Behaviour Change
Chapter 12ücÚĆ.Ä£ËÚÃæ¬ËÄIntroduction
Intersection crashes, particularly
right-angle crashes play a signiﬁcantrole in traffic accidents. According to
the Indian Ministry of Road Transportand Highways, 449,002 road crashes
were recorded in 2019, out of which
28% of the crashes occurred at
the intersections [ 1 ]. Unsignalizedintersections account for 20.6% of
total intersection crashes and mostof these resulted in serious injuries
or fatalities. Crashes at unsignalizedintersections mainly occur when avehicle on minor road attempts toenter or cross the intersection withan unsafe gap condition. Poor sightdistance, wrong judgment in gap
acceptance by minor road vehicles,and priorities not being respected by

the road users are the causes for thecrashes at unsignalized intersections.
To reduce frequency and severity ofcrashes and enhance road safety,
Intersection Conﬂict Warning System(ICWS) is found to be effective.
ICWS consists of an activatedwarning sign and sensors which
detect the vehicles approaching theintersection. It warns the drivers on
the minor road about presence ofvehicles on major road and informs
the drivers on the major road about
presence of vehicles on the minorroad. This situation results in reduced
conﬂicts as drivers get alert about
the possible approaching vehicle,
resulting in lower intersection
approach speeds and improved
driver gap acceptance.

This chapter shows to evaluate
the performance of ICWS for atypical uncontrolled intersection
by examining the responses ofmajor road drivers towards thedesigned warning system. Different
scenarios were designed to assess
the behaviour of the drivers on themajor road approach and driving
performance measures such as speed
and acceleration were evaluated.

Study area andexperiment design
The experimental methodology forevaluating the response of majorroad drivers towards intersection
conﬂict warning system is shown in
Figure 12-1. The study area selected
is of 2.1 km road stretch starting from

Figure 12-1 Methodology for evaluating ICWS at uncontrolled intersections

Test route from hostel
circle to IITH main gate
Instrumented vehicle

Scenario
designPreliminary Analysis••

ANOVA test
Drivers speed
profilesResults and Conclusions

70Data extraction•••Speed
AccelerationDrivers age

Participants
were asked tofill signageform

Chapter 12
Behaviour Change by Traffic Information

IITH hostel circle (point A) to themain gate (point B). It consistsof uncontrolled intersection,roundabout, and side roads.
Intersection conﬂict warning system
was installed at a four-legged
uncontrolled intersection, which is
230 meters away from the hostelcircle (point A). A loop detector wasinstalled on a minor road and awarning signboard installed on themajor road. Twenty-nine participants
with age ranging from 22 to 57 years
were recruited for this study. Sociodemographic characteristics such asage, gender, education qualiﬁcation,driving license and occupation werecollected.
Four scenarios were designed toevaluate the response of major roaddrivers towards intersection conﬂict
warning system. In the ﬁrst scenario,
no vehicle was present on the minor
approach and therefore warning
sign was not activated on the majorroad (Figure 12-2 (a)). In the second
scenario, crossing vehicle waspresent on minor road and warning
sign was not activated on the majorroad. In the third scenario, crossing
vehicle was present on the minor
approach and entering traffic warning
signal was given to the major roadapproach as shown in the Figure 12-2(b), however no prior information
was given to the participant driver
regarding the entering vehicle
from minor approach. In the fourth
scenario, the participant driver
was educated about the deployedwarning system and was asked todrive through the intersection withentering traffic warning signal on.
The fourth scenario was designed
to assess the drivers understandingof the warning system by examining
their responses towards the system.

Procedure
A passenger car instrumented withvideo box was used for collecting thedata. The video box (v- box) consistsof a GPS receiver that records theposition movements at 10 Hz andFigure 12-2 Experiment design with different scenarios

has two video cameras for recording
videos as desired. One camera
ﬁxed to the windscreen records theroad features and moment when
the warning sign is activated. The
second camera placed below thesteering wheel records the driver’s
brake movements. Figure 12-3
represents the image of an
instrumented vehicle used for thestudy. Participants were asked to signon the consent form before they start
the experiment. Each participant has
to perform four test drives in orderto provide responses to the fourdifferent scenarios. At the end of theexperiment, participants were asked
to ﬁll a post signage questionnaire
form to assess the degree to which
the warning system helped themin crossing the intersection safely.
Further, they were asked to complete
a signage questionnaire in which
they have to rank the warnings signs
that they think suitable for placingnear uncontrolled intersection frombetter to worse.

Figure 12-3 Instrumented vehicle used for the study

Subject vehicle(a) Scenario 1: No conﬂicting vehicle with warning sign not activatedConflictingvehicle

Camera 1

Camera 2

Video box

ENTERING TRAFFIC

Loop detector

Subject vehicle(b) Scenario 3: Conﬂicting vehicle present with warning sign activated71Handbook of Multimodal Transport for Smart City
Application of Sensing, Networking and Big Data Analysis

Table 12-1 Driving performance with different scenarios

ICWS
Scenarios
Scenario 1
Scenario 2
Scenario 3
Scenario 4
ANOVA
p-value

Mean
39.21
38.94
37.78
32.86Speed (km/h)
Standard
deviation
5.80
4.95
5.18
4.91

0.000*

Number ofobservations
29292929

Mean0.05
0.22
0.32
0.27

Deceleration (m/s2)Standard
Number ofdeviation
observations
0.12
290.26290.24290.21290.000**p < 0.05

Data Analysis
Drivers speed and acceleration
proﬁles were extracted at a distanceof 80 meters from the uncontrolledintersection. One way ANOVA wasemployed to study the statisticaldifferences in driving performanceagainst three scenarios. A post-hoc
test Tukey’s Honesty Signiﬁcant
Difference was conducted todetermine any interaction exists
between the two scenarios.
A signiﬁcance level α = 0.05 wasconsidered in the study. To assess
the best warning sign from thesignage questionnaire form ﬁlled
by drivers borda count method wasemployed.
The summary statistics of driving
performance measures and one-way
ANOVA results are shown in
Table 12-1. A statistical difference
was observed among four scenarios(F = 9.30, p = 1.52E-05) for mean
speed. The post comparison
revealed that the difference between
the mean speed of scenario 2 andscenario 4 (p = 0.0001) as well as
the difference between the mean
speed of scenario 3 and scenario 4(p = 0.002) was statistically signiﬁcant.
This demonstrates that the drivers
with a better understanding of thewarning system resulted in lower
mean speed in scenario 4 comparedto scenario 2 and scenario 3.
There was no signiﬁcant difference
observed between the mean speedof scenario 2 and scenario 3.
The reason could be that drivers
did not pay much attention to the72

warning system in scenario 3, andthe mean speed for scenario 2 andscenario 3 was almost the same.
A statistical difference was observed
among four scenarios (F = 9.24,p = 1.62E-05) for mean acceleration.
The post comparison test revealed
that the difference between mean
acceleration of scenario 2 andscenario 4 as well as the difference
between the mean accelerationof scenario 3 and scenario 4 wasstatistically not signiﬁcant.
Figure 12-4 represents the boxplot
of mean speed of all drivers for four
scenarios. The quartiles of the box
presented here are the 15th and85th percentile, and median is 50thpercentile. The vertical line in theﬁgure represents the intersection
where a minor road vehicle enters.
From the ﬁgure we can observethat the mean speed of all drivers
for scenario 1 was almost constant.
For scenario 2 there was a slight
reduction in speed when theyapproached the intersection. In
scenario 3 there was a reduction in
speed compared to scenario 2 when
they approach the intersection. In
scenario 4 drivers tend to reduce
more speed compared to scenario 2and scenario 3 when they approach
the intersection. This indicatesthat the drivers with a better
understanding of the warning system
could respond before they approach
the intersection and can avoid
sudden braking at the intersection.

A post signage questionnaire form
consists of two sets of warning signs
i.e., dynamic and static warning signs.
In dynamic warning signs when avehicle is detected by the sensor,
warning light starts blinking andmessage will be displayed. In static
warning signs when a vehicle isdetected by the sensor, only warning
light blinks and message was alreadydisplayed. Four different warning
signs were designed for bothdynamic and static, and participants
were asked to rank the signs frombest to worse. Figure 12-5 represents
the image of a signage questionnaireform.
A ranking analysis was carried out toidentify the best warning sign basedon the ranking order provided bydrivers in the signage questionnaire
form. Borda count method wasconsidered to evaluate the rank data.
In the dynamic warning signboard,the ﬁrst sign got more points, which
has a LED light and message to bedisplayed as ‘ENTERING TRAFFIC’,and a sign symbol representing
a four-legged intersection withvehicles approaching on theminor road. For static sign warning
signboard, second sign got morepoints, which has a LED light andmessage displayed as ‘LOOK FOR
ENTERING TRAFFIC’ and sign
symbol representing intersection withthe direction of approach of minor
road vehicles. Further, a question
was asked to select either dynamic
or static signs that they think moresuitable. 78% of drivers opted for
dynamic signboards explaining that

Chapter 12
Behaviour Change by Traffic Information

Figure 12-4 Average speed proﬁles of drivers for different scenarios(a) Scenario 1 (b) Scenario 2 (c) Scenario 3 (d) Scenario 4

Centre of intersection

Centre of intersection
50

Mean speed (km/h)

Mean speed (km/h)

504040303020050510 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125

Distance (m)Distance (m)

(a)

(b)

Centre of intersection

Centre of intersection

40

45

Mean speed (km/h)

Mean speed (km/h)

55

10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125

35251530

20100510 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125

05

10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125

Distance (m)Distance (m)

(c)

(d)

Figure 12-5 Signage questionnaire73Handbook of Multimodal Transport for Smart City
Application of Sensing, Networking and Big Data Analysis

the activation of LED light blinking
and display of message when they
approach the intersection attracts
their attention to the signboard andmake them more cautious.

Conclusions
The chapter analyzed the responsesof major road drivers towards theconﬂict warning system installed ata typical four-legged uncontrolledintersection. Results indicate astatistical difference among four
scenarios for mean speed andmean acceleration was observed.
The average mean speed ofdrivers for scenario 4 was lowered by
6 km/h compared with scenario 2.
This implies that the drivers after
being educated by the warning
system could result in lower mean
speed because drivers were alert
about the approaching vehicle andresponded before they approached
the intersection. A post signage
questionnaire form results show apositive response from drivers sayingthat the warning system would be
helpful in reducing collisions atuncontrolled intersections.

the movement of vehicles resultsin congestion and an increase in
more fuel consumption and CO2
emissions will be observed. With
the help of ICWS we can reduce
accidents, traffic congestion, CO2
emissions and ensure safe travel ofpeople on road. ICWS also avoids
sudden braking behaviour of drivers
which results in reduction in COF
emissions. When driver applies
sudden braking behaviour a numberof deceleration events takes place
which can increase fuel consumption
and CO2 emissions.

When an accident takes place atintersection there will be a delay in

Reference[ 1 ] Ministry of Road Transport and Highways: Road accidents in India 2019. 197pp, 2020.

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