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Abstract Porous MXene-polymer composites have gained attention due to their low density, large surface area, and high electrical conductivity, which can be used in applications such as electromagnetic interference shielding, sensing, energy storage, and catalysis. High internal phase emulsions (HIPEs) can be used to template the synthesis of porous polymer structures, and when solid particles are used as the interfacial agent, composites with pores lined with the particles can be realized. Here, we report a simple and scalable method to prepare conductive porous MXene/polyacrylamide structures via polymerization of the continuous phase in oil/water HIPEs. The HIPEs are stabilized by salt flocculated Ti 3 C 2 T x nanosheets, without the use of a co-surfactant. After polymerization, the polyHIPE structure consists of porous polymer struts and pores lined with Ti 3 C 2 T x nanosheets, as confirmed by scanning electron microscopy, energy dispersive x-ray spectroscopy, and x-ray photoelectron spectroscopy. The pore size can be tuned by varying the Ti 3 C 2 T x concentration, and the interconnected Ti 3 C 2 T x network allows for electrical percolation at low Ti 3 C 2 T x loading; further, the electrical conductivity is stable for months indicating that in these composites, the nanosheets are stable to oxidation at ambient conditions. The polyHIPEs also exhibit rapid radio frequency heating at low power (10 °C s −1 at 1 W). This work demonstrates a simple approach to accessing electrically conductive porous MXene/polymer composites with tunable pore morphology and good oxidation stability of the nanosheets. 

Different types of lane-changing assistance systems are usually developed separately by different automotive makers or suppliers. A lane-changing model can meet its own requirements, but it may be incompatible with another lane-changing model. In this paper, we verify if two lane-changing models are compatible so that the two corresponding vehicles on different lanes can exchange their lanes successfully. We propose a methodology and an algorithm to perform the verification on the combinations of four lane-changing models. Experimental results demonstrate the compatibility (or incompatibility) between the models. The verification results can be utilized during runtime to prevent incompatible vehicles from entering a lane-changing road segment. To the best of our knowledge, this is the first work considering the compatibility issue for lane-changing models. 

Connected Autonomous Vehicles (CAVs) are expected to enable reliable and efficient transportation systems. Most motion planning algorithms for multi-agent systems are not completely safe because they implicitly assume that all vehicles/agents will execute the expected plan with a small error. This assumption, however, is hard to keep for CAVs since they may have to slow down (e.g., to yield to a jaywalker) or are forced to stop (e.g. break down), sometimes even without a notice. Responsibility-Sensitive Safety (RSS) defines a set of safety rules for each driving scenario to ensure that a vehicle will not cause an accident irrespective of other vehicles' behavior. RSS rules, however, are hard to evaluate for merge, intersection, and unstructured road scenarios. In addition, deadlock situations can happen that are not considered by the RSS. In this paper, we propose a generic version of RSS rules for CAVs that can be applied to any driving scenario. We integrate the proposed RSS rules with the CAV's motion planning algorithm to enable cooperative driving of CAVs. Our approach can also detect and resolve deadlocks in a decentralized manner. We have conducted experiments to verify that a CAV does not cause an accident no matter when other CAVs slow down or stop. We also showcase our deadlock detection and resolution mechanism. Finally, we compare the average velocity and fuel consumption of vehicles when they drive autonomously but not connected with the case that they are connected.