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The UNECE regulation R157 [1] describes the requirements for a successful implementation of an approvable ALKS (Automated Lane-Keeping System) in great detail. This paper reviews some of the content of this document and describes the first steps that would be needed on how to implement such an ALKS as another driver model into the open source microscopic traffic flow simulator SUMO.

Hydrogen storage might be key to the success of the hydrogen economy, and hence the energy transition in Germany. One option for cost-effective storage of large quantities of hydrogen is the geological subsurface. However, previous experience with underground hydrogen storage is restricted to salt caverns, which are limited in size and space. In contrast, pore storage facilities in aquifers -and/or depleted hydrocarbon reservoirs- could play a vital role in meeting base load needs due to their wide availability and large storage capacity, but experiences are limited to past operations with hydrogen-bearing town gas. To overcome this barrier, here we investigate hydrogen storage in porous storage systems in a two-step process: 1) First, we investigate positive and cautionary indicators for safe operations of hydrogen storage in pore storage systems. 2) Second, we estimate hydrogen storage capacities of pore storage systems in (current and decommissioned) underground natural gas storage systems and saline aquifers. Our systematic review highlights that optimal storage conditions in terms of energy content and hydrogen quality are found in sandstone reservoirs in absence of carbonate and iron bearing accessory minerals at a depth of approx. 1,100 m and a temperature of at least 40°C. Porosity and permeability of the reservoir formation should be at least 20% and 5 × 10−13 m2 (∼500 mD), respectively. In addition, the pH of the brine should fall below 6 and the salinity should exceed 100 mg/L. Based on these estimates, the total hydrogen storage capacity in underground natural gas storages is estimated to be up to 8 billion cubic meters or (0.72 Mt at STP) corresponding to 29 TWh of energy equivalent of hydrogen. Saline aquifers may offer additional storage capacities of 81.6–691.8 Mt of hydrogen, which amounts to 3.2 to 27.3 PWh of energy equivalent of hydrogen, the majority of which is located in the North German basin. Pore storage systems could therefore become a crucial element of the future German hydrogen infrastructure, especially in regions with large industrial hydrogen (storage) demand and likely hydrogen imports via pipelines and ships.

Level 3 automated driving systems could introduce challenges to traffic systems as they require a specific lead time in their procedures to ensure the safe return of vehicle control to the driver. These processes, called ’transitions of control’, may particularly pose complications in accelerating traffic flows when regulations mandate control transitions due to an operational speed limitation of 60 km/h as established in recent certification processes based on UNECE regulations from 2021. To investigate these concerns, we conducted a comprehensive simulation study to examine potential safety implications arising from control transitions within mixed-autonomy traffic. The simulation results indicate adverse safety impacts due to increased safety-relevant interactions between vehicles caused by transitions of control in dynamic traffic flow conditions. Our findings also reveal that those effects could become stronger once string unstable ACC controllers are deployed as well.

An important aspect of automated driving is to handle situations where it fails or is not allowed in specific traffic situations. This case study explores means, by which control transitions in a mixed autonomy system can be organized in order to minimize their adverse impact on traffic flow. We assess a number of different approaches for a coordinated management of transitions, covering classic traffic management paradigms and AI-driven controls. We demonstrate that they yield excellent results when compared to a do-nothing scenario. This text further details a model for control transitions that is the basis for the simulation study presented. The results encourage the deployment of reinforcement learning on the control problem for a scenario with mandatory take-over requests.

Level 3 automated driving systems could introduce challenges to traffic systems as they require a specific lead time in their procedures to ensure the safe return of vehicle control to the driver. These processes, called 'transitions of control', may particularly pose complications in accelerating traffic flows when regulations mandate control transitions due to an operational speed limitation of 60 km/h as established in recent certification processes based on UNECE regulations from 2021. To investigate these concerns, we conducted a comprehensive simulation study to examine potential safety implications arising from control transitions within mixed-autonomy traffic. The simulation results indicate adverse safety impacts due to increased safety-relevant interactions between vehicles caused by transitions of control in dynamic traffic flow conditions. Our findings also reveal that those effects could become stronger once string unstable ACC controllers are deployed as well. [ABSTRACT FROM AUTHOR]