automated Driving in Transition Areas – a Prototypic Implementation

Cited by 5 publications

References 2 publications

Deadline Miss Early Detection Method for Mixed Timer-Driven and Event-Driven DAG Tasks

Deadline Miss Early Detection Method for Mixed Timer-Driven and Event-Driven DAG Tasks

Promoting trust in HAVs of following manual drivers through implicit and explicit communication during minimal risk maneuvers

Demonstrating a V2X Enabled System for Transition of Control and Minimum Risk Manoeuvre When Leaving the Operational Design Domain

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