Maram Bani Younes

Intelligent Traffic Light Controlling Algorithms Using Vehicular Networks

In this paper, we propose an intelligent traffic light controlling (ITLC) algorithm. ITLC is intended to schedule the phases of each isolated traffic light efficiently. This algorithm considers the real-time traffic characteristics of the competing traffic flows at the signalized road intersection. Moreover, we have adopted the ITLC algorithm to design a traffic scheduling algorithm for an arterial street scenario; we have thus proposed an arterial traffic light (ATL) controlling algorithm. In the ATL controlling algorithm, the intelligent traffic lights installed at each road intersection coordinate with each other to generate an efficient traffic schedule for the entire road network. We report on the performance of ITLC and ATL algorithms for several scenarios using NS-2. From the experimental results, we infer that the ITLC algorithm reduces, at each isolated traffic light, the queuing delay and increases the traffic fluency by 30% compared with the online algorithm (OAF) traffic light scheduling algorithm. The latter algorithm achieved the best performance when compared with the OAF traffic light scheduling algorithm. On the other hand, the ATL controlling algorithm increases the traffic fluency of traveling vehicles at arterial street coordinations by 70% more than the random and separate traffic light scheduling system. Furthermore, compared with the previously introduced traffic scheduling ART-SYS, the ATL controlling algorithm decreases the average delay at each traffic light by 10%.

A performance evaluation of an efficient traffic congestion detection protocol (ECODE) for intelligent transportation systems

In this paper, we present an Efficient COngestion DEtection (ECODE) protocol that aims at evaluating the traffic characteristics of each road segment (i.e., the road section connecting between any two successive intersections). Moreover, ECODE efficiently and reliably detects road segments with high traffic congestion in any urban grid-layout area. The traffic situation and the congestion level of each road segment changes from time to time. Proactive, reactive, and hybrid iterative execution schemes have been proposed to execute ECODE repeatedly and to thus obtain a more real-time traffic evaluation of each road segment. These iterative execution schemes aim also at investigating the effects of several data dissemination mechanisms that are usually used to control the congestion over the communication network. ECODE is discussed and its performance is reported on and compared to previous protocols in this field; an extensive set of scenarios and experiments have been used which are in turn implemented by NS-2. From the experimental results, ECODE achieves a 30% more accurate evaluation of traffic characteristics compared to previous protocols in this field. Moreover, it consumes on average 60% of the bandwidth that was consumed by the previous protocols. Considering the iterative execution schemes of ECODE, the proactive scheme consumes 50% more bandwidth than the reactive scheme. However, the accuracy of the traffic evaluation per road segment using the reactive scheme is lower than the accuracy of the proactive scheme used for short intervals. The hybrid scheme lies between the proactive and the reactive schemes in terms of the bandwidth consumption and the accuracy of congestion level evaluation. Finally, we have used ECODE to evaluate the traffic congestion level and to investigate the traffic distribution over some main streets in the downtown area of Ottawa; this has been set up as a practical example of the application of ECODE.

An Intelligent Traffic Light scheduling algorithm through VANETs

Traffic signals are essential to guarantee safe driving at road intersections. However, they disturb and reduce the traffic fluency due to the queue delay at each traffic flow. In this work, we introduce an Intelligent Traffic Light Controlling (ITLC) algorithm. This algorithm considers the real-time traffic characteristics of each traffic flow that intends to cross the road intersection of interest, whilst scheduling the time phases of each traffic light. The introduced algorithm aims at increasing the traffic fluency by decreasing the waiting time of traveling vehicles at the signalized road intersections. Moreover, it aims to increase the number of vehicles crossing the road intersection per second. We report on the performance of ITLC and we compare ITLC to previous algorithms in this field for different simulated scenarios. From the experimental results, we infer that ITLC reduces the queuing delay and increases the traffic fluency by 25% compared to previous traffic light signal schedules. Furthermore, ITLC increases the throughput of each signalized road intersection by 30%.

An intelligent path recommendation protocol (ICOD) for VANETs

This work introduces a novel, intelligent, real-time, distributed, and flexible path recommendation protocol. We refer to the introduced protocol as an Intelligent path recommendation protocol (ICOD). This protocol aims to find the best path towards each destination in any grid-based layout area. The path is reactively reconfigured at each road intersection; this is based on the real-time traffic status of the Surrounding Road Segments (SRSs) of that intersection: i.e., any road segment that starts or ends with the road intersection. In order to handle the centralized behavior problems (i.e., bottleneck, single point of failure, etc.) which appeared in the previous path recommendation protocols, ICOD has constructed the path towards each destination in a distributed manner. Three different variants of ICOD are thus introduced to enable flexible selection of the best path towards each destination according to the following driver concerns and priorities: congestion avoidance, economical and context-aware. The congestion avoidance variant aims to reduce the traffic congestion, by recommending each vehicle to take the least congested path towards its destination. The economical variant recommends the best economical path in terms of fuel consumption and gas emission parameters of each candidate path. Finally, the context-aware variant considers the context of each traveled road segment while selecting the desired path. Thus, the located services and the road conditions are considered. We report on the performance of these different variants of ICOD and compare them with previous path recommendation protocols, using an extensive set of scenarios and experiments implemented by NS-2. From these experimental results, ICOD is shown to exhibit a good performance in terms of its ability to recommend the best path which decreases the delay of each vehicle by 50% in the process of obtaining the directions towards its destination; it also eliminates the bottleneck and single point of failure problems.

A distributed infrastructure-based congestion avoidance protocol for Vehicular Ad Hoc Networks

In order to detect and reduce the congestion level in downtown areas, many research works and projects have been proposed. The previous works have been based on the information gathered at a central database to recommend the best path for vehicles, which introduces a bottleneck problem as well as a single point-of-failure. In this work we propose a dynamic and real time protocol that intends to find the fastest path towards each destination in a distributed fashion, without the need for a centralized database. The proposed protocol recommends paths that will allow vehicles to avoid highly congested road segments towards a certain destination. Moreover, this protocol can alleviate the drastic increase in congestion scenarios by distributing the traffic load over the downtown grid road segments without adversely affecting the traveling time of vehicles. In this paper, we discuss our protocol in details, compare it to other path recommendation protocols and report on its performance evaluation an extensive set of scenarios and experiments implemented on the NS-2 simulator. From the results, we can conclude that our protocol provides better performance in terms of vehicular traveling time towards each destination, without the need for a central database.

SCOOL: A secure traffic congestion control protocol for VANETs

Traffic efficiency applications are becoming increasingly popular over the road networks in the last few years. This type of applications aims mainly at increasing the traffic fluency over the road network, which minimizes the travel time of each vehicle towards its targeted destinations. The Vehicular Ad-Hoc Networks (VANETs) technology has been utilized to design these applications. Communications between vehicles, V2V, and between vehicles and installed Road Side Units (RSUs), V2I, helped designing these applications. Malicious, selfish and intruder drivers can take advantages of other cooperative drivers and use their trust. This paper introduces a Secure COngestion contrOL (SCOOL) protocol. This protocol aims to guarantee integrity and authenticity of transmitted data. It is designed to provide the security requirements of traffic efficiency protocols that have been proposed using the technology of VANETs. SCOOL also aims to preserve the privacy of the cooperative vehicles and drivers. From the experimental results we can infer that SCOOL detects the malicious nodes over the road network which enhances the correctness of the traffic efficiency applications.

Time-distance path recommendation mechanisms for vanets

In most of modern cities and urban areas, roads have been constructed following Manhattan layout. The grid layout of Manhattan introduces many different paths that could be followed towards each vehicles targeted destination. Different from other works that consider a centralized server, this paper aims at introducing three distributed and real-time path recommendation mechanisms for VANETs. The introduced mechanisms aim to find the fastest path towards each destination without significantly increasing the vehicles traveling distance.

A performance evaluation of a context-aware path recommendation protocol for Vehicular Ad-hoc Networks

Many protocols and mechanisms have been proposed aiming to find an alternative path towards each targeted destination in downtown and urban areas. These protocols recommend the fastest path (i.e., least congested path) without considering the services or conditions of the recommended road segments. In this work, we propose a real-time, distributed, and context-aware path recommendation protocol. The proposed protocol considers the existence of special services at alternative road segments and guarantees a congestion-free level for each road segment that is located at a critical service (e.g., hospital, school, etc). Moreover, it considers the conditions of each traveled road segment (e.g., pot-holes, weather conditions, obstacles, etc), while recommending the path towards any targeted destination. We discuss and report on the performance of our protocol compared to other path recommendation and traffic congestion avoidance techniques, using an extensive set of scenarios and experiments implemented in NS-2.

A traffic balanced mechanism for path recommendations in vehicular ad-hoc networks

In this paper, we investigate the bottleneck traffic problems that are caused and/or amplified by path recommendation protocols in use. Distributed path recommendation protocols construct the path towards each destination in a hop-by-hop fashion. In some scenarios most of traveling vehicles, arriving the road intersection from several input road segments, are recommended to leave at the same output road segment. This is due to the fact that traveling vehicles are heading towards the same destination or close located destinations. Then, the paper introduces a traffic balancing mechanism (Bal-Traf) that eliminates the traffic congestion over road networks. At each road intersection, Bal-Traf distributes the input traffic among the output road segments towards the targeted destinations. From the experimental results we can see Bal-Traf completely eliminates the bottleneck problem over the road network.

Context-aware traffic light self-scheduling algorithm for intelligent transportation systems

Traffic lights are located on the road intersections to control and manage the competing traffic flows. Several algorithms have been proposed considering the real-time traffic characteristics of each competing traffic flow at the road intersection. Emergency vehicles such as ambulance, fire truck and police vans should have higher priorities to cross any road intersection first. Whenever an emergency vehicle appears close to any road intersection, all vehicles on the competing flows should stop and allow that vehicle to proceed first. However, this may cause a hazards situation in the case that any driver miss-behaves or insists to follow the current traffic light phase. In this paper, we aim at designing a context-aware traffic light self-scheduling (CA-TLS) algorithm. This algorithm uses the traffic characteristics of the traffic flows and the emergency vehicles presence on the competing flows at any signalized road intersection. First, these parameters are gathered using periodic advertisement messages of traveling vehicles. Then, the CA-TLS algorithm sets the phases of each traffic light cycle according to the traffic gathered data. The green phase of any traffic flow can be interrupted to enable the fast proceeding of the appeared emergency vehicles. An extensive set of experiments have shown that this algorithm decreases the delay time of emergency vehicles at the signalized road intersections.