In this paper we propose a new theoretical -yet applicable -framework to model the vehicular traffic. We model a vehicle as an automaton that has its own propulsion and can see the state of other automata in a constant size neighborhood. The rules guiding the change of states of each vehicle comprises of the common traffic rules.By observing the dynamics of such automata, we can devise optimal rules that may relieve the traffic congestion, and increase road safety.Last but not least, this model is an algorithmic framework to devise novel algorithms that use vehicular networks and communication between cars and the infrastructure.

No abstract

No abstract

No abstract

In this paper, we propose STCM, a context-aware secure traffic control model to manage competing traffic flows at a given intersection by using secure messages with real-time traffic information. The vehicle is modeled as a virtual sensor which reports the traffic state, such as its speed and location, to a traffic light controller through a secure and computationally lightweight protocol. During the reporting process, a vehicle’s identity and location are kept anonymous to any other vehicle in the system. At an intersection, the traffic light controller receives the messages with traffic information, verifies the identities of the vehicles, and dynamically implements and optimizes the traffic light phases in real-time. Moreover, the system is able to detect the presence of emergency vehicles (such as ambulances and fire fighting trucks) in the communication range and prioritize the intersection crossing of such vehicles to in order to minimize their waiting times. The simulation results demonstrate that the system significantly reduces the waiting time of the vehicles in both light and heavy traffic flows compared to the pretimed signal control and the adaptive Webster’s method. Simulation results also yield effective robustness against impersonating attacks from malicious vehicles.