Abstract
Traffic management has been and remains to be a major problem especially in urban areas with high vehicle density. Adoption of intelligent transport system (ITS) has been widely experimented with the intention of curbing traffic menace with mixed experiences as the outcome. By communicating with other vehicles travelling on the same road in form of clusters, vehicular ad hoc network (VANET) forms an ITS that can allow cooperation of vehicles with less human input. By considering the high mobility nature of the vehicles in VANET, this paper presents a solution to the main menace of VANET clustering by adopting the flexibility of fuzzy logics for cluster formation on a multilane urban highway. It also shows that the stability of clusters is improved by performing the cluster head (CH) selection process based on a combination of fuzzy logics, lane weighting, and utility function with the fuzzy membership function adjusted to increase stability of clusters.
Highlights
Vehicles in a route travelling in one direction have similar characteristics related to direction of travel, relative speeds, and proximity to each other
All the vehicles in the network are equipped with On-Board Unit (OBU) and global positioning system (GPS) which allows the vehicle to know its position on the road segment
An roadside unit (RSU) used is not limited to one way vehicles but can communicate with vehicle heading on different directions
Summary
Vehicles in a route travelling in one direction have similar characteristics related to direction of travel, relative speeds, and proximity to each other. Since VANET topology is not random but dynamic and predictable, it is possible for vehicles to communicate and share information for an extended period of time without breaking the link. This communication is made possible by utilization of Dedicated Short-Range Communication (DSRC), designed with 75 MHz band between 5.850 and 5.925GHz of the frequency spectrum based on IEEE 802.11p and IEEE 1609.X standard for supporting various vehicular communication applications [7], [8]. With the limited bandwidth of 75 MHz allocated for communication, breakdown in communication links are bound to be experienced The solution to this problem is the application of clustering techniques which partition the network into smaller units.
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