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Traffic systems and Remote monitoring technology
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Dynamic traffic signaling using remote sensing technology
Abstract
Ahmedabad is growing in every possible dimension .The resulting economic growth has fuelled a jump in
four wheelers and two wheelers. Current traffic signaling systems installed in Ahmedabad are static - the
paper attempts to highlight advantages of incorporating RTMS(Remote traffic microwave sensors)
technology and GIS to make the traffic control dynamic and intelligent .Traffic behaviour is studied at
various central business districts of the city to study the feasibility of using RTMS in traffic control
systems. The study runs through various traffic patterns arising in the city at various junctions and tries
to suggest advantage of using RTMS in each case. The paper discuses the simplicity, effectiveness and
viability of such dynamic(technological) adaptation in current traffic systems in Ahmedabad .
Introduction and discussion
Maruti Suzuki , India’s leading carmaker sold over 76000 cars in November 2009,60% more than in the
dire month of November 2008 .This sharp recovery left my uncle with mixed feelings. As a proud owner
of Swift, a popular model, he is finding it increasingly difficult to spot his silver hatchback in Delhi’s
crowded car-parks. In the year 2009 Indian economy grew by 7.9%,far surpassing expectations, in fact a
robust economic indicator considering the fact that the country witnessed worst monsoon since
1972(23% below the historical average).
Such sharp growth has many downsides. The list of downsides includes traffic congestion .Not only
traffic congestion but in a global scenario the aspect of environmental price we pay must also be taken
care of. The number of vehicles in India is already equal to the number of vehicles in U.K.(which is a
developed nation) –it is a surprising fact however that road casualties in India in 2007 were 1.14 lakhs
while the same statistic for U.K. is under 3000 people.
Gujarat is one of the most developed and fastest growing markets in India. Ahmedabad is considered to
be the fastest growing markets for automobile sales. Most of the vehicular traffic in Indian cities is
disoriented and Ahemdabad is no exception. This disorientation brings with it some headaches
of modern day life in the form of Traffic blockages, low average traffic speed, collisions and
other issues.
Not only road safety but business gets directly affected by traffic menace. Businessmen find it hard to
reach their office let alone airports on time. Recently it was reported® that Indian B.P.O business is being
upstaged by Philippines due to ‘messy’ infrastructure here. Arranging employee transit becomes a huge
burden for firms onshore in India. Such basic infrastructure is taken granted in countries like Philippines.
Growth of traffic (all modal systems):(1951-2004) O.P. agarwal and Zimmerman ,towards a sustain able urban t ransit
As the graph suggests the urban vehicle population is growing at double digit rates and as is urban
population.
Growth in percentage(1991-2001)
Urban Population 31%
Urban Vehicle count 250%
The automobile industry in India is the ninth largest in the world with an annual production of over 2.3
million units in 2008.In 2015 it is expected to grow to 4 million units per year level. The World Bank
estimates that traffic in India's cities has grown by 15 percent a year for the last decade, reducing
average speeds during rush hour to five to 10 kilometres an hour in central areas. The internal
combustion engine that powers our transport system is most efficient @ 2000 rpm upwards, that means
a car stuck in congestion or slow moving traffic is spending more time and fuel. Such traffic congestions
are turning chronic by day. Less traffic sense in country worsens the situation in the cities.
India’s traffic infrastructure problems are impending and thus should be taken seriously. RTMS&GIS
technology is a valuable attempt towards improving the current situation.
† Intelligent variable signal timing (iVST)
Traffic behavior is non-linear and the vehicle flux is rarely uniform from all directions arriving at a
junction. There is no debate over the fact that vehicle flux is heterogeneous. Traffic signal is a device
which is meant to control the vehicle flux arriving at a junction. Traffic signal as a tool would be more
effective if we empower it to be dynamic and treat traffic as it behaves. The basic idea behind iVST can
be devised as follows
∆t α V {∆t =signal interval, V=incoming traffic volume}
A rough sketch showing traffic behavior. What is proposed is a spunch-like control system which does
not break owing to sharp and sudden changes-A system that adapts itself to the arising demand.
The tools that can make the proposal possible are RTMS and GIS.
RTMS
RTMS stands for Remote traffic microwave sensor.
The Remote Traffic Microwave Sensor is a low-cost advanced sensor for the detection and measurement
of traffic at intersections and on roadways. This compact true-presence detector provides per-lane
presence indication, as well as Volume, Occupancy, Vehicle Speed, and Classification information, in up
to eight lanes or detection zones simultaneously.
Output information is provided to existing controllers by contact closure and to other computing
systems by its serial communication port. A single RTMS can replace multiple inductive loop detectors
and the attendant controller.
The RTMS is a small radar operating in the microwave band. Mounted on road-side poles, it is easy and
safe to install and remove without traffic disruptions or lane closures. It is fully programmable to
support a variety of applications, using simple intuitive software running on a Notebook PC.
Provides presence indications as well as volume information at up to eight (8) discreet detection zones or lanes
Non-intrusive counting device Increases safety for motoring public
GiS stands for Geographic information system, the data that comes out of RTMS can be integrated
with GIS.GIS can be particularly helpful with
Predicting traffic volumes and alternate routing
Mapping traffic patterns and helping build dynamic traffic algorithm
Study AREA
Ahmedabad: Vroom,Vroom…..
Our study area is beautiful city of Ahmedabad which is the commercial heart of Gujarat . Considered the
second largerst industrial center of the country, Ahmedabad is a vibrant ,colorful city and the bursting
metropolis .The city is designated to ‘mega city’ status recently .Estimated population is 5.2 million in
2009,in an area spread over 200 sq. kms of urban space .The city is physically divided into eastern and
western parts by Sabarmati river. The western part recently witnessed infrastructure and real estate
boom. The western part of the city represents the office going corporate class population, while the east
has industrial pockets where small and medium industries exist. The famous nano project near Sanand is
just one of the many projects in and around Ahmedabad , in coming years Ahmedabad’s prosperity
seems to have no end in sight.
† Urban transport in Ahmedabad
Ahmedabad city is well connected by an expressway, several national and state highways, the broad-gauge and
meter-gauge railways and an international airport. The city transportation system is predominantly dependent
on roadway systems.Vehicular growth has been rapid. Every year about a lakh of vehicles are added in the city.
Of these about 20000 are cars and about 60000 are two wheelers. In fact the vehicle ownership rates are the
highest among the 4 million plus cities of India. Overall, the congestion levels have still not reached their critical
limits but just started to cross the critical limits in some central sectors.
Road map of ahmedabad. Study area marked in red. (Map not to scale)
†Method of data acquisition
A regular digital cam was used to count the vehicular traffic.
†Modal split of vehicles observed(averaged out)[5 cycles of traffic stops][4 junctions-
IIM, Panjrapole ,keshav bag, vijay cross roads][TB1]
MODAL SPLIT Observed % among total vehicle count
2 wheelers 58.3
Auto rickshaws 9.4
Passenger cars 20.8
Buses 2.5
Trucks/Tractors 2.1
Cycles/Others 6.9
Modal split chart
Based on Survey.
2 wheelers58%
Auto rickshaws9%
Passenger cars21%
Buses3% Trucks/Tractors
2%
Cycles/Others7% Modal Split
Peak hour data[TB2]
Based on survey
† Hetrogenity of traffic flux within the junction[TB3]
Junction: IIM(1900-2030 ,10 cycles)Arm1 ×Arm3 Arm2 ×Arm4
Junction Arm BY length(AVG)m BY rate(AVG) Length(min,MAX)
ARM1 70m 21/min (40,400)
ARM2 25m 9/min (20,70)
ARM3 40m 16/min (40,300)
ARM4 50m 14/min (20,250)
Based on survey
RTMS & GIS: FLEXIBLE TREATMENT TO FLEXING PROBLEM
We know that
Efficiency of a traffic system, η= , here the numerator has a random behavior
while the denominator is linear (incase of a static system).
Junction Peak hour
20 cycles each
Volume(est.)
Extrapolated
Recorded frequency
All 4 arms avg.
IIM 1850-2045 7500 65.21/min
Panjrapole 1915-2015 3000 50/min
Vijay cross roads 1930-2015 1000 22/min
Keshav baug 1915-2045 4000 44.44/min
The above graph explains efficiency of a traffic signal in the current system.
As shown above η is maximum at certain value x. Mean while it is less to the left side which is
underutilization and gets even lesser at the right side of the value x –can be said as overutilization.
Here ηmax is a constant which represents a certain count of vehicles(Vmax) in given time that a junction
can handle efficiently. defined by
ηmax = Vmax/∆t
ηmax depends upon road width and hence constant.
WHERE RTMS WILL HELP?
Underutilization [V<< Vmax]
Increase in efficiency by being dynamic using RTMS.
When η<< ηmax
ηu α {where ηu is efficiency during underutilization}
hence the ratio,
ηu/ ηmax = Vmax / V
IF Vmax is more than V and if we change ∆t accordingly we’ll get a positive change in efficiency according
to the above equation. Surely Data from RTMS will tell us about behavior of V helping us improve the
efficiency overall. Refer to table 3 many times it happens so that only few arms of junction have
underutilized capacity. In that sense we optimize the time on underutilized lanes so that remaining
crowded lanes are serviced more efficiently. IIM is one of the intersection where most hetrogenity is
found.
Hence the total stoppage time is a result of individual functions in its arms
Fa(∆t) + Fb(∆t)+ Fc(∆t)+ Fd(∆t)= ∆ttotal {where A,B,C,D are individual arms of junction}
Each individual function may have different parameters but they depend more or less on the same
factors,
F(∆t)=f (V, ,H,R)<SL { V=vehicle volume, rate of incoming traffic, H=hetrogenity mix,R=Road width
SL is an function which calculates operating maxima for F(∆t) based on traffic models that take care of
optimum efficiency of other three arms}
V, ,H is the data that can be provided by RTMS.
RTMS DATA
Above is the example of RTMS data from HAITI. Customized data can be extracted . RTMS data can be
interpolated/customized to match the requirements of various patterns of Traffic and modal splits.
Overutilization [V> Vmax]
Crowding at an intersection is generally responsible for slow moving traffic. Slow moving traffic can
potentially develop into a jam or gridlock. Many countries have developed dynamic systems to control
such situations.
Mostly such systems are powered by some sort of sensors and switching times are computed using
powerful algorithms. This approach considers traffic to be moving smoothly and hence does not require
any management or monitoring. Traffic behavior is extremely complex , when some unpredictable
situation arises sensor-based systems fail to manage it. There are systems with video cameras where
traffic is controlled from a station full of human experts –these systems remain extremely expensive to
operate and take a lot of computing time which is not feasible.
WHERE WILL GIS HELP?
The best way to tackle crowding at a junction is to avoid it.
†UNCERTAINITY IN ROAD TRAFFIC
Mostly sudden occurrences are not manageable. The uncertainty of events in traffic behavior is surely a
matter of huge concern. Traffic behavior is a stochastic process. Each individual event occurs randomly
and is governed by undefined laws. Its very hard to be proactively control such events. Traffic
synchronization becomes a headache not only because of sudden arrival of huge volumes but also
because of undeterministic nature of vehicle flux arriving at a junction .Just imagine if you’d be able to
determine exactly the amount of flux to received you get ample time to react adaptively. The problem
of synchronization multiplies as the number of junctions to be managed increases and also it depends
on factors like average speed,collisions etc.
GIS and CERTAINITY (ARRESTING SUDDEN CHANGES)
Vehicle movement in an urban space is a mixed function.
Total vehicle volume=Regular volume + Random volume
Vtotal = Vreg + Vrndm
Where Vreg ≥ 0 , Vrndm ≥0 at any given point of time.
Regular traffic
People movement is pre-empt at some period of intervals. More acceptable example is that of people
going to their offices and returning .Part of the trips that people make are periodic which are made at
almost identical times and identical routes.
Regular traffic is the most predictable traffic ,still undeterministic in nature. That means Regular traffic is
pseudo-random. All people that commute dialy ,hold choice of changing the trip-time, trip-route, trip-
mode or choose to not make a trip at-all. But most of the people are bound to do their work ,go to
schools etc.
ESTIMATION OF V, , H through GIS
DIAGRAMATIC REPRESENTATION OF A CITY BLOCK
Estimation of V
A city block may consists of different kinds of built up area. Most of the properties can be categorized
into residential or commercial. We may gather origin-destination details of each individual in each
property and know the demand of transport in each sector of the city. We can feed this data into GIS.
VOLUME PROBABILITY DISTRIBUTION AT A REFRENCE POINT
P(V)= N(I)Sd {K is the statistical mean of arrivals,𝝀 is total expected number of
arrivals, N(I) is network performance factor ranging as 0-1, Sd is measured deviation from
average speed}
𝝀 can be directly measured by GIS application
Estimation of H
Hetrogenity in demand and modal split can be estimated with information regarding modal choice
pattern of each individual .
HETROGENITY PROBABILITY DISTRIBUTION AT A REFRENCE POINT
P(H)α P(V)
A very vague representation of P(H) can be done as
+ + + =1 {here P(c),P(m),P(t),P(o) represent average estimated traffic according to the
data collected of cars, mopeds ,truck/buses and other modal choices respectively. P(v) is estimated
volume.}
Estimation of
Speed distribution of vehicles depends on many macroscopic and microscopic properties. It is hard to
estimate such quantities accurately ,however not impossible to measure ,can be vaguely represented as
P(S)= AVG SPEED * *N(I) {F-S is the difference between fastest and slowest vehicle on the road and
N(I) is the network performance.}
P(S) is the corrected speed of total volume of cars.
D(S)=P(S)±d {d is the required interval of accuracy}
CATCHING THE PATTERN AND GIS
Traffic behavior is a sum of independent events and is an extremely complex to model it probabilisticly.
Although it is found that under a long series of observations and large proportion of time an event
occurs the probabilities of random quantities approach a constant. For example the probability of
vehicle volume at a refrence point becomes constant after n cycles of observation.GIS can measure
these quantities and store them at each observation point. When the need arrives the GIS system
should use these quantities to make decisions that help traffic flow by recognizing the pattern in current
environment. We should not forget that traffic pattern is spatially related.
V=
ALTERNATE ROUTING AND GIS
Alternate routing is also a dynamic way of controlling traffic. Refer table 2 you’ll see that at IIM junction
the volume of vehicles is 7500.Clearly from site observation it can be said that it is a large volume to
handle.IF we device a mechanism to route the traffic in other direction then may be part of vehicle users
may choose to deviate from their planned path. For example in our case we can make traffic efficient at
IIM junction if we distribute the extra traffic to other junctions.
Alternate Routing becomes practical only if the vehicles are provided with routing information well
before they enter a congested route. We should remember that our primary objective is to avoid the
congestion and not manage it once it has occurred. Practically alternate routing involves well modeled
algorithm. Although algorithm efficiency depends upon the input we feed into it. IF we have P(V),P(H)
and D(S) known at each junction then the effectiveness of the routing increases manifold. Knowing
these values and quick traffic pattern detection saves times which is advantageous in being proactive
while alternate routing.
CALCULATING LEAST OBJECTIONABLE ALTERNATE ROUTE
GIS system will have real time route statistics of each intersection.This information can be refrenced
while dynamically routing the vehicles. There are numerous factors to be considered to make an
efficient as well as acceptable choice.
There are n possible routes that a person can choose but least objectionable route can be calculated
dynamically using multivariate calculus. Further study needs to be carried out however to reach at
operating standard.
COMMUNICATION WITH USER
Communication with users can be done using digital signboards on each intersection. The choice of
alternatively routing the trip remains with the user. If the system is accurate and really saves time of the
user he’ll accept the system and rely on it in future trips. Communication on individual basis through
mobile telephony can be worked out, but it may increase the complexity of situation.
DIAGRAMATIC REPRESENTATION OF PROPOSED SYSTEM
Conclusion
There are good number of examples where sensor based intelligent traffic systems are involved. More
or less many traffic systems fail when extremely large volumes of vehicles gather at the same junction.
People forget that traffic movement is spatial .It depends on spatial factors.GIS thus becomes essential
tool in enhancing the efficiencies of sensor based systems. The paper suggests the direction of
involvement of GIS in traffic related infrastructure. Further study in this direction can be carried out to
figure out exact algorithms of on field operation.
Road infrastructure is a life-line of Ahmedabad city. Good vehicle volume is an great indicator of
prosperity. Economists believe that increase in traffic problems is a direct indicator of strength of
economy but care should be taken that traffic problems should not increase to a proportion that they
start giving negative effects on economy instead.