A Stochastic Model for Chain Collisions of Vehicles Equipped With Vehicular Communications

Abstract

Improvement of traffic safety by cooperative vehicular applications is one of the most promising benefits of VANET. However, in order to develop properly such applications, the influence of the different driving parameters on the event of a vehicle collision must be assessed at an early design stage. In this paper we derive a stochastic model for the number of accidents in a platoon of vehicles equipped with a warning collision notification system, which is able to inform all the vehicles about an emergency event. In fact, the assumption of communications being used is key to simplify the derivation of a stochastic model. The model enables the computation of the average number of collisions that occur in the platoon, the probabilities of the different ways in which the collisions may take place as well as other statistics of interest. Although an exponential distribution has been used for the traffic density, it is also valid for different probability distributions for the traffic densities as well as for other significant parameters of the model. Moreover, the actual communication system employed is independent of the model since it is abstracted by a message delay variable, which allows it to be used to evaluate different communication technologies. We validate the proposed model with Monte-Carlo simulations. With this model one can quickly evaluate numerically the influence of the different model parameters (vehicle density, velocities, decelerations and delays) on the collision process and draw conclusions that shed relevant guidelines for the design of vehicular communication systems as well as Chain Collision Avoidance (CCA) applications. Illustrative examples of application are provided, though a systematic characterization and evaluation of different scenarios is left as future work.

R-MAC: Risk-Aware Dynamic MAC Protocol for Vehicular Cooperative Collision Avoidance System

“…However, it is assumed that all the vehicles have the same initial speeds and intervehicle distance. A more recent work [21] derived a stochastic model for the number of accidents in the platoon of vehicles equipped with a warning messages communication system. Nevertheless, all the parameters in the model were described by random variables, which cannot give a reliable collision prediction for the real-time traffic scenario.…”

“…Nevertheless, all the parameters in the model were described by random variables, which cannot give a reliable collision prediction for the real-time traffic scenario. Thus, based on the analysis method in [21], we derive a more reliable and practical stochastic collision prediction model, which takes full advantage of the beacons and warning messages.…”

“…Therefore, the collision model is based on the construction of the probability graph depicted in Figure 4, the length of which is − + 1 [21]. We consider an initial state in which no vehicle has collided.…”

A stochastic approach for vehicle safety modeling in a platoon of vehicles equipped with vehicular communications

“…The l i−1 computation is not trivial, and it is detailed in [2]. Let us mention that this computation takes into account the different ways a collision may occur (vehicles have not started to brake, only one of them is braking, both of them are braking or the front vehicle has stopped), since each one of these possibilities results in a different distance traveled.…”

Speeding Up the Evaluation of a Mathematical Model for VANETs Using OpenMP

“…However, the method to compute the probabilities of the path outcomes is independent of the correctness or accuracy of the transition probabilities used, and the goal of this paper is to evaluate the benefits of parallelization for this technique to compute the average number of accidents. An improved model for the transition probabilities can be found in [28].…”