This paper attempts to understand the road pedistrian casaulties at various spatial location by the role of urban scale,density and land use.Various factors such as population,traffic,physical and local environment,types of road infrastructures and various socio economic environmental affects on the road pedistrian casaulties which are expressed graphically and with logistic data of paper study -- Daniel J. Graham and Stephen Glaister.The paper is somehow going to match with the present condition of kathmandu valley Nepal.A seperate subject of thesis matter can be with our present conditions.

1. Nabaraj Poudel
CRN: 014-1217,
M.S.C.(TEAM)
Spatial Variation In
Road Pedestrian
Casualties
The Role of Urban Scale,
Density and land use

2. Introduction
• Spatial Variability in road pedestrians
occurs when a quantity that is measured at
different spatial location exhibits a value
that differ across the location.
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3. Summary of paper
 Paper examines the role of urban scale, density and land use
mix on the incidence of road pedestrian casualties.
 The paper develops spatial model at disaggregate level
 Attempt to understand how nature of urban environment
with its associated traffic generation characteristics of local
environment have powerful influence on pedestrian
casualties.
 The incidence of pedestrian casualties and KSIs (Killed and
seriously injured)is higher in residential then in economic
zone.
 Quadratic relationship is found between urban density &
pedestrian casualties with incident diminishing in most
dense areas
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-- Daniel J. Graham and Stephen Glaister

4. 1.Spatial variation in pedestrian casaulties
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Source : UK DFT,STATS 19 DATA
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Resident
popn(000s)
Pedistrian
casaulties
Pedistrian
casaulties per
1000 residence
London 7177 17225 2.4
Greater
Manchester
2435 5114 2.1
West midland 2440 4880 2.0
West Yorkshire 2033 3863 1.9
Merseyside 1339 2678 2.0
South Yorkshire 1271 1525 1.2
Tyne and Wear 1010 1515 1.5
Non metropolitian
ward
31796 34976 1.1
England 49501 73526 1.5
Pedistrian casaulties in london of metro & non metropolitian ward,1999 & 2000

5. Spatial variation cont.
 This spatial variation in the incidence of pedestrian casualties may be due
to high level of population and traffic. As popn decreases corresponding
fall in pedestrian casualties.
 The table also shows broadly decreasing trend in casualty rate as city size
decreases and substantially lower rate for non-metropolitian areas.
 Spatial variation in the absolute number of pedestrian casualties is
proposed to be a function of six local factors:
 Absolute number of people: Higher people higher casualties.
 Volume of traffic flows: Higher traffic flows more likely casualties
 Physical nature of local environment: Large cities with more structures
 Characteristics of local road infrastructures: A & B Road, Minor & Major.
 Local socio-economic condition: Disadvantaged ,Car ownership, Garden
 Some other local specific factors: Weather condition(Rainy/sunshine)
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6. Spatial model of pedestrian casualties
 Trips generation in wards by proximate employment (PEi)
and Proximate population (PPi)
 Model estimation is done by using Poisson regression model
& Negative binomial model.
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∑
≠
=
ji
j
j
ij
x
d
E
iPE ∑
≠
=
ji
j
j
ij
x
d
P
iPP
jwardtoiwardfromdistance=ijd

7.  IMD: Index of multiple deprivation depend upon
income,employment,health/disability,education/skills,living environme-
nt ,crime,barrier to housing.
 X-cord:east , y-cord:south
 Large urban agglomeration in south east region of England.
01-01-2015Source : UK DFT,STATS 19 DATA
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Negative binomial model for pedestrian
casaulties & KSIs
Pedistrian casualties Pedistrian KSIs
Coefficient Elasticity Coefficient Elasticity
IMD Score 0.012 0.262 0.012 0.255
Rainfall 0.001 0.390 0.001 0.391
Sunshine
X-coordinate 0.001 0.227 0.001 0.540
Y-coordinate -0.001 -0.161

8.  More incidents are likely to take place where there are
greater supply of A roads but less where there is greater
supply of minor roads.
 Supply of motorways has no effects on KSIs.
01-01-2015Source : UK DFT,STATS 19 DATA
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Negative binomial model for pedestrian
casaulties & KSIs
Pedistrian casualties Pedistrian KSIs
Coefficient Elasticity Coefficient Elasticity
A-roads 0.028 0.108 0.044 0.168
B-roads 0.006 0.014 0.017 0.040
Minor roads -0.014 -0.347 -0.009 -0.219
Motorways 0.002 0.001

9. 01-01-2015Source : UK DFT,STATS 19 DATA
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Negative binomial model for pedestrian
casaulties & KSIs
 Quadratic relationship is found
 TPC & TKSI rises and reaches maximum at a popn of 25000 resident at
certain level and then reduces later from graph 1.
 More employment and residental activity also increse TPC &TKSI graph2

10.  Urban wards with high node density will tend to have more accidents then
with low density but later diminishes as ward become built up and suffer
from congestion, having lower traffic as shown in graph1.
 As pop density increases TPC & TKSI decreases. This negative relationship is
because the use and speed of vehicles are controlled by density of traffic
light,pedestrian crossing, road design and speed restriction shown in graph 2.
01-01-2015Source : UK DFT,STATS 19 DATA
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Negative binomial model for pedestrian
casaulties & KSIs

11. 01-01-2015Source : Nepal road safety action plan (2013-2020)
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Road traffic accident in different region of Nepal
-GON,Ministry of physical planning and transport mgmt

12. 01-01-2015Source : Nepal road safety action plan (2013-2020)
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Some finding of RTAs in Nepal:
 About half of the total RTAs nationwide occurs in kathmndu valley
 RTAs fatalities amongest the vehicle fleet (own/leased by business,gov
agency or organisation rather then by individual or family) are higher in
region outside kathmandu valley.
 Pedistrian are most vulnerable groups in road accidents because
pedistrian safety is not considered.
 People between 15 to 40 yrs.are most affected then above 50.
 Significant number of motorcycle accidnts in urban areas and Bus &
truck accident in Rural areas.
 About 30-40% of accidents happens after sunset when traffic is low
 From conservative estimate,the economic loss from RTAs of 2007 price
was Nrs 4.12 crore and 0.4% of GNP.

13. 01-01-2015Source : World Bank,Transport Road Safety, http://www.worldbank.org/
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 Every year more than 1.17 million people die in road crashes around the
world.65% death involve pedestrian, out of which 35% are children.
 It has been estimated that at least 6 million more will die and 60 million
will be injured during the next 10 years in developing countries unless
urgent action is taken.
 Also estimated that developing countries are loosing $100 billion each
year.
 The global burden of disease study undertaken by WHO, Harvard
university and World bank showed that in 1990,traffic crashes were
assessed to be world’s ninth most important health problem ad by the
year 2020 road crashes would move up to third place.
 Economic perspective on traffic safety: Government should see
expenditure on road safety as an investment and not as a cost.
Global issues

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 Where scale of population is larger, the incidence of pedestrian
casualties and KSIs is higher due to increased traffic and greater supply
of potential victims.
 Pedestrian casualty taking place is higher in residential then in
economic zones.
 For the most extremely dense ward population, there is decrease in
expected casualty rate due to effect of urban congestion.
 Employment density with increase in population in busy environment
increase pedestrian casualty rate, but that in the most extremely dense
economic environment there is a fall in incidence.
 Thus it can be seen that local characteristics related to urban scale,
density and land use do not have an effect on pedestrian casualties and
KSIs as many other factors are lumped together.
 This can usefully inform transport and land use planning policies.
Conclusion

15. Thank You
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