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In order to use the road network as efficiently as possible and to fully exploit the potential of automated vehicles, vehicle cooperation is essential. Conflicts between road users over available space on the road can only be resolved efficiently through cooperation. To this end, we investigate the space time reservation procedure (STRP) which is a generic approach to cooperation between vehicles. The method is based on a decentralized two-step negotiation procedure during which parts of the road can be reserved in order to carry out maneuvers that were originally conflicting. After the rollout of the first cooperative automated vehicles, a long transition period with mixed traffic is expected. Since the approach in this paper builds on existing road traffic regulations and does not abolish them, the method can also be applied in mixed traffic. Compared to the preliminary work on this approach, the method is simplified and further generalized for already supported traffic situations. This increases flexibility during the execution of cooperative maneuvers. Additionally, new reservation geometries covering almost all possible conflicts in traffic are investigated, e. g. lane changes, intersections, overtaking, roundabouts. Finally, the approach is evaluated by means of test drives with two research vehicles and in simulations.

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The emergence of connected automated vehicles and advanced V2X applications and services can challenge the scalability of vehicular networks in the future. This challenge requires solutions to reduce and control the communication channel load beyond the traditional congestion control protocols proposed to date. In this paper, we propose and evaluate the use of V2X message compression to reduce the channel load and improve the scalability and reliability of future vehicular networks. Data compression has the potential to reduce the channel load consumed by each vehicle without reducing the amount of information transmitted. To analyze its potential, this paper evaluates the compression gain of three compression algorithms using standardized V2X messages for basic awareness (CAMs), cooperative perception (CPMs) and maneuver coordination (MCMs) extracted from standard-compliant prototypes. We demonstrate through network simulations that V2X message compression can reduce the channel load. In particular, the tested compression algorithms can reduce the channel load by up to 27% without reducing the amount of information transmitted. Reducing the channel load and the consequent interferences significantly improves the reliability of V2X communications. However, this study also emphasizes the need for high-speed compression and decompression modules capable to compress and decompress V2X messages in real time, especially under highly loaded scenarios.