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Vehicular Ad-hoc Network (VANET) is an emerging technique dedicated to wireless vehicular communication to improve transportation safety by exchanging driving information between vehicles. For safety purposes, vehicles periodically broadcast a safety packet via Vehicle-to-Vehicle (V2V) communication. Accordingly, VANET safety applications demand a reliable exchange of the safety packet with high Packet Delivery Ratio (PDR), acceptable latency, and communication fairness. However, the communication performance significantly degrades due to numerous packet collisions when a large number of vehicles simultaneously access limited channel resources for the safety broadcast. In particular, the problem grows more severe in congested VANETs absent infrastructures since vehicles must control channel access using a self-adaptive scheme without external assistance. Thus, a robust and decentralized channel access protocol for VANETs is required to achieve road safety. In this paper, we propose an intelligent channel access algorithm empowered by cooperative Reinforcement Learning (RL), in which vehicles coordinate the channel access in a fully-decentralized manner. We also consider a proper interaction scheme between vehicles for enhancing the V2V safety broadcast in infrastructure-less congested VANETs. We provide evaluation results with extensive simulations according to various levels of traffic congestion. Simulations confirm the superior performance of the algorithm: the algorithm has a 20% increase in PDR compared to the latest RL-based channel access scheme. Furthermore, the algorithm satisfies the low latency requirement of VANET safety applications as well as both short-term and long-term communication fairness. INDEX TERMS Vehicular ad-hoc network, congestion control, decentralized channel access, reinforcement learning, cooperative multi-agent systems.

This paper presents a method to improve the Vehicle-to-Everything (V2X) security. With the recent rapid development of communication technology and traffic applications, V2X is recently commercialized and has been growing as a fundamental system for future applications. Because of the high mobility of the vehicles, V2X requires a low latency and high-reliability. However, previous security methods demand a large computational burden and generate high latency owing to complex operations and long additional data bits for ensuing security. To resolve such constraints, an advanced security method ensuring lower latency and higher reliability is required.We propose a noise-shaped signaling method that provides high-level security with low latency for reliable V2X communication. The proposed method encrypts original data symbols to noise-like symbols by applying a noise envelope that consists of Chaotic Random Magnitude Sequence (CRMS) and Chaotic Random Phase Sequences (CRPS). Our method simplifies the sequence sharing process between a sender and an intended receiver by adapting the characteristics of a chaotic dynamic system. Moreover, the proposed method does not demand additional data bits and generate delay because the method only uses simple multiplication and division procedure for data encryption in the physical layer. We analyze our method in depth using extensive simulations and various viewpoints such as error rate, probability of modulation identification. From the simulations, we demonstrate that a malicious adversary cannot comprehend the transmitted symbols and always has the maximum error rate under various network environments and conditions. We also demonstrate how the adversary cannot infer the modulation scheme from the symbols applying the proposed method. After these analyses, we confirm that the noise-shaped signaling method is high-level of secure method with a low latency for V2X communication.