Modeling and simulation play an important role in transportation networks analysis. With the widespread use of personalized real-time information sources, the status of the simulation depends heavily on individual travelers reactions to the received information. As a consequence, it is relevant for the simulation model to be individual-centered, and agent-based simulation is the most promising paradigm in this context. Information is now personalized, and the simulations have to take into account the interaction of individually guided passengers. In this paper, we present a multiagent simulation model to observe and assess the effects of real-time information provision on the passengers in transit networks. These effects are measured by simulating several scenarios according to the ratio of connected passengers to a real-time information system. We represent the passengers and the vehicles as agents in the system. We analyze the simulated scenarios following their effect on the passengers travel times. The information provided to the connected passengers is based on a space-time representation of the transportation networks. Results show that real-time personalized information may have an increasingly positive impact on overall travel times following the increasing ratio of connected passengers. However, there is a ratio threshold after which the effect of real-time information becomes less positive.

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Intelligent Transport Systems (ITSs) are part of road transportation sector evolution and constitute one of the main steps towards vehicle automation. These systems use technologies that allow vehicles to communicate with each other or with road infrastructure. By increasing information quality and reliability, ITSs can improve road safety and traffic efficiency, but only if cybersecurity and data protection is ensured. With the increase in the number of cyberattacks around the world, cybersecurity is receiving increased attention, especially in the area of transportation security. However, it is equally important to examine and analyze security in depth when it concerns connected vehicles. In this paper, we propose a qualitative risk analysis of ITSs based on Threat, Risk, Vulnerability Analysis (TVRA) methodology, and we focus on ETSI ITS communication architecture. We present a review of solutions and countermeasures for identified critical attacks.