A Collaborative Environment Perception Approach for Vehicular Ad Hoc Networks

Abstract

In this paper, we focus on vehicular safety applications based on the Dedicated Short Range Communication (DSRC) standard. We propose a new mechanism to alleviate channel congestion by reducing the beacons load while maintaining an accurate awareness level. Our scheme is based on the collective perception concept which consists in sharing perceived status information collected by vehicles equipped with different types of sensors (radars, lidars, cameras, etc.). To achieve our goal, we propose two main schemes. The first one consists in implementing the collective perception capability on vehicles and adding a new category of status messages to share locally collected sensor data in order to reduce channels load and enhance vehicles' awareness. The second scheme concerns the accuracy level of the received information from the collective perception enabled vehicles by fixing a prior error threshold on the position. The method proposed is validated by simulations and the results obtained are compared to those of an application based on the traditional beaconing scheme of the IEEE802.11p standard. The simulations show that the proposed scheme is able to significantly reduce the load on the control channel incurred by the beacons and the packet error ratio for different network densities and built-in sensors characteristics.

On the benefits of increased vehicles perception to cooperative communications

“…In this paper, we analyzed the utilization and benefits of the vehicle's embedded sensors to enhance car perception and improve cooperative communication efficiency. To this purpose, we implemented the Collaborative Environment Perception Approach for vehicular safety applications proposed by [1] and analyze its performance and behavior in congested urban traffic. In this ECAM (Extended Cooperative Awareness Message) mechanism, vehicles share information of their neighboring vehicles through a collaborative beaconing scheme to reduce congestion on the communication channel collected by their various type of sensors.…”

“…We believe that a cooperative approach that uses vehicles' embedded sensors does not degrade these parameters while increasing the communication range and awareness of the vehicles while reducing the channel load. [1] enhances the classical CAM scheme and provides a collective perception approach by sharing the information collected from embedded sensors among connected vehicles. The objective is to take advantage of some safety features using sensors integrated to recent vehicles, such as acoustic sensors, cameras, radars, lidars, etc.…”

“…The primary objective of this paper is to study the benefits of exploiting vehicle's embedded sensors to increase its perception and use this feature to enhance the cooperative awareness and decrease the contention on the wireless interface by reducing beacon transmissions. To this purpose, we will expand the work proposed in [1] and study its performance in the congested traffic of the urban environment. The proposed scheme, so-called ECAM (Extended Cooperative Awareness Message), utilizes the Collective perception concept [6] [7] to decrease the frequency of beacons.…”

“…In this paper, we analyze the benefits of exploiting vehicle's embedded sensors to enhance car perception and hence improve the efficiency of cooperative communications. To this purpose, we implemented the collaborative environment perception approach for vehicular safety applications proposed by [1] and analyze its performance and behavior in congested urban traffic. In this proposal, so-called ECAM (Extended Cooperative Awareness Message), vehicles use a different type of sensors (cameras, radars, lidars etc.)…”

Context-Aware Content Selection and Message Generation for Collective Perception Services

“…Finally, channel overloading being one major issue with CPM dissemination, it has been shown that controlling CPM content can have a positive impact on channel usage [24,31]. In [32], the authors proposed to assess channel congestion to adapt object inclusion policies.…”