Ali Jalooli

Ant-based vehicle congestion avoidance system using vehicular networks

Vehicle traffic congestion leads to air pollution, driver frustration, and costs billions of dollars annually in fuel consumption. Finding a proper solution to vehicle congestion is a considerable challenge due to the dynamic and unpredictable nature of the network topology of vehicular environments, especially in urban areas. Instead of using static algorithms, e.g. Dijkstra and A*, we present a bio-inspired algorithm, food search behavior of ants, which is a promising way of solving traffic congestion in vehicular networks. We have called this the ant-based vehicle congestion avoidance system (AVCAS). AVCAS combines the average travel speed prediction of traffic on roads with map segmentation to reduce congestion as much as possible by finding the least congested shortest paths in order to avoid congestion instead of recovering from it. AVCAS collects real-time traffic data from vehicles and road side units to predict the average travel speed of roads traffic. It utilizes this information to perform an ant-based algorithm on a segmented map resulting in avoidance of congestion. Simulation results conducted on various vehicle densities show that the proposed system outperforms the existing systems in terms of average travel time, which decreased by an average of 11.5%, and average travel speed which increased by an average of 13%. In addition, AVCAS handles accident conditions in a more efficient way and decreases congestion by using alternative paths.

A Dynamic Vehicular Traffic Control Using Ant Colony and Traffic Light Optimization

Vehicle traffic congestion problem in urban areas due to increased number of vehicles has received increased attention from industries and universities researchers. This problem not also affects the human life in economic matters such as time and fuel consumption, but also affects it in health issues by increasing CO2 and greenhouse gases emissions. In this paper, a novel cellular ant-based algorithm combined with intelligent traffic lights based on streets traffic load condition has been proposed. In the proposed method road network will be divided into different cells and each vehicle will guide through the less traffic path to its destination using Ant Colony Optimization (ACO) in each cell. Moreover, a new method for traffic lights optimization is proposed in order to mitigate the traffic congestion at intersections. Two different scenarios have been performed through NS2 in order to evaluate our traffic lights optimization method. Based on obtained results, vehicles average speed, their waiting time and number of stopped vehicles at intersections are improved using our method instead of using usual traffic lights.

Intelligent Advisory Speed Limit Dedication in Highway Using VANET

Variable speed limits (VSLs) as a mean for enhancing road traffic safety are studied for decades to modify the speed limit based on the prevailing road circumstances. In this study the pros and cons of VSL systems and their effects on traffic controlling efficiency are summarized. Despite the potential effectiveness of utilizing VSLs, we have witnessed that the effectiveness of this system is impacted by factors such as VSL control strategy used and the level of driver compliance. Hence, the proposed approach called Intelligent Advisory Speed Limit Dedication (IASLD) as the novel VSL control strategy which considers the driver compliance aims to improve the traffic flow and occupancy of vehicles in addition to amelioration of vehicles travel times. The IASLD provides the advisory speed limit for each vehicle exclusively based on the vehicles characteristics including the vehicle type, size, and safety capabilities as well as traffic and weather conditions. The proposed approach takes advantage of vehicular ad hoc network (VANET) to accelerate its performance, in the way that simulation results demonstrate the reduction of incident detection time up to 31.2% in comparison with traditional VSL strategy. The simulation results similarly indicate the improvement of traffic flow efficiency, occupancy, and travel time in different conditions.

Performance analysis of V2V dynamic anchor position-based routing protocols

Recently, vehicular ad hoc networks (VANETs) have received more attention in both academic and industry settings. One of the challenging issues in this domain is routing protocols. VANETs’ unique characteristics such as high mobility with the constraint of road topology, fast network topology changes, frequently disconnected networks, and time-sensitive data exchange makes it difficult to design an efficient routing protocol for routing data in vehicle-to-vehicle (V2V) and vehicle-to-infrastructure communications. Designing routing protocols for V2V commutations are more challenging due to the absence of infrastructure nodes in the communication procedure. They become even more challenging, when they get benefit from dynamic anchor computation method in which the anchor nodes (junctions or basic nodes for routing) are dynamic in their routing procedure. Position-based routing protocols have been proven to be superior and outperform the other protocols since there is no requirement to establish and save a route between source and destination during the routing process which is suitable for dynamic nature of vehicular networks. In this paper, the performance of V2V dynamic anchor position-based routing protocols, which are proposed for the most challenging condition of packet routing in VANET, are investigated and evaluated under two different scenarios (i.e. various vehicle densities and velocities) through NS-2. The obtained results are then illustrated based on average delay, packet delivery ratio and routing overhead as routing performance indicators. Our objective is to provide a quantitative assessment of the applicability of these protocols in different vehicular scenarios. The comparison provided in this paper makes the research contribution of this survey paper quite higher than a regular survey paper only with explanations.

Quality of service management for IPTV services support in VANETs: a performance evaluation study

In order to deliver a qualitative Internet Protocol Television (IPTV) service over vehicular ad hoc networks (VANETs), a quality of service (QoS) mechanism is needed to manage the allocate of network resources to the diverse IPTV application traffic demands. Unlike other mobile network, VANETs have certain unique characteristic that presents several difficulties in providing an effective QoS. Similarly, IPTV requires a constant stream for QoS which at the moment is quite difficult due to the inherent VANET characteristics. To provide an effective QoS that will meet the IPTV application service demands, VANETs, must satisfy the compelling real-time traffic streaming QoS requirement (i.e., minimum bandwidth allocation, packet loss and jitter). In this report, we evaluate via simulation the feasibility of deploying quality IPTV services over VANETs, by characterizing the association between the IPTV streaming quality determining factors (i.e., throughput, delay, loss, jitter) and the IPTV quality degradation, with respect to node density and node velocity. Furthermore, we used an objective QoS metric (Media-Delivery-Index) to identify, locate and address the loss or out-of-order packet. We outline how, using these information’s can support in shaping network parameters to optimize service flows. The implementation assures a priority for handling IPTV traffic, such that maximise the usage of VANETs resources, and opens the possibility that loss and delay can be minimised to a degree that could guarantee quality IPTV service delivery among vehicle in a vehicular network system.

Public Alerts on Landslide Natural Disaster Using Vehicular Communications

Landslide is a serious geological disaster that has severe impact on road safety, traffic flow efficiency, and environment preservation. It is important to develop a landslide warning system to recognize the sharpness of the landslide. However, there are several problems (e.g., the quality of the collected sensor data) to reduce the performance of the system (e.g., false alarms). Thereby, this study aims to design a landslide detection technique based on (i) motion detection and (ii) cross movement methods. They are applied in a detection phase, in order to identify the degree of landslide influence on road capacity by considering vehicles dimensions. Roadway landslide information dissemination (RLID) detects the landslide based on several image processing techniques, and determines the current condition by considering landslide level of road safety. As a result, landslide information can be disseminated to vehicles encountering the target area by using infrastructure-to-vehicle (I2V) and vehicle-to-vehicle (V2V) communications, in order to reduce crash likelihood and to increase traffic flow efficiency. Experimental results have shown that the proposed method in the detection phase can identify the degree of landslide influence on road capacity and monitor the level of effect on road safety.

Opportunistic XOR-coding content propagation in VANET

  Abstract— The main difference between typical wireless networks and Vehicular Ad-hoc Networks is mostly about the way traffic is propagated in these types of networks. Unlike conventional wireless networks in VANET connections are established quick and short. Because of these two factors connections in VANET are not as reliable and robust as typical wireless networks. Hence Due to these limitations in VANET and also in order to achieve higher throughput, we are aimed at investigating the adoption of network coding with the existing data propagation and routing methods in Vehicular networks. In order to address the disadvantages, we present an approach called Opportunistic Network Coding-aware Data Dissemination in Wireless Networks (NCODWN). This approach is an enhanced version of COAR. We have managed to improve network throughput and decrease end-to-end delay of the network by implementing a more efficient and reliable mechanism. The simulation results indicate that our approach outperforms COAR in terms of end-to-end delay, percentage of encoded packets, packet delivery and network throughput.