# Augmenting CCAM Infrastructure for Creating Smart Roads and Enabling Autonomous Driving
## 4 Literature Review
However, the minimization problem can be difficult from three perspectives, namely, the unknowable latency function, the Markovian nature of the problem, and the heterogeneity of time scales associated with the coupling optimization variables. They used the ORB algorithm to extract features from sensor images for relocalization, which results in creating a global map (the latest point clouds are broadcasted to all vehicles) based on the SLAM technique (which divides the computation between edge and vehicle components). To implement the EdgeMap, the following steps are taken:  
* A fully-connected neural network with Leaky Recifier and sigmoid activation functions is used for multiple DRL agents using PyTorch. * The GPR model is build using scikit-learn. * The Machine Hall 01-05 scenarios are used with the EuRoC dataset. * A time-driven network simulator is build for experiments, which consists of vehicles, servers, and a wireless transmission (based on an open-source 5G simulator) modules. * A desktop (AMD Ryzen 3600 3.8 GHz, 32 GB RAM) and a laptop (Intel i7-6500U 2.5 GHz, 8 GB RAM) were used as compute vehicles and edge servers in the experiments. On the desktop and laptop, the mean computation latency is 286.54 ms and 609.27 ms, respectively. With EdgeMap, 0.31 MHz is used for uplink, 0.02 MHz for downlink, 19.4% of computation resources (1.94 server capacity), and 9.2% of average resources, and an average latency of 502.8 ms is obtained. This translates to a 33% reduction in average resource usage when compared to other approaches. The CAMINO framework [12] supports hybrid cellular technologies, which are better suited to low latency use cases (e.g., truck platooning) and throughput-intensive passenger infotainment applications. In this way, the framework supports a multitude of services and enables dynamic management of technologies and integration of devices, interfaces, and services (with the help of DUST framework). The proposed framework manages C-ITS messages via controller, controls the data flow between interfaces, and interconnects different V2X wireless technologies. For example, communication of custom messages and standardized messages (i.e., CAM, DENM and IVIM) with C-V2X PC5 and ITS-G5 modules via UDP sockets and with an MQTT broker via TCP over wired (or cellular) networks. By using a publisher/subscriber architecture, DUST framework enables interconnection of devices, services, and interfaces for CAMINO. Hence, C-ITS services testings is possible over hybrid communication technologies. The proposed framework provides:  
* The logging service for post-processing information. * The forwarder service for external messages exchange using MQTT. * The GNSS service for positioning and timing information (using GPS daemon). * The GeoCasting services for messages distribution (using geo-tiling technique). For implementation and validation in real-life environments, the Smart Highway testbed used the Vanetza library (C-ITS protocol suite) for services, DUST publisher for real-time information access, public Belgian Government datasets for fetching traffic sign values, JSON message format for relevant information, DUST subscriber for relevant decoded information publishing, InterCor logging format for positioning/speed data, and entities, i.e., RSUs, MEC, OBUs for evaluating V2X technologies. For packet-loss evaluation, the Packet Delivery Rate (PDR) performance is almost equal by both short-range technologies and more stable (up to 600 m distance). For latency, ITS-G5 outperforms C-V2X PCS. The former takes 4 ms and the latter takes 33 ms to transmit 95% of the packets. For interoperability, it is evaluated through the V2X communication equipment, considering highways such as the E313 highway in Belgian and A16 highway in Amsterdam. The 5G-MEC [13] approach enables a cooperative perception between AVs in a specified targeted area. The AVs are registered with MEC and share their information in a periodical manner, which are stored in a database.