Area Traffic Control Systems

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CE 310: TRANSPORTATION ENGINEERING

AREA TRAFFIC CONTROL SYSTEMS

JAYANT PATIL (09004023) AVISHMA MATTA (09004078) VIKAS SHARMA (09004028) VINAY KRISHNAN (09004017) VISHAL KHATRI (09004025)

WORD COUNT: 2967

CONTENTS

1. INTRODUCTION 2. PAST DEVELOPMENTS 3. MAJOR COMPONENTS OF AREA TRAFFIC CONTROL SYSTEMS 3.1. VEHICLE DETECTORS 3.2. INTERSECTION CONTROLLER 3.3. COMMUNICATION NETWORK 3.4. CENTRAL CONTROLLER 3.5. APPLICATION SOFTWARE 4. ADVANTAGES OF AREA TRAFFIC CONTROL SYSTEMS 5. NETWORK CONTROL STRATEGY 6. STATE OF THE ART IN ATCS 6.1. SPLIT CYCLE OFFSET OPTIMIZATION TECHNIQUE 6.2. SYDNEY COORDINATED ACAPTIVE TRAFFIC SYSTEM 6.3. COMPOSITE SIGNAL CONTROL STRATEGY 6.4. OTHER MODELS 7. CASE STUDIES 7.1. CoSiCoSt 7.2. SCOOT 8. FUTURE SCOPE OF ATCS 9. CONCLUSION 10. REFERENCES

1. INTRODUCTION In recent years there has been a major rise in the volume of vehicles in major cities across the world. This has resulted in traffic management problems such as congestion, delays, accidents, pollution, increased fuel consumption etc. A need has arisen for proper traffic management measures, policies and systems. Area Traffic Control Systems are intelligent, real time systems that optimize traffic signal settings in an area, based on data obtained from vehicle detectors to reduce vehicle delays and stops. The Area (or Adaptive) Traffic Control Systems have two main functions: 1.Controlling Traffic Signal Timings depending on the data acquired by the vehicle detectors. 2.Providing drivers (public and private vehicles) with traffic information. 2. PAST DEVELOPMENTS The first electronic traffic signals were introduced by the Cleveland Engineers in 1914. Denver Engineers used analogue computers with sampling detectors to select the most appropriate signal timing from programs. The development of traffic control systems started in 1960s. These first generation systems monitored traffic flow continuously and initiated the appropriate algorithm from a database to give optimal signal settings. In 1973, a full Adaptive Traffic Control System called SCOOT (Split Cycle Offset Optimization Technique) was developed by the Transport Research Laboratory (TRL) in collaboration with the UK Traffic Systems Industry. The Australian SCATS (Sydney Coordinated Adaptive Traffic System) was developed in the 1974 in Sydney by the Roads and Traffic Authority. In the 1980s and 1990s, these traffic control and management systems started to gain wide acceptance and were implemented for both freeways and urban streets. Developments in microprocessors and vehicle detection mechanisms led to further advancements in control algorithms and strategies for traffic control systems. Today, the traffic monitoring and control systems are mature and the emphasis is on implementation of effective operational tools. Presently, there is a wide array of system designers, hardware manufacturers and suppliers and software developers to choose from, for system selection. (FHWA, 2005) 3. MAJOR COMPONENTS OF AREA TRAFFIC CONTROL SYSTEMS 3.1 Depending on the type of sensors, vehicle detectors collect data for vehicle volume, average speed, class, gap, headway, occupancy, queue length measurement, weight, corridor travel time etc. Vehicle detection technologies contain three components: a transducer which detects the vehicle, a signal processing device converts the transducer output to electrical signal and data processing device converts this into useful traffic parameters.

Detectors can be broadly classified into : Intrusive Sensors - these include inductive loops, magnetometers, microloop probes, pneumatic road tubes, piezoelectric cable, bending plate (weigh-in-motion), piezoelectric (WIM), load cell (WIM), capacitance mat (WIM) sensors. Of these the inductive loop detectors are most widely used as they are relatively low cost and the technology is mature. Non-intrusive sensors – these include video image processing, microwave radar, laser radar, passive infrared, ultrasonic, passive acoustic array and combinations like passive infrared and microwave Doppler or passive infrared and ultrasonic detectors. They measure vehicle count, presence, vehicle speed, vehicle classification, and have multiplelane, multiple-detection zone coverage.

3.2. Intersection Controller consists of electronic equipment placed at the signal. The data acquired by the vehicle detectors at various points on a road network is sent to the Signal Controller which then relays it to the Central Control (except in CoSiCoSt and similar systems where it also does split optimization, Muralidharan et al). 3.3. Communication Network: The data is sent from Intersection Controller to the Central Control which after analysis of the data updates the time plan to all intersection controllers in the area through this UDP Internet Protocol based network communication link. 3.4. Central Control: The Central Control System comprises of the ATCS Server, Operator Consoles, external storage devices etc. The master controller takes complex decisions based on the traffic data. The type of decision includes calculating the cycle time, removing or adding a junction from the network area, isolating a junction, selecting plan from the database etc.

3.5. Application software is integrated into the intersection controller to recieve detector inputs, process status data, compute signal timing and driving signal lamp load switches.

Figure 1. Basic Components of ATCS

The figure depects the components of a typical Area Traffic Control System with the vehicle detector, Intersection Controller, Central Control, Communication network 4. ADVANTAGES OF AREA TRAFFIC CONTROL SYSTEMS ATCS provide a management measure to tackle traffic congestion since they increase volumecapacity ratio of a network. For a road user, this implies greater average speed due to less delay and stoppage time, besides reducing fuel consumption and atmospheric pollution (FHWA, 2005). The ATC system is equipped with the fault detection and logging mechanisms which are triggered when there is a fault in data collection or transmission. This facilitates prompt repair and maintenance action. 5. NETWORK CONTROL STRATEGY The algorithms used by ATCS are, in general, a hybrid of mathematical and heuristic models. Models have been developed to optimize cycle time in an intersection, relative cycle times at nearby intersections and the offset time of these cycles. They are briefly described below. Split optimization includes algorithms to calculate optimal cycle time at an intersection and the time allotted to each approach or stage. During a red signal at an intersection, sensor loops present at the stop line register a demand for right of way. After the mandatory minimum green

time is executed, if the sensors continue to register demand, then the green time is extended by the traffic signal controller until the sensors stop registering demand, subject to the maximum green time allocated for that approach by the central control. In case the sensors register a gap in the flow of vehicles, the green time allocated to that stage is immediately terminated and the next stage is opened. Thus this stage would have the advantage of additional time due to preempting of the previous stage. Normally, this additional time is given to the approach carrying the maximum traffic at the intersection. In order to check the effectiveness of the stage timings and cycle lengths allotted to the signal control by the central control, a feedback mechanism is developed. Stages that use only a fraction of the green time allotted to them or stages which are so saturated that the green time allotted to them is insufficient to clear the queue require revised settings and this is done by the feedback provided to the central control by the signal control system. Accordingly, highly saturated stages are allotted more green time, keeping the cycle length same, if possible. If not, care should be taken to avoid oscillations in cycle time and maintain signal coordination since several intersections with similar characteristics may operate on a common cycle time. In order to ensure smooth flow of traffic, the relative cycle lengths of nearby intersections should also optimized. Therefore intersections with similar traffic volume characteristics are grouped together considering their geographical distribution to operate on a common cycle time. Whereas intersections with high disparity in traffic volume characteristics are either isolated or are accommodated in group with half or double cycle time. The purpose is to ensure that traffic which is smoothly dispersed at one intersection gets similar conditions on reaching the next intersection. The common cycle time for intersections belonging to a particular group is taken as the cycle time of the intersection with maximum traffic volume in that group, i.e. the critical cycle time. Based in these explanations, it may be inferred that an intersection with similar traffic characteristics as the critical intersection, but not as saturated, is less efficient since it is forced to operate at the common cycle time that is, the critical cycle time. However, this is not true since the difference between the common cycle time and the required cycle time for such an intersection is allotted to some stages in the intersection, identified as priority stages. These are the stages contributing traffic to the route with the maximum volume of traffic in the area and hence are given the advantage of additional time to ensure that they are dispersed smoothly. Apart from this, any additional time due pre-empting of any poorly saturated stage is also given to the aforementioned stages. The third parameter to be given due consideration is the offsets between stage timings of intersections. The purpose is to minimize the stopping time of a platoon arriving at an intersection by coordinating signal settings between intersections. The flow profile in an arterial road is determined by providing sensor loops at strategic locations. Based on this flow profile, the intersection controller calculates the ground speed of the platoon of vehicles and sends this information to the central control which in turn calculates the optimal offsets and applies them to the network to achieve maximum coordination between intersections.

6. STATE OF THE ART IN ATCS 6.1 SPLIT CYCLE OFFSET OPTIMIZATION TECHNIQUE Split Cycle Offset Optimization Technique (SCOOT) is an urban traffic control system developed in 1973 by Transportation Research Laboratory in collaboration with the United Kingdom traffic systems industry. Over the years, it proved to be an effective and efficient tool to manage traffic at signalized road networks (Hunt et. al, 1981) and is now used in over 170 towns and cities in the United Kingdom and across the world. The first ATCS project in India, consisting of 47 junctions at National Capital Region, New Delhi, has been executed using SCOOT by CMS in collaboration with Peak Traffic Systems, UK. SCOOT essentially uses a variant of the TRANSYT optimization model that runs in a background called SCOOT kernel. Traffic volume data, continuously obtained at all approaches of intersections in a network, are the input to the kernel, which generates optimal signal timings and communicates it to the intersection controller. The intersection controller uses these suggested timings, in combination with the changing traffic demand, to make incremental adjustments to the cycle length, stage timings and offsets for the current and next cycles (Head et. al, 1992). Several problems have been reported in the implementation of SCOOT in India. Most prominently, SCOOT is not designed for the heterogeneous traffic conditions prevalent in India where drivers tend to use available road width rather than sticking to the lane. Secondly, it has been reported that the interface of SCOOT is difficult to handle and it traffic terminologies are different from those used India. Thus, adaptations are required to implement SCOOT in Indian conditions.(Muralidharan et al.) 6.2 SYDNEY COORDINATED ADAPTED TRAFFIC CONTROL SYSTEM Originally developed for Australian cities in 1974, SCATS is an adaptive system which optimizes cycle time, stage time and offsets in response to real time traffic. However, unlike SCOOT which is based on an optimization model, SCATS uses a library of plans to select from and therefore relies extensively on available traffic data. In this context, it has been loosely described as a feedback control system (Head et. al, 1992). Similar to SCOOT, it has been reported that SCATS lacks an user friendly interface and is perceived to be excessively complex and labour intensive operationally. SCOOT Centralized System Upstream Detection Fixed Traffic Regions Fallback - Fixed Model based - Time generated SCAT Distributed System Stop line Detection Adjustable Region Fallback - VA Algorithmic - Plan Selection SCOOT vs SCAT – a comparison

Source – Presentation by Prof.Tom Mathew (IIT-B) and P Ravikumar (CDAC-T)

The table summarizes the different aspects of SCOOT and SCAT. While SCOOT is designed as a centralized system for fixed traffic regions, SCAT is a distributed system for adjustable regions. The vehicle detection is done at an upstream cross section in SCOOT and at the stop line in SCAT. SCOOT is a model based system in which the solution is time generated while the SCAT provides an algorithmic plan selection. 6.3 COMPOSITE SIGNAL CONTROL STRATEGY While developing an area traffic control system for a developing country like India, several considerations need to be taken into account which are not applicable to developed countries. For instance, SCOOT and SCAT assume less heterogeneity in traffic vehicles and lane discipline is followed by everyone except a very small minority. In contrast, the traffic in India is highly heterogeneous & not separated and lane discipline is rarely followed. It is also assumed that there is no lane change in the detection zone, which again, is highly unlikely in Indian cities. This results in wrong vehicle count estimation and detectors failing to report the correct turning vehicle proportions at intersections. There are other problems like poor road network planning in the cities, side roads, uncontrolled on-street parking, pedestrians and road side vendors encroaching the road space, data loss due to power failure, network failure, availability of funds etc. Thus classical methods of signal time computation cannot be applied in this case because of the complexities involved in the calculation of Passenger Car Units (PCUs) in real time (Muralidharan et al). Composite Signal Control Strategy (CoSiCoSt) is an indigenous area traffic control system developed by Centre for Development of Advanced Computing (CDAC), Thiruvananthapuram. It uses appropriate modifications to previous ATCS such as SCOOT to suit Indian conditions. Most notably in this regard, methods to synchronize heterogeneous road traffic and the ATCS and methods for vehicle identification to obtain traffic count have been developed. Currently, it has been implemented in Pune, Kolkata, Jaipur, Ahmedabad and Bangalore. However, certain limitations have been identified and the model needs better offset calculation, an optimization model for local control, optimization for network level traffic management (Source - Presentation by Tom V. Mathew). 6.4 OTHER MODELS Others models of area traffic control systems developed include OPAC (Optimization Policies for Adaptive Control), RHODES (Real time Hierarchical Optimized Distributed and Effective System), ACS-Lite, SPOT/UTOPIA (Urban Traffic Optimization by Integrated Automation), MOTION (Method of Optimization of Traffic Signals in Online controlled Networks), ITACA (Intelligent Adaptive Control Area), RTACL (Real time Traffic Adaptive Control Logic). 7.CASE STUDIES 7.1 CoSiCoSt CoSiCoSt was implemented in 38 junctions in Pune by CDAC in 2006. The project was jointly funded by DIT and Pune Municipal Corporation at the cost of Rs.597.98 lakhs. A study

conducted by CDAC in 2007 (Muralidharan, Ravikumar et. al.) regarding the various measures of effectiveness of the implemented systems gave the following results: 1. Average travel speed increase in the range 2-12% 2. Reduction in average delay in the range of 11-30% 3. Estimated annual fuel savings in the year 2006 due to implementation of ATCS is about Rs.4.77 crores. 4. Estimated annual time saving benefits due to implementation of ATCS is Rs.0.83 crores. 5. Total annual savings due to implementation of ATCS on 6 project corridors is about Rs.5.60cr 6. Overall increase in traffic volume is about 9.06% 7.2 SCOOT The results of a study titled “SCOOT Adaptive Signal Control: An Evaluation of its Effectiveness over a Range of Congestion Intensities” by Chintan S. Jhaveri, Joseph Perrin & Jr. Peter T. Martin for Transportation Research Board(January 2003) are summarized below. The study aimed at testing the effectiveness of SCOOT using CORSIM(a simulation software). The SCOOT-CORSIM Interface (developed by University of Utah) was used to test the simulation of networks under SCOOT control. Modeling of the test corridor at different congestion levels proved the benefits of SCOOT over fixed time plans. This was tested on two real-world corridors’ (in Salt Lake Valley) simulation. The results were as follows: 1. Delay reductions for SCOOT over fixed-time control at 0.7 volume/capacity ratio were 8% and 13% at 0.9 volume/capacity ratio. But this reduced to a 0% for an oversaturated 1.1 ratio. Thus it performs better at undersaturated traffic flow conditions and the performances improves as the corridor approaches saturation but the benefits are minimal. For oversaturated conditions, it behaves like a fixed time control system. This is because all directions demand maximum green time and any depend actuated optimization system would thus behave like a fixed time control. 2. Validation was found to be an important requirement. A nonvalidated system performed 219% worse (and a validated performed 8% better) than the fixed time system. 3. The two real-world corridors’ simulation proved that SCOOT reduced delay (14% reduction), travel time and queue lengths as compared to an updated fixed time plan. 8. FURTHER SCOPE OF ATCS ATCS can be integrated with other features like: 1.Variable Message Signs (VMS) systems are used to direct drivers to the closest car parking that has space available or to provide other information to the driver like traffic density along a route in real time. 2.Emergency Green Wave Routes provide a continuous chain of green signals along a predefined route to provide the emergency response vehicle with highest priority 3.Incidents Detection: Incidents are complex scenarios that can cause traffic congestion. Traffic congestion is a result of lower traffic flow through the arterial road which itself is a consequence of decrease in roadway capacity. These incidents can be detected through videographic

techniques and the corresponding intersection can give more green signal time to this route, thus clearing the accumulated traffic. 4.Diversions: The ATCS can take input from an external source to implement a predetermined diversion as in the case of a regular bridge closure or a road closure due to some maintenance activity. 5.Prioritization: The ATCS can be programmed to favour specific routes considering particular traffic management policies. This can be done by assigning different weights to the routes at an intersection. 9. CONCLUSION Area Traffic Control Systems have been proven to be beneficial over fixed time traffic control systems (V. Muralidharan et al, Peter Martin et al). There is significant reduction in delays and stoppings after the implementation of ATCS at various traffic networks throughout the world. In a developing country like India, transportation plays a crucial role in growth. As the cities are getting more crowded, the road transportation facilities are moving towards saturation. Thus there is a need of improving the efficiency of utilization of these facilities in addition to constructing new ones. ATCS like CoSiCoSt can be designed and used to suit the Indian traffic conditions. Further research should be carried out in this area.

REFERENCES 1. Suresh P.S. (2009). Traffic models for real time area traffic control systems in heterogeneous traffic conditions. PhD Thesis, IIT Bombay. 2. Shabade A.M. (2009). Urban intersection modelling for area traffic control in heterogeneous traffic. M.Tech. Dissertation, IIT Bombay. 3. Revade R.S. (2008). Evaluation of an area traffic control system and saturation flow model for heterogeneous traffic. M.Tech. Dissertation, IIT Bombay. 4. Revathy Nair. (2010). Development of system architecture of area traffic control system for heterogeneous traffic. M.Tech. Dissertation, IIT Bombay. 5. Suraj Shinde. (2007). Evaluation of area traffic control system.” M.Tech. Dissertation, IIT Bombay. 6. Kajal Dubey. (2008). Conceptual architecture and progression model for an area traffic control system. M.Tech. Dissertation, IIT Bombay. 7. Ravikumar P., Tom V Mathew. (2011). Second Generation CoSiCoSt. IIT Bombay and CDAC, Thiruvananthapuram. 8. Muralidharan V., Ravikumar P. (2007). Area Traffic Control System implementation at Pune- Case study. CDAC. 9. Chintan S. Jhaveri, Joseph Perrin Jr., Peter T. Martin. (2003). Scoot Adaptive Signal Control: An evaluation of its effectiveness over a range of congestion intensities. University of Utah. 10. Tavladakis K., Voulgaris N.C. (2006). Development of an Autonomous Adaptive Traffic Control System. Technical University of Crete. 11. A.G. Sims, K.W.Dobinson, (1979) The Sydney Coordinated Adaptive Traffic system philosophy and benefits. 12. Technical Specification of Area Traffic control system, Webel Mediatronics, http://www.webelmediatronics.in/ 13. Muralidharan V., Ravikumar P., Binala S. and Tagore M. R. (2006) A Composite Signal Control Strategy for Indian Roads, Journal of Indian Highways. 14. Federal Highways Association. (2005) Traffic Control System handbook, Publication No. FHWA-HOP-06-006

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