Effect of connected and autonomous vehicles on traffic flow at a bidirectional road

The objective of this study was to investigate the impact of connected and autonomous vehicles (CAVs) on traffic flow under various parameters. For this purpose, we propose a mixed CAV and conventional vehicle (CV) model to investigate a bidirectional two-lane traffic flow under the periodic boundary condition. The traffic flux and the phase diagrams of the system in the ([Formula: see text]) area are constructed in both cases: with and without CAVs. The overtaking frequency is also calculated. The simulation findings show that the traffic capacity is greatly enhanced with the increase in the CAV penetration ratio. Owing to the cooperative driving strategy, with the increase in penetration ratio of the CAV, the portion of smooth overtaking is boosted. Furthermore, it is found that the traffic throughput is positively correlated to the speed limit of the fast vehicle where the flux increases as [Formula: see text] increases. Also, even if there is a low rate of slow moving vehicles in the system, it will have an appreciable and a significant negative influence.

AVoD: Advanced Verify-on-Demand for Efficient Authentication against DoS Attacks in V2X Communication

Owing to the development of information and communication technology (ICT), autonomous cooperative vehicles are being developed. Autonomous cooperative driving combines vehicle-to-everything (V2X) communication technology in existing autonomous driving and provides safe driving by sharing information between communication entities. However, security factors should be considered during communication. Security Credential Management System (SCMS) has been proposed as one of these elements, but it is vulnerable to denial-of-service (DoS) attacks due to message authentication costs. In congested situations, the number of messages exchanged between vehicles becomes very large. However, the performance of the on-board unit (OBU) is not sufficient to handle huge number of messages, which can lead to a DoS attack. Therefore, a technique to prevent DoS attacks on autonomous cooperative driving vehicles using SCMS has been proposed in this paper. The proposed technique reduces authentication costs by classifying similar messages into multiple categories and authenticating only the first message represented in the group for a unit time. The effectiveness of this technique has been demonstrated by comparing the time it takes to verify huge number of message signatures in each method.

Cooperative- and Eco-Driving: Impact on Fuel Consumption for Heavy Trucks on Hills

Greenhouse gas emissions are the cause of climate change, which in turn has a negative impact on people and the environment. Reducing the fuel consumption of conventional engines reduces climate-damaging emissions and can, thus, contribute to achieving climate protection goals. In addition, fuel costs are a major cost factor for long-haul trucking. Eco-driving helps to reduce fuel costs when driving on inclines and declines. Due to the high mass and, therefore, high kinetic and potential energy of heavy trucks, fuel can be saved by coasting before slopes and before speed limits. However, energy-efficient and non-cooperative driving, i.e., without considering other road users, can lead to increased fuel consumption as vehicles impede each other. To resolve conflicts in road traffic, a variety of methods that enable cooperative driving exist. In general, vehicles communicate with vehicle-to-everything (V2X) and negotiate a joint driving strategy. This paper presents a method that combines cooperative and energy-efficient driving and examines the impact on fuel consumption during uphill driving. The method relies on the exchange of trajectories for cooperative maneuver coordination. By computing a strategic trajectory, energy-efficient driving with long coasting maneuvers is enabled. In the simulative evaluation, travel over hills with two and three trucks is investigated. It is shown that the combination of cooperative and eco-driving reduces the fuel costs for traffic.