25-05-2012, 12:54 PM
Toward an Effective Risk-Conscious and Collaborative Vehicular Collision Avoidance System
[attachment=22987]
INTRODUCTION
ALONG with the ongoing advances in dedicated shortrange
communication (DSRC) and wireless technologies,
intervehicular communication (IVC) and road–vehicle communication
(RVC) have become possible, giving birth to a new
network-type called vehicular ad-hoc network (VANET). The
key role that VANETs can play in the realization of intelligent
transport systems has attracted the attention of major car
manufacturers (e.g., Toyota, BMW, and Daimler-Chrysler). A
number of important projects have been subsequently launched.
Crash Avoidance Metrics Partnership (CAMP), Chauffeur in
Europe Union, CarTALK2000, FleetNet, and DEMO 2000
by the Japan Automobile Research Institute (JSK) are a few
notable examples.
RELATED WORK
VANETs are well characterized for their rapidly and dynamically
changing topologies due to the fast motion of vehicles.
Unlike traditional mobile ad hoc networks (MANETs), the
nodes’ mobility in VANETs is constrained by predefined roads
and restricted speed limits. Additionally, nodes in VANETs can
be equipped with devices with potentially longer transmission
ranges, rechargeable source of energy, and extensive on-board
storage capacities. Processing power and storage efficiency are,
thus, not the issue in VANETs that they are in MANETs.
CLUSTER-BASED RISK-AWARE COOPERATIVE COLLISION-AVOIDANCE SYSTEM
In this section, we initially provide a brief overview of
the functionality of the traditional CCA system proposed by
Biswas et al. [17] and point out its shortcomings. We then
propose our C-RACCA system, which consists of adequate
solutions to address these issues, namely, a dynamic clustering
procedure to formulate clusters of vehicles, followed by a
uniquely designed risk-aware MAC protocol.
Risk-Aware MAC Protocol
In this section, we describe the envisioned risk-aware MAC
protocol. To lay the basis of this work, we consider studying
the original MAC protocol in the IEEE 802.11 specifications,
owing to its enormous popularity among VANET designers and
researchers. For simplicity, the case of a single cluster is considered,
whereby the vehicles are indexed based upon their order
within the cluster with respect to their movement directions.
In other words, without any loss of generality, C1 refers to the
cluster head, C2 refers to the car immediately behind it, and so
forth. In addition, we consider highway platoons for studying
the envisaged risk-aware MAC protocol due to the fact that the
likelihood of chain vehicle collisions is substantially high in a
highway.
CONCLUSION
In this paper, we have proposed an effective collisionavoidance
strategy for vehicular networks that we refer to as
the C-RACCA system. As it can be inferred from its name,
the C-RACCA forms clusters of vehicles that belong to the
same group. A number of features pertaining to the movements
of the vehicles are taken into account to construct effective
clusters. We envisioned a set of mechanisms to enable vehicles
to join or depart from a specific cluster. Indeed, the clustering
mechanisms lead to various heterogeneous clusters, i.e., multiple
clusters with different sizes, independent cluster heads, and
different numbers of subcluster heads.
[attachment=22987]
INTRODUCTION
ALONG with the ongoing advances in dedicated shortrange
communication (DSRC) and wireless technologies,
intervehicular communication (IVC) and road–vehicle communication
(RVC) have become possible, giving birth to a new
network-type called vehicular ad-hoc network (VANET). The
key role that VANETs can play in the realization of intelligent
transport systems has attracted the attention of major car
manufacturers (e.g., Toyota, BMW, and Daimler-Chrysler). A
number of important projects have been subsequently launched.
Crash Avoidance Metrics Partnership (CAMP), Chauffeur in
Europe Union, CarTALK2000, FleetNet, and DEMO 2000
by the Japan Automobile Research Institute (JSK) are a few
notable examples.
RELATED WORK
VANETs are well characterized for their rapidly and dynamically
changing topologies due to the fast motion of vehicles.
Unlike traditional mobile ad hoc networks (MANETs), the
nodes’ mobility in VANETs is constrained by predefined roads
and restricted speed limits. Additionally, nodes in VANETs can
be equipped with devices with potentially longer transmission
ranges, rechargeable source of energy, and extensive on-board
storage capacities. Processing power and storage efficiency are,
thus, not the issue in VANETs that they are in MANETs.
CLUSTER-BASED RISK-AWARE COOPERATIVE COLLISION-AVOIDANCE SYSTEM
In this section, we initially provide a brief overview of
the functionality of the traditional CCA system proposed by
Biswas et al. [17] and point out its shortcomings. We then
propose our C-RACCA system, which consists of adequate
solutions to address these issues, namely, a dynamic clustering
procedure to formulate clusters of vehicles, followed by a
uniquely designed risk-aware MAC protocol.
Risk-Aware MAC Protocol
In this section, we describe the envisioned risk-aware MAC
protocol. To lay the basis of this work, we consider studying
the original MAC protocol in the IEEE 802.11 specifications,
owing to its enormous popularity among VANET designers and
researchers. For simplicity, the case of a single cluster is considered,
whereby the vehicles are indexed based upon their order
within the cluster with respect to their movement directions.
In other words, without any loss of generality, C1 refers to the
cluster head, C2 refers to the car immediately behind it, and so
forth. In addition, we consider highway platoons for studying
the envisaged risk-aware MAC protocol due to the fact that the
likelihood of chain vehicle collisions is substantially high in a
highway.
CONCLUSION
In this paper, we have proposed an effective collisionavoidance
strategy for vehicular networks that we refer to as
the C-RACCA system. As it can be inferred from its name,
the C-RACCA forms clusters of vehicles that belong to the
same group. A number of features pertaining to the movements
of the vehicles are taken into account to construct effective
clusters. We envisioned a set of mechanisms to enable vehicles
to join or depart from a specific cluster. Indeed, the clustering
mechanisms lead to various heterogeneous clusters, i.e., multiple
clusters with different sizes, independent cluster heads, and
different numbers of subcluster heads.