1.1 Background of the study.

The monitoring and control of vehicular traffic and pedestrians pose a major challenge to transport authorities around the world. The escalating number of vehicles in cities not only has a huge environmental impact, but also results in loss of lives on the road. This situation demands a comprehensive approach involving a system in which both the traffic controls for vehicles and pedestrians are coordinated so that road users are safe and traffic is smoothly flowing. Currently, pedestrian crossings pose a significant hazard in many countries, both in developed and developing countries due to the increase in the number of vehicles. Each year a staggering figure of 500,000 pedestrians are killed all over the world and in China alone from 2000-2004, half a million pedestrians were killed (Zhen Liu, Simulation of Pedestrians in Computer Animation in Proceedings of ICICIC (2) 2006. pp. 229~232.). 

The European Transport Safety Council (ETSC) claims that 15 to 30 percent of the transportation mode used is walking. According to a telephone survey conducted by the Royal Automobile Club of Spain in the year 2000, walking is highly recommended as part of a healthy lifestyle with no negative side effects. However, it has been the victim of badly controlled traffic, thus increasing the mortality rates of road users. In the large cities of Europe, especially in Spain, people walked to their destinations but this is being seen as dangerous as pedestrians are more vulnerable to road accidents than passengers and drivers of cars (European Transport Safety Council(ETSC), In a conventional traffic light controller, the traffic lights change at a constant cycle time which is clearly not the optimal solution. The system calculates the cycle time based on average traffic load and disregards the dynamic nature of the traffic load, which aggravates the problem of congestion.

Consequently, we see an urgent need to optimize traffic control algorithms to accommodate the increase in vehicles in urban traffic that experience long travel times due to inefficient traffic light controls and to improve pedestrian’s safety.

In this paper, we propose an optimal control of traffic lights using a genetic algorithm (GA), in a four-way, two-lane junction with a pedestrian crossing. The innovative design of the pedestrian crossing is also based on such algorithm, which includes pedestrians as one of the parameters. The specific genetic algorithm used in this work is a standard genetic algorithm. A Genetic Algorithm is an adaptive and efficient heuristics that is able to solve optimization problems. This is a stochastic search technique to look for optimal solution. Most genetic algorithms are used in research and science related works to look for optimal solutions. They usually run on powerful computers as genetic algorithms generally are resources taking in terms of CPU time and memory size. Some methods a genetic algorithm uses are selection, crossover and mutation inspired from evolution in the real nature. Genetic algorithm is introduced in the traffic control system to provide an intelligent green interval response based on dynamic traffic load inputs, thereby overcoming the inefficiencies of conventional traffic controllers. In this way, the challenges are resolved as the numbers of vehicles are read from sensors put at every lane in a four-way, two-lane junction and pedestrians are monitored at the road junction. 

The features inherent in genetic algorithm play a critical role in making them the best choice for practical applications, namely optimization, computer aided design, scheduling, economics and game theory. It is also selected because it does not require the presence of supervisor or observer.

 However, genetic algorithms, without prior training, continuously allow permanent renewal of decisions in generating solutions. Instead of trying to optimize a single solution, they work with a population of candidate solutions that are encoded as chromosomes. Within these chromosomes are separate genes that represent the independent variables for the problem at hand.

There are a number of specific attributes of genetic algorithms that give them an edge over other traditional optimization techniques. These are:

1. A genetic algorithm works from a population, not a single point, and hence it is likely to be trapped at a local optimum.

2. Derivative freeness, i.e., a genetic algorithm does not need the objective function’s derivative to do its work.

3. Flexibility, i.e., a genetic algorithm can function just fine regardless of how complex the objective function is; the only thing it requires of the function is that it is executable (i.e., its value can be calculated given the values of the decision variables).

4. Because of its implicit parallelism, a genetic algorithm can handle combinatorial problems efficiently. It has been shown that as the size of the search space or number of solutions increases exponentially, the time requirements for the genetic algorithm to reach a solution only grows linearly. This feature is particularly useful for on-line optimization of transportation problems such as traffic control.

5. A genetic algorithm naturally lends itself to parallel implementation. This follows from its functional components structure.

6. Genetic algorithm is, for the most part, based on intuitive notions and concepts.

The preliminary review of the literature indicates that genetic algorithm has not been tested on pedestrian crossings. This work has, therefore, attempted to implement this algorithm and study its effects on this problem.AyadMashaanTurky, MohdSharifuddin Ahmad and MohdZalimanMohdYusoff, Use of Genetic algorithm for Traffic Light and Pedestrian Crossing Control, (2009). pp.1-2.

From a recent analytical statistics of the Nigerian Ministry of Transportation 2010, it is estimated that roughly half of the congestion is what is known as recurring congestion, which is caused by recurring demands that exist virtually every day, where roads use exceeds existing capacity and bad roads. The other half is due to non-recurring congestion caused by temporary disruptions. Four main reasons of non-recurring congestion are: traffic incidents (ranging from disabled vehicles to major crashes), work zones, weather and special events. Expert systems with Application systems dramatically reduce available capacity and reliability of the entire transportation system. Therefore, researchers have carried out many researches to increase capacity and remove bottlenecks. Schaefer, Upchurch and Ashur (2008) developed a simulation model for evaluating freeway lane control signing. The simulation results show that the lane control has little influence on congestion. However, the region between heavy and medium traffic flow is sensitive to lane control. This is why the Genetic algorithm has been proposed to solve this major problem, because by making use of this algorithm, traffic quality can be improved and operation costs can be reduced.

1.2 Statement of the Problem

Port Harcourt and indeed Nigeria alongside other developing countries are facing serious traffic congestion problem due to rapid motorization and rapid population growth in their cities. Infrastructure development could not match the rapid motorization. As a result, serious congestion occurs almost at every intersection during peak hours mainly because of the inability of signal system to provide optimum flows, either due to the imbalance green time split or optimum band width for progressive flows. Thus this project work has come with the view of designing an expert system to check this difficulty in the urban and sub-urban metropolitan areas of our country.

1.3 Objectives of the Study

The aim of this project is to develop and design an effective traffic control system that can monitor and regulate traffic congestions within the road network in our cities. Aims include:

1. To design a traffic system that is not only time based but traffic based on highly packed junctions.

2. To design a traffic control system that will be available round-the-clock

3. To design a system that coordinates traffic flow using the appropriate programming language.

1.4 Significance of the Study

The uniqueness of the project is not only for clearing the traffic but it shares time slot equally between two sides of a junction. It is going to be a useful project for traffic police to prevent road accidents and promote safety on the road for road users. Since automotive technologies are gaining ground in modern day traffic-control systems and the number of vehicles and passengers is rapidly growing, traffic control systems are needed to ensure the safety of all parties involved which include, pedestrians who obediently wait for traffic signal to interrupt traffic so they can cross and drivers who also patiently wait for their turn to move.

1.5 Scope of Study

This work is essentially intended to design an efficient traffic control system to control traffic in the urban areas and industrial estates across the country. It looks at controlling traffic in a four-way, two lane junction.

1.6 Limitations of the Study

This study was limited by some factors which include:

1. Limited materials: due to some materials being inaccessible, I only had to work with the few I could get.

2. Technical issues: owing to the fact that my system’s battery had expired, I could only work on my project when there was power supply.

3. Time factor: because of the challenges mentioned above and others, the time given to finish my project work was not enough.

1.7 Definition of terms

It’s pertinent to highlight and define properly some important terms that are used in this work. They include:

Algorithm: a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer.

Congestion: the state of being overcrowded, especially with traffic or people.

Control: this is the action necessary to ensure that plans and objectives are being achieved. Control as applied to road traffics is the act of directing vehicles (motorists) and pedestrian traffic around a construction zone in order to be free from accidents and other road disruptions.

Genetic: of or relating to genes or origin.

Traffic: this is defined as the vehicles that are travelling in an area at a particular time.

Traffic light: which is also known as ‘stop light, traffic lamps, traffic signal, signal light, robot or semaphore’ is a signalling device which is positioned at road intersections, pedestrian crossings and other locations to control competing flows of traffic. Traffic lights alternate the right of way of road users by displaying lights of standard colours (red, amber and green) using a universal colour code.

Transportation: the action of transporting someone or something or the process of being transported.



The literature review was conducted to survey past work on traffic signal control.

2.0 Introduction

Traffic is a problem almost everyone has faced, especially in developed areas due to it being the main vein of transportation for most people. Traffic has caused accidents, tardiness, and general aggression. Many factors affect traffic patterns and traffic jams. The most potent and problematic factors have been identified as the general public's mindset, accidents, and the traffic flow system itself. The mindset of the public is that closely following the car in front and aggressive driving helps to mitigate the problem. This, in fact, is basically the opposite of how traffic will revert back to normal traffic flow. In that, if one were to leave a large amount of room in front of them and move at a constant speed, the traffic would change to a more standard pace. Accidents are a problem that caused many traffic slow-downs. Although they cause some of the worst traffic jams, accidents cannot truly be fought against on a large scale as they are caused by individuals. Lastly, the set-up of the traffic grid further compounds the problem. These ailments cannot be targeted on the highway as there is no constrictive element that slows cars other than the cars themselves. Therefore, this study aims to amend the traffic system, specifically the traffic lights. 

Traffic lights conduct the flow of traffic on many roads. Since they were originally conceptualized so long ago, they are out of date and in need of a new system. A highly promising algorithm resulted from the idea of genetic algorithms. Genetic algorithms are mathematical instructions that are fed a certain parameter and what is qualified as "good". The algorithm then, incrementally, finds the "best" algorithm. If the traffic lights were fixed, it would allow traffic to flow off the interstates and onto smaller roads; effectively dividing the traffic flow so that it would run more smoothly for all individuals. Thus, this study aimed towards creating a genetic algorithm that would dictate the scheduling of traffic lights to help traffic move more efficiently.Therefore, to more specifically pin point the problem, information was collected in respect to how the traffic lights operated, different hypotheses of traffic patterns, and these all tie together. Since some causes of traffic are now known, it can be determined that it’s the interaction of the scheduling, and thus the devices, and of the individuals that causes the problems of traffic to occur. 

Many individuals implement the practice of tailgating in which they follow the car in front of them very closely, leaving little room between the two. As more and more cars commit this, the effect is amplified until it reaches the back of the traffic. One comparison to how traffic works is the slinky image in which the whole of traffic is a giant slinky. The slinky constricts and relaxes at different points, the constricted parts symbolizing high traffic concentrations whereas the relaxed portions represent the freely flowing traffic. The largest portion of the project lies within the code that functions behind the scenes. It is wholly based upon the genetic algorithm. This specific algorithm is based upon meiosis and the rules that dictate the transition of genes. These rules allow the genetic algorithm to become "better" after each "generation" is created. Thus, after executing the script many times, the algorithm's fitness increases by a large margin. Therefore, it is very important to fully understand the background information on this subject since it is so fundamental to this project. This project also has a large portion vested in traffic lights. Traffic lights are scheduling devices used to dictate traffic flow through intersections. Therefore, it is necessary for this study to understand the inner workings of how traffic lights function.

 Additionally, it is also important to better comprehend scheduling in computing in general. Traffic lights are usually set by a timer or by some sort of mechanism (weight or magnetic) underground that indicates when cars are near. 

These resources allow the study to obtain more specific information in relation to traffic lights, the operation of traffic lights, and how they operate mechanically.

Lastly, it is important for this study to better understand how traffic occurs and why it develops. This allows the study to create a better algorithm program because the program is dependent upon traffic and how it flows. Thus, resources dealing with traffic are crucial to the project as well.



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