Evaluating the Impact of Transmission Power on Selecting Tall Vehicles as Best Next Communication Hop

The relatively low height of antennas on communicating vehicles in Vehicular Ad Hoc Networks (VANETs) makes one hop and as well multi-hop Vehicle-to-Vehicle (V2V) communication susceptible to obstruction by other vehicles on the road. When the transmitter or receiver (or both) is a Tall vehi- cle, (i.e., truck), the V2V communication suffer less from these obstructions. The transmission power control is an important feature in the design of (multi- hop) VANET communication algorithms. However, the benefits of choosing a Tall vehicle when transmission power is varied are not yet extensively re- searched. Therefore, the main contribution of this paper is to evaluate the im- pact of transmission power control on the improved V2V communication capa- bilities of tall vehicles. Based on simulations, it is shown that significant bene- fits are observed when a Tall vehicle is selected rather than a Short vehicle as a next V2V communication hop to relay packets. Moreover, the simulation exper- iments show that as the transmission power is increasing, the rate of Tall vehi- cles that are selected as best next V2V communication hop is significantly growing

Vehicular Fog Computing Enabled Real-time Collision Warning via Trajectory Calibration

Vehicular fog computing (VFC) has been envisioned as a promising paradigm for enabling a variety of emerging intelligent transportation systems (ITS). However, due to inevitable as well as non-negligible issues in wireless communication, including transmission latency and packet loss, it is still challenging in implementing safety-critical applications, such as real-time collision warning in vehicular networks. In this paper, we present a vehicular fog computing architecture, aiming at supporting effective and real-time collision warning by offloading computation and communication overheads to distributed fog nodes. With the system architecture, we further propose a trajectory calibration based collision warning (TCCW) algorithm along with tailored communication protocols. Specifically, an application-layer vehicular-to-infrastructure (V2I) communication delay is fitted by the Stable distribution with real-world field testing data. Then, a packet loss detection mechanism is designed. Finally, TCCW calibrates real-time vehicle trajectories based on received vehicle status including GPS coordinates, velocity, acceleration, heading direction, as well as the estimation of communication delay and the detection of packet loss. For performance evaluation, we build the simulation model and implement conventional solutions including cloud-based warning and fog-based warning without calibration for comparison. Real-vehicle trajectories are extracted as the input, and the simulation results demonstrate that the effectiveness of TCCW in terms of the highest precision and recall in a wide range of scenarios

Performance of CAM based Safety Applications using ITS-G5A MAC in High Dense Scenarios

ETSI ITS-G5 is the current vehicle-to-vehicle communication technology in Europe, which will be standardized by ETSI TC ITS. It is based on IEEE 802.11p and therefore uses a CSMA/CA scheme for Media Access Control (MAC). In this paper we analyze the performance of CAM based safety applications using the ETSI ITS-G5 MAC technology in a challenging scenario with respect to MAC issues: A suitable freeway segment with 6 lanes in each direction. The freeway scenario is thoroughly modeled and implemented in the well known ns-3 simulation environment. Based on this model, the paper shows the performance of CAM based safety applications under MAC challenging conditions. Therefore we provide a set of simulation results resting upon a particular performance metric which incorporates the key requirements of safety applications. Finally we analyze two concrete example scenarios to make a point how reliable CAM based safety applications are in high dense traffic scenarios

Fine-grained traffic state estimation and visualisation

Tools for visualising the current traffic state are used by local authorities for strategic monitoring of the traffic network and by everyday users for planning their journey. Popular visualisations include those provided by Google Maps and by Inrix. Both employ a traffic lights colour-coding system, where roads on a map are coloured green if traffic is flowing normally and red or black if there is congestion. New sensor technology, especially from wireless sources, is allowing resolution down to lane level. A case study is reported in which a traffic micro-simulation test bed is used to generate high-resolution estimates. An interactive visualisation of the fine-grained traffic state is presented. The visualisation is demonstrated using Google Earth and affords the user a detailed three-dimensional view of the traffic state down to lane level in real time

Infrastructure Wi-Fi for connected autonomous vehicle positioning : a review of the state-of-the-art

In order to realize intelligent vehicular transport networks and self driving cars, connected autonomous vehicles (CAVs) are required to be able to estimate their position to the nearest centimeter. Traditional positioning in CAVs is realized by using a global navigation satellite system (GNSS) such as global positioning system (GPS) or by fusing weighted location parameters from a GNSS with an inertial navigation systems (INSs). In urban environments where Wi-Fi coverage is ubiquitous and GNSS signals experience signal blockage, multipath or non line-of-sight (NLOS) propagation, enterprise or carrier-grade Wi-Fi networks can be opportunistically used for localization or “fused” with GNSS to improve the localization accuracy and precision. While GNSS-free localization systems are in the literature, a survey of vehicle localization from the perspective of a Wi-Fi anchor/infrastructure is limited. Consequently, this review seeks to investigate recent technological advances relating to positioning techniques between an ego vehicle and a vehicular network infrastructure. Also discussed in this paper is an analysis of the location accuracy, complexity and applicability of surveyed literature with respect to intelligent transportation system requirements for CAVs. It is envisaged that hybrid vehicular localization systems will enable pervasive localization services for CAVs as they travel through urban canyons, dense foliage or multi-story car parks

A New Vehicle Localization Scheme Based on Combined Optical Camera Communication and Photogrammetry

The demand for autonomous vehicles is increasing gradually owing to their enormous potential benefits. However, several challenges, such as vehicle localization, are involved in the development of autonomous vehicles. A simple and secure algorithm for vehicle positioning is proposed herein without massively modifying the existing transportation infrastructure. For vehicle localization, vehicles on the road are classified into two categories: host vehicles (HVs) are the ones used to estimate other vehicles' positions and forwarding vehicles (FVs) are the ones that move in front of the HVs. The FV transmits modulated data from the tail (or back) light, and the camera of the HV receives that signal using optical camera communication (OCC). In addition, the streetlight (SL) data are considered to ensure the position accuracy of the HV. Determining the HV position minimizes the relative position variation between the HV and FV. Using photogrammetry, the distance between FV or SL and the camera of the HV is calculated by measuring the occupied image area on the image sensor. Comparing the change in distance between HV and SLs with the change in distance between HV and FV, the positions of FVs are determined. The performance of the proposed technique is analyzed, and the results indicate a significant improvement in performance. The experimental distance measurement validated the feasibility of the proposed scheme

Simulation of WLAN Based V2X Signal Models Using Deterministic Channel

Vehicle to everything (V2X) communication is one of the important topics in the telecommunication field aiming to provide a great improvement in the transport sector by increasing safety and comfort while driving as well as reducing traffic congestion and as a result there are a lot of researches , developments and investments made in this field. This thesis presents the use of Unity 3D game engine program for the creation of a deterministic channel model through which we can analyse and study the performance of the WLAN based signal models that are used in the vehicle to everything (V2X) technology.AN open source V2X simulator was used for the process of channel creation and performance assessment making use of its real time stochastic measurements .Two different methods were used to assess the performance of both the IEEE 802.11p and 802.11bd signal models with different calculations but eventually the latter proved to be the superior since it is considered the most advanced and latest version of the IEEE 802.11 family