System Design
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TrafficMonitoring_AnalysisUpdated.docxIntelligent Traffic Monitoring System
Abstract Traffic congestion in cities is a major problem mainly in developing countries; to encounter this, many models of traffic system have been proposed by different scholars. Different ways have been proposed to make the traffic system smarter, reliable, and robust. This paper presents the various approaches made to enhance the traffic system across the globe. A comparative study has been made of different potential researches in which intelligent traffic system (ITS) emerges as an important application area. Important key points of each research are highlighted and judged on the basis of implementing them in developing countries like India. A model is also proposed which uses infrared proximity sensors and a centrally placed microcontroller and uses vehicular length along a length to implement intelligent traffic monitoring system.
Keywords Infrared proximity sensors · RF module · Bluetooth module · ITS
1. Introduction
The traffic jam is a daily-life problem in any metropolitan city. With the rise of standard of living, the number of vehicles is increasing at an exponential rate. In response to this, many researches are done in developing an intelligent traffic system (ITS), i.e., a traffic system which is involved in a much closer interaction with all the components of a traffic including vehicles, drivers, and even pedestrian. It not only provides safety at intersections and prevents traffic jam, but manages the traffic as a whole. Developed countries like America, Japan, and U.K. have already implemented ITS on their roads and still many researches are going on to make traffic systems more advanced and suitable for developing countries also. Apart from surveying various research works on ITS, this paper proposes a model which follows a simple algorithm based on the length of traffic on each lane. The length of traffic on the other lanes affects the time allotted to the current lane. Proximity sensors instead of WAN are to be used to determine the length of the traffic. The proposed idea can reduce the traffic in all lanes proportionately reducing the chances of congestion without the use of WANs. Besides, it also manages the occurrence of any emergency vehicles such as ambulance, fire brigade, etc. in any lane and also provides the mechanism to detect the route of a vehicle. Once implemented, it does not require any human assistance for its working.
2. Classification of ITS
ITS is being researched and implemented through various means such as the use of wireless sensor networks, RFID, applying various concepts of graph theory to find the minimized path and many other. Here, the concept of ITS has been classified into two broad domains, namely, (I) real-time system and (II) data analysis system.
Real-time systems have been further diversified into two fields:
I. Path optimization and II. Traffic density. The data analysis systems are also divided into two parts:
i. Green light optimization, ii. Information chaining systems.
2.1. Real-Time Systems
Real-time systems in case of traffic managing system take the input of the current situation through video surveillance or WSNs and deal with the situation. The traffic signals are controlled according to the presence of vehicles and are operated
Intelligent Traffic Monitoring System
automatically in real time. A real-time optimization model was used by Dotolie .that investigated the issue of traffic control in urban areas. The model took into considerations the traffic scenarios which also include pedestrians. This tech- nique was applied for analyzing real case studies. Wenjie et al. concentrate on calculating the time that a vehicle requires to reach the intersection from a particular point, dynamically, by the use of sensors. By this, data performs various calcula- tions to find the green light length. Albers et al. used real-time data to monitor current traffic flows in a junction so that the traffic could be controlled in a con- venient way. Reliable short-term forecasting video captured in a recorder plays an important role in monitoring the traffic management system. The data required can be easily provided by the CCTV cameras that can be beside the roads as per requirement. Van Daniker visualized the use of transportation incident man- agement explorer (TIME) for calculating real-time data. Challal et al. proposed a distributed wireless network of vehicular sensors to get a view of the actual scenario and used its various sectors to lower the congestion but not taking decisions in real time. The use of two types of sensor network was proposed, vehicular sensor network and wireless sensor network, and the combination of these two permits the monitoring as well as managing of the traffic. Chandak used video sur- veillance for realizing the real-time scenario. It deals with decreasing response time of the emergency cars by establishing communication between emergency cars and traffic lights. The data collected in real time can be used to determine the traffic density and also based on the traffic present. Several path optimization techniques can be used, which are discussed in the next two sections.
2.1.1. Traffic Density
Realization of the traffic density at a selected intersection for a given time also can facilitate in reducing traffic congestion at that time. This information are often analyzed to work out many factors like inexperienced lightweight length, traffic at the actual time, etc.
Zhou used the idea of adaptive adaptive lightweight management algorithmic program that manipulates each the sequence and length of traffic lights in accordance with the detected traffic.
The algorithmic program uses period information just like the waiting time of vehicles, volume of traffic in every lane, etc.to work out to work out sequence and best length of inexperienced lightweight.
The algorithmic program produces lower vehicle’s average waiting time, so providing abundant higher turnout.
The system projected by Sinhmar used IR sensors to work out the density of traffic supported that the traffic signals were updated to produce a swish flow of vehicles.
Hussain projected a system that uses a central microcontroller at each junction that receives information wireless sensing element placed on the road that determines the traffic density.
The microcontroller uses this information to regulate to regulate mistreatment the programed algorithmic program to manage the traffic in Associate in Nursing Associate in Nursing manner.
Srivastava prompt ways in which to work out the number of vehicles mistreatment weight sensors, then with the utilization of a programmable logic controller to research the information, so park in automatic parking or has diverge them consequently
.
2.1.2. Path Optimization Technique
Finding the simplest and shortest path to destination are often used as a tool to reduce to reduce on a path.
The traffic on the road are often sent to the incoming vehicle proving them the concept regarding the traffic and so they will take another path to the destination.
Gambardella Associate in Nursing Bertelle projected to find an optimized path for transportation victimization the idea of pismire colony improvement.
Once Associate in nursing optimized path is found, we are able to add many alternative options to form it a lot of convenient and avoid traffic jams.
Ozkurt have projected the utilization of video police investigation and neural network to cut back to cut back stress across the network. Xia researched to find Associate in Nursing best road network and analyse the traffic dynamics by the movement of every automotive and therefore the applied math property of the full network. Designed a system that uses the traffic info and sends it to the incoming automobile by permitting it take manner consistent with the case. The varied performance analysis criteria area unit used like average waiting time, the typical distance travelled by vehicles, and change frequency of inexperienced light-weight at a junction
.
2.2. Data Analysis Systems
Data analytical systems area unit those systems that take this or applied mathematics information, method them within the processor, and so act in line with in line with. Like time period systems, it should collect information in real time, however is unable to require any call in real time, i.e., it should follow the directions that area Yousef urged a theme of determination determination congestion in terms of the typical waiting time and length of the queue at the isolated intersection and supply and supply in world world management on multiple intersections with the accordance of time period information.
Thus, the information collected is utilized in numerous ways in which counting on the angle of the user.
Following 2 sections define such ways in which of mistreatment the information.
2.2.1. Information Chaining System
The data collected at one junction are often sent to the opposite junction informing it regarding true and permitting it to require measures. An equivalent are often employed in case of cars, ambulance, and different vehicles. This is often quite kind of like the trail optimisation technique, however here the trail that will be taken by the user isn't prompt by the system, and it simply warns the others just in case of any unwanted state of affairs. Leader represented the traffic management on a period of time basis mistreatment the traffic lights.
Wireless sensors area unit deployed on every of the lanes that area unit ready to discover variety of vehicles passing and additionally the expected vehicles and convey the knowledge Blessy planned a system that uses different vehicles to deliver messages regarding any engorged path.
They used AN adjustable field radar-based system, vehicle controller detector that senses the count of the vehi- cles, rejecting the humans sure enough distances.
GSM service is employed to send data regarding the engorged junction to the server placed during a remote location that successively can inform its adjacent signal junction and additionally to different drivers regarding the congestion, forming a chain-like structure informing each other and suggesting them to alter route if necessary.
2.2.2. Green Light Optimization
One of the foremost causes of traffic congestion is giant red light-weight delays, therefore dominant dominant signals and optimizing the length of the inexperienced light-weight can become useful. Genus have given the answer for minimizing waiting time of vehicles by testing the setting issues with issues with. Here, the graph model is employed to rep- resent the traffic network. Therefore on perceive optimum resolution the paper has used particle swarm optimisation and colony improvement and genetic algorithms that have larger importance. Language unit given a MATLAB simulation of fuzzy dominant controller for dominant traffic flow at intervals the multilane isolated signalized intersection.
The controller controls the traffic light-weight timings and 0.5 sequence to verify swish flow of traffic with token waiting time, queue length, and delay time. Jantan planned observance system besides to the traffic light-weight system to establish totally fully completely different street cases (e.g., empty, normal, crowded) with totally fully completely different weather exploitation little or no associative memory hoping on the stream of pictures, that unit extracted from the streets’ video recorders. It along provides a high flexibility to hunt out out {different totally fully completely different completely different} street cases exploitation different coaching footage. Placzek delineate the best manner that is meant to be impel- mended in an internet simulation atmosphere that permits optimisation of adaptation management ways. Performance measures unit computed employing a fuzzy cellular traffic model, developed as a hybrid system combining each cellular automata and fuzzy calculus. Dakhole used ARM7-based traffic system that proposes a multiple traffic light-weight management and observance system that prune the chances the chances jams, caused by traffic lights. Methodology this system this technique} uses ATmega16 and ARM7 for its method. Jaiswal delineate the optimisation of traffic signals by that target 3 areas—Ambulance, priority vehicles (like important person cars, police jeeps), and Traffic density control—thus providing a stoppage free path for ambulances, preventing traffic congestion, and along managing traffic density by increasing length of inexperienced light-weight of the lane wherever density is high (Table 1)
Table 1 Summarization of classification of ITS
|
|
Name |
Summarization |
Remarks |
|
|
Intelligent traffic system |
Real-time system |
Traffic density |
Finding the density of vehicles along a road and follow a certain algorithm to direct the vehicles |
On spot detection and handling of traffic. Requires good financial investment |
|
|
|
Path optimization |
Deciding an optimal path, for an incoming vehicle based on the traffic present at the approaching junction |
Real-time analysis of data to find an easy path, but not applicable for all situations where alternative path is not present |
|
|
Data analysis system |
Information chaining system |
To inform the vehicles about the traffic along any lane and directing them to change to another route if necessary |
Useful in routing of vehicles in an optimized path, but highly developed and error-free system is required else ambiguous situation may arise |
|
|
|
Green light optimization |
Use of different logics like fuzzy logic and other simulation techniques to determine the green light length so that every lane is provided with some appropriate time slot |
Highly efficient system. Requires large capital for implementation |
3. Proposed Method
The planned model in the main concentrates on the subsequent factors:
(i) Unnecessary consumption of the time slice during a sure lane, once there area unit fewer vehicles.
(ii) If any lane has any emergency vehicle like motorcar, it conjointly needs to stay up for its flip.
(iii) A lane with less or additional needs to stay up for constant time span.
Normally, the inexperienced signal within the within the remains on for a fixed interval for every road within the existing system, congestion of vehicles might happen if uncountable vehicles area unit waiting during a specific lane and also the different lane that has fewer numbers of
Intelligent Traffic Monitoring System
3.1. Hardware Implementation of the Method
In the projected model, infrared proximity sensing element, AT Mega 2560, and RF modules are accustomed style the system. The infrared sensors are going to be accustomed collect knowledge from the lane and fetch the collected knowledge to the microcontroller. In every road, there'll be four infrared sensors which is able to be placed at an explicit distance from the intersection, placed on either aspect of the roads in try dividing the thought of length of the road from the intersection into 2 zones—a high density zone and denseness zone. The presence of vehicles in every region is perceived by 2 proximity infrared sensors placed at either aspect of the road within the other way. The sensors square measure placed by keeping an explicit distance in order that they are doing not have Associate in Nursing intersection. the employment of 2 sensors eliminates the issue if “vehicles square measure gift on one aspect solely,” i.e., it provides U.S. The important read in what manner the vehicles square measure aligned on the road. The sensors square measure connected to the analog pins of the chip and also the and also the to the digital pins. Whereas putting the sensors, it's to be unbroken in mind that the vary of the sensors doesn't cross, which is able to end in inaccurate knowledge browse (Fig. 1).
IR Sensor
Connection to the Analog pins of the micro controller from sensors
IR
IR Sensor
Connection to the Digital pins from micro controller to traffic led
IR
IR Sensor
IR Sensor
IR Sensor
IR Sensor
IR Sensor
Central Micro Controller
IR Sensor
IR
IR Sensor IR Sensor
IR
IR Sensor
Fig. 1 Schematic circuit diagram of the proposed model
3.2. Prioritizing the Lanes
Moreover, it provides North American nation the choice to classify the density into multiple values. Like, if all the four sensors of 1 lane sense the worth low, then there'll be no traffic and therefore the priority assigned is zero during this case. once each the 2 sensors in low intensity zone sense the worth as low, however each the sensors in high intensity zone sense the worth as high, then this case won't be thought-about, and it's out of the question. Suppose one among the 2 sensors in low intensity zones provides the worth as high, however the 2 sensors in high intensity zone sense the worth as low, which can indicate that the traffic is incredibly less during this lane and therefore the priority assigned is one. If 2 sensors from constant facet one from low and therefore the different from the high intensity zone sense the worth as high, then it'll indicate that one facet of each zones is full and therefore the different facet is free from traffic and therefore the priority assigned is 2.Then if each the sensors in low intensity zone sense the worth as high, however the sensors in high intensity zone sense the worth as low, then the low intensity zone is full however no vehicle within the high intensity zone and therefore the priority assigned is 3. once each the sensors in low intensity zone sense the worth as high and one among the sensors in high intensity zone senses the worth as high, then it'll indicate that low intensity zone is full however no vehicle in one facet of the high intensity zone and therefore the priority assigned is four. If all the four sensors give the worth as high, then it'll indicate that there's vehicle in each the zones, i.e., each is full which provides high alert and priority assigned to the present case is five (Fig. 2).
Indicates sensors placed along the road to detect the presence of a vehicle. 4 in each lane
Fig. 2 Conceptual view of the proposed model
Intelligent Traffic Monitoring System
3.3. Algorithm for the Control of Traffic Lights
The projected rule at first senses the transport length of every lane and sets its priority and pushes it into the stack.
The sequence during which the lanes are pushed are going to be dead during this sequence solely. Sense_and_Set check the length of the vehicles and set their time consequently, conjointly keeps a make certain the lane with lower priority at first could have no inheritable the next priority than its preceding lane; in such case, the inexperienced lightweight period Ti, to be provided to the current lane, is ablated. The stack is popped once execution of every lane. Once the stack is empty, the lanes are once more pushed into the stack in keeping with priority and dead consequently.
Control_Algo
End.
P_STACK [4]: Stack to store the lane according to priority. Ti: Green Time assigned to the lane.
Pi, Pi-1: Priority assigned to the top two lanes.
While (true) repeat
Sense_and_Push (): for setting the P_STACK . While (Length.P_STACK not equal to 0) repeat
Sense_and_Set (P_STACK): sense the priority for the lane at the top of the P_STACK and setting the green light time of the lane at the top of the P_STACK.
Execute (P_STACK, Ti): Execute the green Light of the lane at the top of the P_STACK.
Sense_and_Push ()
Sense each lane and prioritize them.
Push the lane according to their priority into P_STACK, the lane at the top of the P_STACK has maximum priority.
End.
Sense_and_Set (P_STACK)
If there is an emergency vehicle across any lane Bring it to the top of the P_STACK, Set Ti
Return. Else
Sense the priority of the top two elements of the stack. Pi= Priority of the lane at the top of the stack.
If (i=0)
Else
Pi-1 =0.
Pi-1 = Priority of the lane next to the top of the stack.
End.
Set Ti according to Pi If (Pi < Pi-1)
Indicating that the vehicle length has increased after setting the P_STACK. Update Ti
Execute (P_STACK, Ti)
Set the green light for the lane at the top of P_STACK for time Ti.
Set the yellow light for the lane next to the top of the P_STACK for time Ti, indicating that it will be executed next and red to the other two lanes..
Pop P_STACK End.
4. Conclusion
The work presents review of the prevailing analysis wiped out wiped out tries to develop a system appropriate for developing countries. The project has 2 objectives, which are, first, scheming the length of the vehicles on the road for the flow of the traffic swimmingly while not congestion and, second, developing priority-based sign which can facilitate to relinquish the priority to the emergency vehicles like auto. The microcontroller are often programed simply which provides scope for readying higher algorithms in future. The sensors area unit to be fitted on the facet of the roads and connected to the controller at the intersection. These area unit some feverish jobs that area unit to be dealt before implementing the system, however once enforced, it'll create our traffic system additional convenient and cities smarter.
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