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Vehicular Ad-Hoc Networks (VANET) is a research venue that promises for many useful applications. Most of these applications require a precise real-time positioning system for each vehicle. However, practically the existing tecniques are still not accurate and hence not suitable for some critical applications. In this paper, we will focus on the most critical ones which are the collision avoidance, and collision warning, or lane-tracking. Collision occurs when the distance between nearby vehicles decreases rapidly. Hence, an accurate and precise knowledge of the distance among each vehicle and all the surrounding vehicles has to be obtained to enable a realistic collision avoidance service. We propose to use the carbon nanotube network (CNT) integrated with other nano-devices that can provide accuracy in the order of millimeters. In this paper, theoretical investigations and mathematical formulations are presented. The obtained results show the effectiveness and accuracy of the proposed methodology.

Recently, there are many research efforts on a new technology named as Vehicular Ad-Hoc Network (VANET) [1-5]. In VANET, vehicles will be equipped by wireless transceiver that allows each vehicle to communicate with the surrounding vehicles on the street. This is referred to vehicle-to-vehicle (V2V) communication. In addition, the roads will be reengineering by installing wireless equipments on the sides of roads. These equipments are referred as the Road-Side Units (RSUs). The RSUs are connected together using wired infrastructure or in some cases using the Wireless Mesh Networks (WMS) infrastructure. The RSUs are connected to the central servers. In this case, the vehicles can communicate also with the RSUs as they move. This type of communication is referred as Vehicle-to-Infrastructure (V2I) communication. Both V2V and V2I communications form moving ad-hoc networks. Using this network architecture, the vehicles can be connected all the time with the infrastructure network and with the surrounding vehicles. Many useful applications can be implemented with VANET. Some promising applications may include collision avoidance, cooperative driving, automatic driving, navigation and probe vehicle data that increase vehicular safety and reduce traffic congestion, and offer access to the internet and entertainment applications. Another kind of services that could not be realistic without VANET includes the autonomous street lightening system [

On the other hand, VANET technology is still in the research phase, where there are some challenges to be undertaken before the real deployment of VANET technology on the streets. The most critical one is the positioning system (aka localization system) for the vehicles. In other words, this system answers the question “How to provide each vehicle by its real time location?” There exist several positioning techniques that are suitable for many applications [9-18]. Each application or service provided by VANET has its own requirement of the positioning system. Some applications may tolerate some error level in the positioning information. Other applications require a very accurate and reliable positioning system. Example of the first category is the traffic management applications. Most of the safety applications on the other hand require the second category. Some examples are the collision avoidance, automatic driving and lane tracking. The accuracy of positioning system must be within the centimeter. In addition, its availability must be guaranteed. If it fails for some time, catastrophic circumstances may occur such as collisions or car crashes.

The most famous positioning system is the GPS (by using a set of satellites that feeds information about the position of a GPS receiver). However, all the existing positioning techniques including the GPS have several drawbacks. Lack of accuracy of the resulting measurements is the most unacceptable disadvantage. For example, GPS devices can produce an error of up to 50 meters [

On the other hand, nanotechnology is a field of science that is concerned by controlling matter on a scale between 1 - 100 nm. It provides solutions for sensing, actuation, radio, embedding intelligence into the environment, power efficient computing memory, energy sources, human-machine interaction, materials, mechanics, manufacturing and environment issues [19-26].

Nanotechnology wireless ad-hoc networks with large number of extremely low cost, low power nodes are studied. For example, all required components of a wireless sensor node, i.e., a sensing unit, a processing unit, and a power unit have already been demonstrated with nanoelments, such as carbon nanotubes (CNs) [27-32]. Nanotechnology transceivers devices have important role in the network applications. It increases the sensorial of each vehicle with other neighboring things. We, thus, will provide a theoretical study for obtaining accurate inter-vehicle distance measures based on the CNT networks.

In this paper, we propose an accurate inter-vehicle distance estimation model that can be used for accurate short distance estimation. The range can be less than 20 meters and with accuracy that can be within several millimeters. The model is referred as the Vehicular Carbon Nanotube (VCNT) networks. It is clear that this system can be used in the critical applications like the collision avoidance. The system is accurate and reliable and can work in all areas. If this system is used in conjunction with DGPS, it could provide a full range of distance and position estimation in real time.

The rest of this paper is organized as follows: In Section 2, the related works and research efforts are given. Theoretical model of vehicle carbon nanotube network is denoted in Section 3. Finally, the conclusions and the future works are given in Section 4.

There exits two categories of positioning systems: indoors techniques [33,34], which are not suitable for VANET due to its cost and the limited distance they support. Another research works in VANET positioning includes the following techniques. First, the signalstrength-based techniques, where the receiver calculates an estimate of its location based on the received signal strength from several wireless access points. These techniques are not accurate. Reported results based on this technique shows poor accuracy [1,13] (around 50 meters). An interesting work that proposes a positioning system based on the Received Signal Strength (RSS) for VANET is proposed in [

Second, Time-Of-Arrival (TOA)-Based techniques, which are based on the travelled distance from the base station to the receiver of a known signal. This is the solution adopted by GPS [

From nanotechnology point of view, the significant interesting application is wireless ad-hoc networks with large number of extremely low-cost, low power elements. For example all the required components of a wireless sensor node, i.e., a sensing unit, a processing unit, a transceiver unit, and a power unit have already been demonstrated with nanoelments, such as carbon nanotubes (CN) [

A nanosensor is not necessarily a device merely reduced in size to a few nanometers, but a device that makes use of the unique properties of nanomaterials and nanoparticles to detect and measure new types of events in the nanoscale [

The activation signal is an electromagnetic wave has certain duration, tuned according to the resonance frequency of the nanotube antennas of the nodes to be activated [

Here, description of the construction of VCNT and mathematical model will be demonstrated for the overall capacity and the capacity per meter between nodes. CNT have a period of one decade and each year new applications are proposed [

The total VCNT is the sum of vehicles in the zone at specific time. The number of nodes (vehicles) is changed according to the place and time in ad-hoc manner. So, we will start by determining the internal link capacity between nodes. The capacity per meter of a channel from specified transmitter to receiver is given by Shannon’s famous formula [

where, BW is the bandwidth of the communication, S/N is the signal-to-noise ratio (SNR) of the link, and d is the distance. The previous formula states the relation between the theoretical of clean maximum bit rate of clean data (or low bit error rate) with a given average signal power that can be sent through an FM analog communication channel subject to additive, white, and Gaussiandistribution noise interference.

Also, the obtained channel capacity for CNT is higher than the traditional wireless network as it depends on the BW which is in the range of THz in our case. In VCNT model, assume that each point source is omni-directionally radiation and a network of the randomly distributed n nodes is spread over a circular area, A. Each connection between the adjacent nodes (vehicles) has a determined channel capacity, C_{TR}. Also, there is guard distance ∆, which ensure channel transmission do not overlap [

where, is the expected nearest-neighbor distance, the summation denotes the total distance that data must travel.

_{max }

_{ }

will be dramatically greater than before. To have a wide view about the behavior of VCNT, Figures 5 and 6 depict the concept of dependency of maximum capacity into each of radiation radius; r and the distance between nanotube transmitter and receiver; d, at two values of bandwidth. One can recognize that as the distance increased, Cmax will decrease as discussed before in

From the above equations, the distance can be estimated from SNR and capacity (see Figures 5 and 6). Finally, it is desirable to obtain accurate distance estimation at small space between vehicles and continuously cover suitable area surrounding it at any instant of time while it moves. This will direct us to denote more attention for studying and analyzing the important role of

nano-processor in the future for activating or deactivating the surrounding nodes at any time and at any speed of vehicle.

In this paper, an integrated nanotechnology model that can be used to precisely cover and assign the locations in near distance positions is presented. Moreover, we aimed to obtain distance estimation within several meters with an accuracy of several millimeters.

Additionally, the theoretical model for Vehicular Nano Tube Networks (VCNT) is presented. The aim of this theoretical phase is to complete the picture that the nanotechnology system for vehicular positioning can be exploited to give more accuracy and high performance with lower cost and power consumption. Future research direction may include the validation of the model in realistic environment.