Vehicle Mobility Information Research Articles

Multiple Precaching Vehicle Selection Scheme Based on Set Ranking in Intermittently Connected Vehicular Networks

In vehicular networks, vehicles download vehicular information for various applications, including safety, convenience, entertainment, and social interaction, from the corresponding content servers via stationary roadside units. Since sufficient RSUs might be difficult to deploy due to rough geographical conditions or high deployment costs, vehicular networks can feature uncovered outage zones between two neighboring RSUs. In these outage zones, vehicles cannot download content, and thus the vehicle networks are defined as intermittently connected vehicular networks. In intermittently connected vehicular networks, the download delay and traffic overhead on the backhaul links are increased due to the large size of the content requested by vehicle users and the long distances between RSUs. Using the mobility information of vehicles, several schemes have been proposed to solve this issue by precaching and relaying content via multiple relaying vehicles in the outage zone. However, because they involved the individual ranking of vehicles for precaching and allocated all of the available precaching amounts to the top-ranking vehicles, they decreased the success rate of content requests and the fairness of vehicle precaching. To overcome the problem of these previous schemes, this paper proposes a multiple precaching vehicle selection (MPVS) scheme that efficiently selects a content-precaching vehicle group with multiple precaching vehicles to precache relayed content in outage zones. To achieve this, we first designed numerical models to decide the necessity and the amount of precaching and to calculate the available precaching amounts of vehicles. Next, MPVS calculates all available vehicle sets and ranks each set based on the available precaching amount. Then, the content-precaching vehicle group is identified from the sets by considering both set rankings and vehicle communication overheads. MPVS also provides a content downloading process through the content-precaching vehicle group in the outage zone. Simulation results conducted in various environments with a content request model and a highway mobility model verified that MPVS was superior to a representative previous scheme.

Handover Network Selection for Vehicle in LTE-A Communication Networks

One of the challenges to achieving smooth communications in heterogeneous networks is to find the right balance between various handover parameters for network selection. The Receive Signal Strength (RSS) from a network's Point of Attachment (PoA) is the primary factor used in traditional approaches to network selection. Therefore, network selection is vital for a successful handover in the vehicle communications network. However, vehicles moving through such diverse networks faced difficulties like frequent unwanted handovers, selecting the wrong candidate networks for handovers, and taking too long to finish the drawn-out handover procedure, which results in failed handovers. All of these factors will impair the efficiency of the handover process, which will affect the smooth operation of the vehicles. Hence, the main idea of this research is to improve the handover network performance selection performance. The proposed work is for vehicles to self-evaluate a candidate list of Access Points (AP) that are located in the vehicle movement direction and select the best underlying candidate network. In this project, the network selection framework of the vehicle communications network with the distance between the target candidate and the trajectory of the vehicle movement was developed as well as the vehicle mobility information. The important parameters which are the relative direction index, proximity index and residence time index are chosen to identify the best candidate network. Once the target of the base station has been identified, then the optimum value of the distance is calculated using the Particle Swarm Optimization (PSO) technique to initiate the handover process. The performance of the proposed handover network selection is simulated and evaluated using MATLAB software. The results show that the proposed handover network selection method improved the successful handover rate as compared to the conventional method.

Cooperative Content Precaching Scheme Based on the Mobility Information of Vehicles in Intermittently Connected Vehicular Networks

Intermittently connected vehicular networks (ICVNs) consist of vehicles moving on roads and stationary roadside units (RSUs) deployed along roads. In ICVNs, the long distances between RSUs and the large volume of vehicular content lead to long download delays to vehicles and high traffic overhead on backhaul links. Fortunately, the improved content storage size and the enhanced vehicular mobility prediction afford opportunities to ameliorate these problems by proactively caching (i.e., precaching) content. However, existing precaching schemes exploits RSUs and vehicles individually for content precaching, even though the cooperative precaching between them can reduce download delays and backhaul link traffic. Thus, this paper proposes a cooperative content precaching scheme that exploits the precaching ability of both vehicles and RSUs to enhance the performance of content downloads in ICVNs. Based on the trajectory and velocity information of vehicles, we first select the optimal relaying vehicle and the next RSUs to cache the requested content proactively and provide it to the requester vehicle optimally. Next, we calculate the optimal content precaching amount for each of the relaying vehicle and the downloading RSUs by using a mathematical model that exploits both the dwell time in an RSU and the contact time between vehicles. To compensate for the error of the mobility prediction in determining both the dwell time and the contact time, our scheme adds a guardband to the optimal content precaching amount by considering the expected reduced delay. Finally, we evaluate the proposed scheme in various simulation environments to prove the achievement of efficient content download performance by comparing with the existing schemes.

Enhanced weight-based clustering algorithm to provide reliable delivery for VANET safety applications.

A vehicular ad hoc network (VANET) is an emerging and promising wireless technology aimed to improve traffic safety and provide comfort to road users. However, the high mobility of vehicles and frequent topology changes pose a considerable challenge to the reliable delivery of safety applications. Clustering is one of the control techniques used in VANET to make the frequent topology changes less dynamic. Nevertheless, research has shown that most of the existing clustering algorithms focus on cluster head (CH) election with very few addressing other critical issues such as cluster formation and maintenance. This has led to unstable clusters which could affect the timely delivery of safety applications. In this study, enhanced weight-based clustering algorithm (EWCA) was developed to address these challenges. We considered any vehicle moving on the same road segment with the same road ID and within the transmission range of its neighbour to be suitable for the cluster formation process. This was attributed to the fact that all safety messages are expected to be shared among the vehicles within the vicinity irrespective of their relative speedto avoid any hazardous situation. To elect a CH, we identified some metrics on the basis of the vehicle mobility information. Each vehicle was associated with a predefined weight value based on its relevance. A vehicle with the highest weight value was elected as the primary cluster head (PCH). We also introduced a secondary cluster head (SeCH) as a backup to the PCH to improve the cluster stability. SeCH took over the leadership whenever the PCH was not suitable for continuing with the leadership. The simulation results of the proposed approach showed a better performance with an increase of approximately40%– 45% in the cluster stability when compared with the existing approaches. Similarly, cluster formation messages were significantly minimized, hence reducing the communication overhead to the system and improving the reliable delivery of the safety applications.

In-vehicle sensor-assisted platoon formation by utilizing vehicular communications

These days, vehicles are equipped with in-vehicle sensors so that they can collect the situation-related information, such as velocity, heading, and position. From the viewpoint of intelligent transportation system, platooning is getting more attention because of its advantages of increased road capacity, fuel saving, safety, and so on. In this article, we propose a mechanism that allows vehicles to form platoons based on their own and 1-hop neighbors’ sensory information obtained from vehicular communications. Within a platoon, the front vehicle is the leader whose role is leading the platoon, so the stability of the leader is the most critical performance factor of platooning. To achieve this, we propose to use relative mobility information of vehicles computed from the sensory information for the leader election. The performance of our platooning mechanism is evaluated by carrying out ns-3-based simulations, especially from the perspective of leader stability and road capacity.

GeoMobCon: A Mobility-Contact-Aware Geocast Scheme for Urban VANETs

Geocast, which consists of delivering messages to a specific location, has become an important technique with the accelerated development of the location-based services in mobile networks. Geocast in the automotive domain is of particular interest, enabling many promising applications, such as geographic advertising, location-based traffic alerts, etc. Different from the conventional geocast algorithms focusing on the distance-based approaches, in this paper, we propose a node mobility-aware and node contact-aware geocast algorithm (GeoMobCon) for urban vehicular ad hoc networks from the delay-tolerant network perspective to better deal with the high mobility and transient connectivity issues. Different levels and aspects of vehicle mobility information and self-maintained contact information are employed, making GeoMobCon simple, scalable, and communication and computation effective. Practical issues are well considered by introducing real-world trace analysis, trace-driven simulation, and efficient buffer management. Extensive performance comparisons with other protocols have been conducted to show the advantages of GeoMobCon.

Joint Routing and Spectrum Allocation for Multi-hop Inter-Vehicle Communication in Cognitive Radio Networks

In multi-hop inter-vehicle communications (MHIVC) for cognitive radio (CR), high mobility of vehicles causes the situation change of the primary user (PU) near the secondary user (SU) and changes a link distance in a short time. In this paper, in order to overcome these problems, we propose a joint routing and spectrum allocation utilizing the PU information (e.g., position, channel, and transmit power) and vehicle mobility information (e.g., position, direction, and speed) to predict the end-to-end delay time for sending required packets. By using PU information, we predict a period of SU’s available frequency according to SU’s mobility. By using SU’s mobility information, we predict the available transmission data rate of each frequency. The proposed joint routing and spectrum allocation is more likely to establish minimum delay time multi-hop paths for VANET. By using computer simulations, we confirm the effectiveness of the proposed method in terms of end-to-end delay time.

Mobility-Aware Coordinated Charging for Electric Vehicles in VANET-Enhanced Smart Grid

Coordinated charging can provide efficient charging plans for electric vehicles (EVs) to improve the overall energy utilization while preventing an electric power system from overloading. However, designing an efficient coordinated charging strategy to route mobile EVs to fast-charging stations for globally optimal energy utilization is very challenging. In this paper, we investigate a special smart grid with enhanced communication capabilities, i.e., a VANET-enhanced smart grid. It exploits vehicular ad-hoc networks (VANETs) to support real-time communications among road-side units (RSUs) and highly mobile EVs for collecting real-time vehicle mobility information or dispatching charging decisions. Then, we propose a mobility-aware coordinated charging strategy for EVs, which not only improves the overall energy utilization while avoiding power system overloading, but also addresses the range anxieties of individual EVs by reducing the average travel cost. Specifically, the mobility-incurred travel cost for an EV is considered in two aspects: 1) the travel distance from the current position of the EV to a charging station; and 2) the transmission delay for receiving a charging decision via VANETs. The optimal mobility-aware coordinated EV charging problem is formulated as a time-coupled mixed-integer linear programming problem. By solving this problem based on Lagrange duality and branch-and-bound-based outer approximation techniques, an efficient charging strategy is obtained. To evaluate the performance of the proposed strategy, a realistic suburban scenario is developed in VISSIM to track vehicle mobility through the generated simulation traces, based on which the travel cost of each EV can be accurately calculated. Extensive simulation results demonstrate that the proposed strategy considerably outperforms the traditional EV charging strategy without VANETs on the metrics of the overall energy utilization, the average EV travel cost, and the number of successfully charged EVs.