HIGHWAY SAFETY

Course code:CE480

Instructor:
Dr. Arpan Mehar
Assistant professor
NIT Warangal
Course Outcomes

Analyze highway safety by considering the effect of driver

CO1 characteristics, roadway characteristics, and climatic factors

CO2 Plan and design a road safety program

Analyze crash data and evaluate safety measures at

CO3
junctions and roads
CO4 Conduct road safety audit program on rural and urban areas
• Course overview:
– Introduction to safety - Accident characteristics and
factors: road – driver – vehicle-environment, safety aspects
of geometric design
– Statistical Interpretation Crash Data and Analysis - Accident
recording and statistical analysis
– Crash Reconstruction- Driver behavior and crash
“causality”, Crash reporting and collision diagrams, Before-
after methods in crash analysis
– Road Safety Audits - Safety Programs, Safety
Education, Traffic Law Enforcement.
– Safety management- Elements of highway safety
management systems, Safety countermeasures, Safety
management process, Road Safety Management System
– Mitigation Measures - Crash Facts, Exclusive pedestrian
signal phasing, Roadway lighting, pedestrian refuge islands
and curb extension.
• Reading and references:

– Institute of Transportation Engineers (ITE), The Traffic Safety Toolbox: A Primer

on Traffic Safety, ITE, 1999.
– Lynn B. Fricke, Traffic Accident Reconstruction, Northwestern University
Center for Public Safety, 1990.
– Ogden, K.W. Safer Roads: A Guide to Road Safety Engineering. Avebury
Technical, 1996.
– Rune Elvik and Truls Vaa, The Handbook of Road Safety
Measures, Elsevier, 2004.
– Leonard Evans, Traffic Safety, Science Serving Society, 2004.
– Ezra Hauer, Observational Before-After Studies in Road Safety, Pergamon
Press, 1997 (reprinted 2002).
– Simon Washington, Matthew Karlaftis, and Fred Mannering, Statistical and
Econometric Methods for Transportation Data Analysis, Chapman & Hall/CRC
Press, 2003.
– J. Stannard Baker, Traffic Collision Investigation, Northwestern University
Center for Public Safety, 2002.
– Lynn B. Fricke, Traffic Accident Reconstruction, Northwestern University
Center for Public Safety, 1990.
 Road accidents and Economy

• 1.25 million people killed each year, around

3000 deaths daily, 500 of them children
• 50 million people are injured in road crossing
every year, 15 million are seriously injured
• India loses $58 billion annually due to road
accident (UN study, 2016)
• India’s GDP takes a 3% hit every year due to
road accidents
In the Asia-Pacific, one person is killed on the road every 40 seconds, which means
15,000 lives per week.

UN study finds India is behind only Japan among the 19 countries covered in the Asia-
Pacific region regarding cost of road accidents
 Causes of accidents

• Road users
• Vehicle
• road and its condition
• Environmental factors
• Traffic Conditions
 Road users
•Drivers

•Excessive speed and rash driving

•Carelessness

•Violation of rules and regulation

•Failure to see or understand traffic situation

•Temporary effects due to fatigue , sleep or

alcohol
 Pedestrian related facts
• 46% of fatalities in Delhi

• USA-2/3 deaths of car occupants

20% pedestrian

• Age

• Sex

• Social condition

• Driving experience

• Familiarity with locality

• Drunken pedestrian
Vehicle factors
• Failure of brakes

• Steering system

• Lighting system

• Tyre burst

• Other defects
 Road and its condition
• Road design factors

• Inadequate sight distance

• Inadequate width and condition of
shoulders
• Improper curve design-
radius, superelevation
• Improper lighting
• Improper traffic control devices
• Medium width
 Road and weather conditions

• Slippery or skidding road surface

• Pot holes , ruts and other damaged condition of road surface

Unfavorable weather condition

• Mist,fog,snow,dust,smoke or heavy rainfalls-restrict normal

visibility

• Render driving unsafe

 Stray Animals on the road

.
 Other causes
• Incorrect signs or signal
• Gate of level crossing not closed when
required
• Ribson development
• Badly located advertisements boards or
service station etc.
• Narrow bridges and culverts
• Formation delineators and guard rails
 Accident statistics
• Road accidents in India, (The Indian
Express, 2017)
– 17 deaths on roads every hour (published by
Transport Research wing under Ministry of Road
Transport & Highways, GOI)
• As per the data cited in the report, the
country recorded at least 4,80,652 accidents
in 2016, leading to 1,50,785 deaths
• The number suggests that at least 413 people
died everyday in 1,317 road accidents.
 Accident data and Analysis

• Number and severity of accident

• Accident density per length of the road
• Interpretation of the statistical data
• Probability of accident occurrence
• Points of their clustering (BLACK SPOT) are
determined
 Accident Record
• Accident data collection
Data to be collected should comprise of following parameters:
• General info: Date, time, person involved in accident,
classification of accident like fatal, serious, minor
• Location: Description and detail of location of accident
• Details of vehicle involved -
• Nature of accident
• Road and traffic conditions
• Primary causes of accident
• Accident cost
 Relative safety measure
• Driver and Pedestrian
• Vehicle
• Roadway conditions

Accident rate provide a means of comparing the relative safety

of different highway, street system and traffic controls.

And, accident involvement by the type of drivers and vehicles

associated with accidents.

Accident rate reflects accident involvement by type of highway

 Accident risk and rate

• Accident rate (number of personal injury

accidents related to the number of vehicle-
kilometres)
• Accident density (number of personal injury
accidents related to the length of a road
section)
– Used in the field of black spot identification and
analysis, and for the comparison of accident risk
on different road categories.
• The relationship between traffic volume and
accidents can be expressed as follows

Where: Q = measure of traffic volume

a, b = constants
• For injury accidents b=0.911
• Then, there is nearly a linear relationship
between the frequency of accidents and the
traffic volume
• Therefore, increasing accident numbers can
express decreasing accident risk, if the traffic
volume has increased to a higher amount than
the number of the accidents.
 Parameters to evaluate accidents

• Accident Rate per Kilometre : (expressed as the number of accidents

of all types per km)

• Accident involvement Rate : (numbers of drivers of vehicles with certain

characteristics)
• Death rate based on population: (accident exposure)

• Death rate based on registration: (traffic hazard to life in a

Number of traffic fatalities per 10,000 vehicles registered community )
• Accident Rate based on vehicle-kms of travel:
(accident hazard, Number of accidents per 100 million vehicle km of travel)
• The Motor vehicle consumption in a city is 5.082 million
liters, there were 3114 motor vehicle fatalities, 355,799 motor
vehicle injuries, 6,721,049 motor vehicle registrations and an
estimated population of 18,190,238. Kilometer of travel per
liter of fuel is 12.42 km/liter. Calculate registration death
rate, population death rate and accident rate per vehicle km.
Highway Geometric design considering safety
 Horizontal curve at critical corner
• A horizontal curve is exist which joining two straight
stretches meet at an angle of 90 degree. The critical
corner of an important building (which can not be
moved) is located at (1495, 1469) near road alignment.
The location of PI is at (1500, 1500). The design speed on
the curve is 40 kmph. The bench mark point from which
the coordinates have been determined is at an upstream
point on the curve lies to the left of the building.
Determine the minimum radius of curve that will provide
for safe vehicle operation? Check whether the available
sight distance is safe enough for allowing overtaking on
curve. ?
 Vertical curves
• A parabolic curve that is
applied to make a smooth and
safe transition between two
grades on a roadway or a
highway
Geometry of Vertical curves
 Safety clearance problem

• A vertical curve is required to join a road with +3%

grade to a road with -2.5% grade. The design speed
of the road is 100 km/h. The VPI is located at
coordinates (1000,100). Further, the mid point of an
overhead electric transmission line of width 5 m
crosses the road at a distance of 1100 m and
elevation of 118 m. Determine the length of the
vertical curve so that a stopping distance of 180 m is
available. Also determine (i) location of VPC and (ii)
the minimum safety clearance from the transmission
line.
 ACCIDENT AETIOLOGY
• Herbert W. Heinrich was a pioneering
occupational safety researcher, whose 1931
publication Industrial Accident Prevention: A
Scientific Approach

• Developed the “five domino model”

represents an accident sequence as a causal
chain of events represented as dominos that
topple in a chain reaction.

• Heinrich is most famous for originating the

concept of the “safety pyramid”.

• 1 was based on the analysis of large

amounts of accident data collected by his
employer, a large insurance company.
• The fall of the first domino leads to the fall of the second, followed by the
third, etc., as illustrated below.

The domino model, as depicted by H. Heinrich in the 1950 edition of his book Industrial Accident
Prevention: A Scientific Approach

Accident prevention by interrupting the accident sequence, from the 1950 edition of the
book Industrial Accident Prevention: A Scientific Approach
• The sequence of accident factors is as follows:
– Ancestry and social environment
– Worker fault
– Unsafe act together with mechanical and physical
hazard
– Accident
– Damage or injury
• Heinrich proposed that:

– 88% of workplace accidents were caused by unsafe acts

(usually by the injured person);

– 10% of workplace accidents were the result of unsafe

equipment or conditions; and

– the remaining 2% were unavoidable.

 Road Accidents Prediction models
• The main objective for the studies was to establish
simple, practicable accident models that can predict the
expected number of accidents at urban junctions
and road links as accurately as possible. ...
 Identification of High Accident Locations
Identification of Accident prone location

• Locations which are hazardous as identified based

on accident experiences

• Locations and elements that are potentially

hazardous due to their geometrics or physical
features

• A location can be identified as hazardous by the

occurrence of an abnormal number, rate, or
severity of accidents over a given period of time
Time Period and Segment Length Considerations
Time Period Considerations
– Accident data for the most recent 1 to 3-year period is
normally used and is generally sufficient

– 2 or 3 year analysis periods are more appropriate at

locations with low traffic volumes, where a 1-year
period may not provide sufficient information

– Accident data should only be used when there are no

major changes in facility characteristics or land use
Road length Considerations
• The roadway network can be divided into spots
and/or segments

• Isolated curves, bridges, and intersections are

examples of spot locations

• Segments are typically defined by a particular

length (250 m, 0.5 km, 1.0 km, etc.) or as the
section of highway between two defined spots
 Segment and spot analysis
• When selecting a length for spots or segments, the following points
are considered:
– Segment (long roadway) lengths should not be shorter than the
minimum distance used by police officers to describe an accident
location

– For areas where accident reporting is subject to errors or less

accuracy (i.e., rural areas or areas where field reference markers
are far apart), longer segment lengths should be used for analysis
purposes.

– Spot (short roadway) lengths should include the area of influence

around a hazard. For instance, the analysis of intersections should
include all accidents that occur within a specified radius, such as
250 feet, from the centre of the intersection.
Methods for Identifying High Accident Locations

• Spot map method

• Accident frequency method

• Accident rate method

 Spot Map Method
• The map will show the spots or segments
having the greatest numbers of accidents. This
is an effective way to get a picture of the
accident clusters in small areas.
 Accident Frequency Method
• The frequency method ranks locations by the number of
accidents
• The location with the highest number of accidents is ranked
first, followed by the location with the second highest number
of accidents, and so on
 Accident Rate Method
• The accident rate method compares the
number of accidents at a location with the
number of vehicles or vehicle miles of travel at
a location
• The rate is stated in terms of “accidents per
million vehicles” for intersections (and other
spots), and “accidents per million vehicle-miles
of travel” for segments
• The locations are then ranked in descending
order by accident rate
 Accident Exposure
• The exposure at any location is the number of
vehicles that travel over a segment of roadway or
through a spot on the roadway, such as, an
intersection, segment
– Spot Exposure
The exposure at a spot, such as an intersection, is
measured by the total number of vehicles entering the
intersection for the period.
EXPOSURE (ENTERING VEHICLES) = ADT X 365 X YRS
– Section Exposure
The exposure over a roadway section is measured by
the total vehicle miles of travel over the section for
the period.
EXPOSURE (VEHICLE MILES OF TRAVEL) = ADT X 365 X MI X YRS
 Calculation of Accident Rates
• The accident rate for a location is found by dividing the
accident experience by the exposure:

Accident Rate = Accidents/Exposure

The equation for computing accident rate for a spot location is as follows:
 Case Study: High Accident Location Analysis
• Five roadway sections (A through E) identified as high-accident
locations based on the use of several identification methods. All
sections are on rolling terrain with moderate horizontal
curvature. The average accident rate for this class is 3.5
ACCS/MVM.
• Use Frequency method and Accident rate method for rating of
locations:
Identifying a Hazardous Location Using
Critical Crash Rate
• A common method of analysis involves the
determination of crash rates based on the
exposure data for the study site with apparent
high rates and several other sites with similar
traffic and geometric characteristics.
• An appropriate statistical test, such as the
expected value analysis is then performed to
determine whether the apparent high crash
rate at the study site is statistically significant.
• The critical crash rate method involves the
following expression.

The crash ratio of actual crash occurrence for the segment being
studied with respect to the critical rate is determined.
Potential for Safety Improvement (PSI)
• An alternative method is that proposed by the
Federal Highway Administration which uses an
index that indicates the Potential for Safety
Improvement(PSI) at a location.
• The PSI can be determined for
fatal, injury, and property damage only
crashes separately and a combined index
(PSIindex) for the location determined by using
a weighting factor for different crash types.
• Safety Performance Function (SPF)
Determining Expected Long-term Crashes on a
Section of Highway
 Comparing Different Accident data

• The number of large-truck crashes that occur on 20-mile

segments of highways with DSL and USL with the same
AADT over a two-year period. Using the Kruskal-Wallis H-
test, determine whether it can be concluded that the
distribution of large-truck crashes are similar at the 5%
significance level.
• In order to assess whether there is any
relationship between the accident severity and
the age of drivers, an analysis of previous data
yielded the following:
Accident severity Age group of drivers

18-30 30-50 > 50

Fatal 12 8 16
Grievous Injury 25 14 41

Minor injury 48 35 70

• Test whether there is any significant relationship

between the accident severity and the age
 Parametric method for comparing accident data
• An engineer wishing to test whether large trucks are
significantly involved in crashes on rural two-lane highways
than on rural multilane highways ( in five years). Determine
whether it can be concluded that large-truck-involved crashes
on rural two-lane highways are significantly higher than those
on rural multilane highways at a significance level of 5%.

Sections are each of the same length, with similar large truck percentages, AADT, and posted speed limits.
One Sided 75% 80% 85% 90% 95% 97.5% 99% 99.5% 99.75% 99.9% 99.95%
Two Sided 50% 60% 70% 80% 90% 95% 98% 99% 99.5% 99.8% 99.9%
1 1.000 1.376 1.963 3.078 6.314 12.71 31.82 63.66 127.3 318.3 636.6
2 0.816 1.080 1.386 1.886 2.920 4.303 6.965 9.925 14.09 22.33 31.60
3 0.765 0.978 1.250 1.638 2.353 3.182 4.541 5.841 7.453 10.21 12.92
4 0.741 0.941 1.190 1.533 2.132 2.776 3.747 4.604 5.598 7.173 8.610
5 0.727 0.920 1.156 1.476 2.015 2.571 3.365 4.032 4.773 5.893 6.869
6 0.718 0.906 1.134 1.440 1.943 2.447 3.143 3.707 4.317 5.208 5.959
7 0.711 0.896 1.119 1.415 1.895 2.365 2.998 3.499 4.029 4.785 5.408
8 0.706 0.889 1.108 1.397 1.860 2.306 2.896 3.355 3.833 4.501 5.041
9 0.703 0.883 1.100 1.383 1.833 2.262 2.821 3.250 3.690 4.297 4.781
10 0.700 0.879 1.093 1.372 1.812 2.228 2.764 3.169 3.581 4.144 4.587
11 0.697 0.876 1.088 1.363 1.796 2.201 2.718 3.106 3.497 4.025 4.437
12 0.695 0.873 1.083 1.356 1.782 2.179 2.681 3.055 3.428 3.930 4.318
13 0.694 0.870 1.079 1.350 1.771 2.160 2.650 3.012 3.372 3.852 4.221
14 0.692 0.868 1.076 1.345 1.761 2.145 2.624 2.977 3.326 3.787 4.140
15 0.691 0.866 1.074 1.341 1.753 2.131 2.602 2.947 3.286 3.733 4.073
16 0.690 0.865 1.071 1.337 1.746 2.120 2.583 2.921 3.252 3.686 4.015
17 0.689 0.863 1.069 1.333 1.740 2.110 2.567 2.898 3.222 3.646 3.965
18 0.688 0.862 1.067 1.330 1.734 2.101 2.552 2.878 3.197 3.610 3.922
19 0.688 0.861 1.066 1.328 1.729 2.093 2.539 2.861 3.174 3.579 3.883
20 0.687 0.860 1.064 1.325 1.725 2.086 2.528 2.845 3.153 3.552 3.850
21 0.686 0.859 1.063 1.323 1.721 2.080 2.518 2.831 3.135 3.527 3.819
22 0.686 0.858 1.061 1.321 1.717 2.074 2.508 2.819 3.119 3.505 3.792
23 0.685 0.858 1.060 1.319 1.714 2.069 2.500 2.807 3.104 3.485 3.767
24 0.685 0.857 1.059 1.318 1.711 2.064 2.492 2.797 3.091 3.467 3.745
25 0.684 0.856 1.058 1.316 1.708 2.060 2.485 2.787 3.078 3.450 3.725
26 0.684 0.856 1.058 1.315 1.706 2.056 2.479 2.779 3.067 3.435 3.707
27 0.684 0.855 1.057 1.314 1.703 2.052 2.473 2.771 3.057 3.421 3.690
28 0.683 0.855 1.056 1.313 1.701 2.048 2.467 2.763 3.047 3.408 3.674
29 0.683 0.854 1.055 1.311 1.699 2.045 2.462 2.756 3.038 3.396 3.659
30 0.683 0.854 1.055 1.310 1.697 2.042 2.457 2.750 3.030 3.385 3.646
40 0.681 0.851 1.050 1.303 1.684 2.021 2.423 2.704 2.971 3.307 3.551
50 0.679 0.849 1.047 1.299 1.676 2.009 2.403 2.678 2.937 3.261 3.496
60 0.679 0.848 1.045 1.296 1.671 2.000 2.390 2.660 2.915 3.232 3.460
80 0.678 0.846 1.043 1.292 1.664 1.990 2.374 2.639 2.887 3.195 3.416
100 0.677 0.845 1.042 1.290 1.660 1.984 2.364 2.626 2.871 3.174 3.390
120 0.677 0.845 1.041 1.289 1.658 1.980 2.358 2.617 2.860 3.160 3.373
0.674 0.842 1.036 1.282 1.645 1.960 2.326 2.576 2.807 3.090 3.291
 Proportionality Test
• This is used to compare two independent proportions
• For example, it can be used to compare the proportion of fatal
and injury crashes at an unsignalized intersection with that at
signalized intersections
 Using the Proportionality Test for Significant Differences in
Crash Severity
• The number of fatal and injury (F& I) crashes and property damage only
(PDO) crashes that occurred over the same period at randomly-selected
unsignalized and signalized intersections with similar approach volumes
and geometric characteristics.
• Using the proportionality test, determine whether, based on this data
set, it can be concluded that the proportion of fatal and injury crashes is
significantly higher at unsignalized intersections than at signalized
intersections at a 5% significance level.
Z table
 Over-representation of Different Crash Type
• Expected value analysis is a mathematical method used
to identify locations with abnormal crash
characteristics.
• Locations with values higher than the expected value
are considered as over representing that specific type of
crash. The expected value can be obtained from the
expression:
 Determining Overrepresentation of Different Crash Type
• Data collected for three consecutive years at an intersection
study site show that 14 rear-end collisions and 10 Right-turn
collisions occurred during a 3-year period. Data collected at 10
other intersections with similar geometric and traffic
characteristics. Determine whether any type of crash is
overrepresented at the study site for a 95% confidence level
 Regression Method
• Expected number of accident on certain road
system during given time period is dependent
in a liner way on the factors which are
supposed to be significant
• Number of accident on a certain day is
assumed to be normally distributed with a
mean (linear fun. variable) and variance
(constant)
• Some of the regression variables that could be
considered are;
– 2W involvement
– Estimated vehicle mileage travelled in darkness
– Volume
– Cost of safety improvement
– No/. Of pedestrians
– Pavement width
– No. of Junctions per km
– Curvature
 Poisson Distribution method
• This distribution of very appropriate for
accident analysis because accidents are
governed by the law of chance
Prob.
• It is observed that on an average, a vehicle
driver drives 5000 km during the course of a
year. The probability of having an accident is
100 per 200 million vehicle-km. What is the
probability of a driver having at least two
accidents during his driving career extending
to 25 years.
• The accident records for three consecutive
years at an uncontrolled junctions indicate the
following number of accidents:

Years No. Of accidents

1972 3
1973 6
1974 9
– Calculate the probability of 4 accidents accruing
per year at the site.