Tunnels and bridges are installed as efficient context over the road network. Adding extra layers to an existing road network reduces the traffic congestion on that road. This is due to the distribution of traffic among the layers. However, bottleneck problems may appear at the entrance or exit points due to some driving behaviors. Moreover, the several exit points around these road contexts usually lead toward different trajectories. Taking a wrong exit leads to drastically expanding the trip traveling time, the fuel consumption, and the gas emission of any vehicle. This work aims to introduce an efficient driving assistance protocol that recommends drivers' optimal speed and behavior around tunnels and bridges. This mainly reduces the bottleneck constructions and enhances the movement's smooth-ness. Moreover, it accurately recommends the exit point there for each driver toward his/her targeted destination. The experimental study shows that the proposed protocol reduces the percentage of bottlenecks around the tackled road context. It also reduces vehicles' traveling time and distance during their trips toward the targeted destinations compared to the scenario of the absence of this protocol.

Fuel consumption and gas emissions of traveling vehicles have become of great consideration for green environmental researchers. Several technologies have been developed to enhance the efficiency of daily traveling vehicles in terms of fuel consumption. Moreover, many protocols have been developed to reduce the fuel consumption and emissions of traveling vehicles. However, most of these protocols were dedicated to downtown and urban areas, since they are considered more consuming scenarios. Drivers spend a long time traveling over highways toward a targeted destination. Small mistakes could lead to greater fuel consumption; the percentage of extra fuel consumption can be drastically increased when drivers repeatedly make the same efficiency mistakes during their trips. In this work, we aim to introduce a green protocol to assist drivers and self-driving vehicles to drive efficiently over highways in order to reduce the fuel economy and gas emission of their vehicles. This protocol is designed to keep the speed of the traveling gasoline vehicles steady as much as possible in order to save energy and enhance efficiency. It also smooths the acceleration and deceleration reactions of vehicles when required. The performance of the proposed protocol has been evaluated using an extensive set of experiments.

Traffic distribution over highways affects several applications and functionalities of traveling vehicles. The level of traffic congestion has been scaled over road networks based on the traffic density, traveling speed or estimated traveling time of the investigated road scenario. These measurements have been used individually or combined with other parameters to indicate the level of the traffic congestion on certain road scenario. In this paper, we propose a context-aware traffic prediction technique. It predicts the context of the highway scenarios in terms of the existence of obstacles, broken vehicles, or entrance/exit points based on the distribution of vehicles’ traveling speed. From the experimental study, we can see that the proposed protocol have succeeded to predict the context of the highway. Our results indicate that our propose scheme exhibit good performance based upon an extensive set of simulation experiments.

Stop signs are located at road intersections, school buses and besides pedestrians crosswalks. Drivers should obey a full halt that their vehicles have no momentum for a certain period of time infront of these signs. However, this requires early notification for drivers to start the safe and smooth stop at adequate time and distance. In some scenarios drivers miss to see these stop signs early enough to respond properly. This is due to some obstacles, road design and/or bad weather conditions. Moreover, the optimal time and distance of each vehicle to start reducing its speed aiming to stop depends on that vehicle's type and its traveling speed, the road design and weather conditions. Thus, drivers may face some difficulties in many scenarios to stop their vehicles smoothly. In this paper, we propose a driving assistance protocol that early detects the existed stop signs in the surrounding road network. It also notifies each vehicle regarding the time, location and deceleration rate where it should start reducing its speed to park smoothly in front of the next stop sign. The proposed protocol uses the technology of the vehicular network to gather the real-time conditions of each scenario. It proves a good performance in terms of enhancing the safety of vehicles around stop signs.

Freeways have been known over decades as high-speed multi-lane roads, where the opposite traffic directions are completely separated. No intersections, pedestrians, or bicycles are expected on these road scenarios, besides specific ramps are designed to facilitate the entrance and exit of vehicles. Although freeway driving is considered safer and faster for experienced drivers, it can be more demanding and difficult for fresh or exhausted ones. Entering and existing the freeway road are considered the most critical situations where the driver needs to achieve high synchronizations with the surrounding traffic there. In this work, we introduce a freeway driving assistance protocol for drivers aiming to reduce the difficulties for fresh drivers and enhance the safety and efficiency conditions over the freeway road scenarios. This proposed protocol can also be used by the autonomous vehicles where no drivers control the vehicle. We evaluate the performance of the proposed protocol using several simulated driving scenarios. It shows a good performance in terms of increasing the safety of traffic and smoothing the traffic speed of vehicles.

Roundabouts or traffic cycles reduce the possibilities of accidents and smooth the traffic at road intersections. In order to master the rules of driving around these traffic cycles intensive practicing is required. The more congested the area of the roundabout, the more confused for drivers to drive there. Especially, fresh or exhausted drivers which panic or/and do mistakes while entering, cycling or existing the roundabout. In this work, we aim to introduce a driving assistance protocol to help drivers choosing the best lane to enter the roundabout and the best time to enter or exist the roundabout. The proposed protocol recommends the best reaction of any vehicle regarding the roundabout based on its location, its targeted destination, and the distribution of traffic in the vicinity of the roundabout. Using some experimental scenarios, we evaluate the performance of this protocol in terms of decreasing the percentage of accidents, increasing throughput of the roundabout and decreasing the waiting delay time of vehicles.

Long driving trips that traverse several states or counties are common these days, for tourism or products shipping aims. These trips are usually classified as dangerous trips due to the challenges and difficulties they introduce. The diversity of geometry and quality of road networks over the extended traveling areas, the diversity of weather conditions, and the long time of the day that drivers witness during these driving hours make even expert drivers in need for professional advices. In this work, we propose a driver assistance protocol that uses the real-time critical conditions of each driving area to recommend the safety speed. Moreover, this protocol measures the speed of each traveling vehicle and compares it to the recommended speed aiming to determine the severity of the dangerous situation introduced by drivers that are not following the safety recommendations. Severe scenarios should be reported to surrounding vehicles to be more careful regarding this irresponsible driver and/or reported to the driving authorities to enforce the driver to follow the driving safety rules.

Drivers change the lane over the road networks is a common seen practice when they face a slow, stopped or broken vehicle. Sometimes they have to change the lane to take the next exist or the next U-turn towards their targeted destination. Changing the lane requires that the driver should be aware of vehicles behind him on the new lane or vehicles intending to change to the same lane during that period of time. If any of these vehicles are located on the blind-spot or if the driver miss-expect that vehicle's location or speed, his attempt of changing the lane can be failed or on some scenarios this may lead to an accident. On highways this type of accident can be fatal due to the high speed vehicles which do not allow drivers to stop the severity situation. This paper presents an Intelligent LAne CHange assistant protocol (ILACH) for highway road scenario. This protocol assists drivers to change the lane safely and efficiently. Several scenarios are considered where a certain driver attempts to change the lane. From the experimental results we can see that the proposed protocol enhances the safety and the efficiency of the tested scenarios.

Vehicular Ad-hoc Networks (VANETs) technology has been utilized in recent applications to enhance the traffic fluency over the road network. Various types of emergency cases may negatively affect the efficiency of traffic flow in highway road scenarios, including accidents, damaged vehicles or the presence of emergency vehicles. These cases exaggerate the traffic problems in severe congestion scenarios. In this paper, we propose a traffic efficiency protocol which first aims to detect emergency cases over highway road scenarios. Then, it recommends the most appropriate response for each vehicle affected by the detected emergency case. The best response for each vehicle is determined based on the vehicle's location and speed. Our protocol also considers overall traffic conditions over the investigated road scenario. From the experimental results, we can prove that our proposed protocol has increased traffic fluency in the vicinity of emergency cases over highway road scenarios. Moreover, it has increased safety conditions for vehicles in such scenarios.

Delay-tolerant sensor networks (DTSNs) require efficient MAC transmission strategies that include energy constraint, relaxed latency, mobility support and diverse traffic load. Reservation-based and contention-based MAC schemes are used to improve throughput and energy consumption. In this paper, we propose a traffic adaptive, energy-efficient MAC protocol to achieve better data transmissions and as energy consumption, in order to satisfy the requirements in DTSN. In our protocol, reservation and contention modes are adjustable, in order to adapt to the traffic load with a suitable duty cycle length for achieving energy efficiency. The simulation results of our protocol demonstrate better performance in terms of energy efficiency and traffic adaptability than the schedule-based MAC protocol TDMA, the contention-based protocol CSMA, and the traffic adaptive protocol TRAMA under mobile DTSN environments.

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.

In this paper, we propose both reactive and proactive balancing traffic path recommendation mechanisms, which we refer to as Bal-Traf and Abs-Bal, respectively. Bal-Traf is initiated when a certain output road segment located at any road intersection is detected in an overloaded situation. In the event that the existing traffic density of any output road exceeds its optimal capacity, Bal-Traf recommends that those vehicles that plan to pass over this road segment as next hop choose another, less congested output road segment. On the other hand, Abs-Bal is a proactive balancing traffic mechanism. Its main purpose is to distribute input traffic completely even among all output road segments at intersections. Moreover, Abs-Bal considers the best travel time of vehicles in addition to the goal of balancing traffic. From the experimental results, we can see that Bal-Traf eliminates the number of overwhelmed road segments over the road network in scenarios with only partial network congestion. It also decreases the number of congested road segments in scenarios with complete network congestion. However, it increases the density drastically over the remaining congested road segments in these scenarios. Abs-Bal performs well in decreasing the percentage of congested road segments and balancing traffic among road segments located throughout the road network, in the event of complete network congestion.

Several research studies have introduced an efficient and intelligent path recommendation protocols for vehicular networks. Communications among traveling vehicles and located roadside units (RSUs) have been utilized to investigate the traffic distribution over the road network. This helps construct the optimal path towards each targeted destination located on the road network. However, none of the previous proposed protocols in this field have specifically considered potential faults among the nodes of the vehicular networks or potential link failures. In this paper, we present a fault tolerant distributed-based path recommendation (TD-PR) protocol. Our protocol detects and tolerates faults occur among nodes and/or communication links. We present TD-PR protocol in this paper and report on its performance evaluation. Our simulation experiments show that TD-PR improves the success rate significantly over our previously proposed path recommendation protocol (ICOD). The success ratio is improved in roadside failure and link failure scenarios. In general TD-PR has better performance in terms of decreasing the traveling time and traveling distance compared to ICOD in these scenarios.

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.

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.

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.

In large and highly populated downtown areas, traffic congestion is becoming a challenging problem. This work proposes an Efficient road COngestion DEtection protocol (ECODE). This protocol intends to detect road segments that are suffering high traffic congestion using cooperative vehicular communication. It uses multi-hop communication and geocast principles to gather and analyze vehicles' basic data per road segment. Each vehicle can evaluate and report its road segment's congestion level per direction efficiently. This protocol is discussed and reported on its performance compared to previous techniques in this field, using an extensive set of scenarios and experiments implemented on NS-2.

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.