Heterogeneous Traffic Safety Models
Heterogeneous Traffic Safety Models
INTRODUCTION
Two basic parameters of traffic flow which influence the safety of road users are traffic
volume or flow measured in terms of number of vehicles per unit time and traffic
speed. The amount of traffic, often called traffic flow or more general exposure, is
often treated as a matter of routine. Relationship between accidents and flow is,
therefore, often assumed to be a simple (linear) relationship. One major reason could
72/ Injury Prevention and Control
depending on
the degree of
heterogeniety Figure 1Speed flow relationship (May, 1990)
in the traffic
mix, fatalities As number of vehicles increase on a network, speed remains constant
and injuries as long as the flow is below a certain value. This condition is defined
may decrease as level of service A. Speed reduces gradually until the flow reaches
even if the capacity. Consider this relationship with the relationship of speed
and fatalities and injuries shown in Figure 2. The estimates for
exposure of probability of pedestrian deaths at different impact velocities are: 5–
vulnerable 8 per cent at 30 kph, 25 per cent at 40 kph, 45–80 per cent at 50 kph,
road users and more than 85 per cent at 60 kph (European Transport Safety
increases Council, 1995; University of Zurich and Swiss Federal Institute of
Tiwari /73
Technology, 1986.) For car occupants in crashes at 80 kph the likelihood of death is 20
times more than at 32 kph (IIHS, 1987). Clearly, increase in speed is associated with
disproportionate increase in number of fatalities. Also, the safe speed for car occupants is
much higher than for the pedestrian and bicyclists.
Speed influences energy consumption, pollution, noise, vehicle and road maintenance
costs, stress on road users and safety. In general, higher speeds have an adverse influence
on all these factors. The safety of road users is influenced both by the absolute speed of
vehicles and by the variation in speeds among vehicles on the road (Noguchi, 19**).
Other factors remaining constant, higher speeds increase the probability of a crash taking
place and the severity of injury in a crash, whereas a greater variations in speeds of
vehicles only increases the probability of the event. As illustrated in Figure 2, small
reductions in travelling speed result in large reductions in injuries and fatalities in both
urban and rural areas. This is because the stopping distance of a vehicle under braking is
proportional to the square of the original velocity and the damage to human beings is
related to the square of the impact velocity. Lower initial speeds means that the driver
has better control on the vehicle and the vehicle can stop much earlier and reduce the
probability of a crash. In the event of a crash the injuries are less severe at lower impact
velocities.
Probability of pedestrian fatality
Impact of speed km
Figure 2 Speed and pedestrian fatalities
The relationship between flow, speed and fatalities requires further consideration in
the case of mixed traffic and vulnerable road users. A heterogenous traffic mix has an
effect on traffic safety, specially traffic fatalities. Figure 3 shows the distribution of the
percentage of non-motorized vehicles (NMV) fatalities versus the percentage of motorized
vehicles (MV) trips comprising the location’s modal split (Fazio and Tiwari, 1995).
Theoretically, no NMV fatalities can result from a striking MV at the origin on the graph
because no MVs exist in the traffic stream at this point. When MVs account for 100 per
cent of the trips, no NMV fatalities occur because of the absence of NMVs in the traffic.
Presence of NMVs also has a calming effect on traffic speed. Data from Delhi also show
that as NMV flow increases, the average speed difference between MVs and NMVs
decrease specially on roads where mixing of MV and NMV takes place (high conflict
between MV and NMV). As the speed difference or initial speed reduces, number of
fatalities and injuries reduce. Therefore, depending on the degree of heterogeniety in
the traffic mix, fatalities and injuries may decrease even if the exposure of vulnerable
road users increases.
Models which predict number of fatalities, injuries and accidents based on a linear
relationship with motorization or flow are inappropriate if they do not include speed
implications. Rate of fatalities would depend on how the increased flow affects mean
speed of the traffic stream as well variation of speed of the traffic stream. The modal
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Western Europe
Southern Europe
Northern Europe
Eastern Europe
models which Europe
fatalities,
Eastern Asia
Regions
Asia
accidents
Northern America
Central America
based on a Caribbean
American
motorization 0 5
Africa
10 15 20 25 30 35 40 45 50
the pover ty line, 29–60 per cent (Figure 5). Therefore, the demand for non-motorized
modes and pedestrians on highways and urban areas is inevitable.
Venezuela
Mexico
Guatemala
El Salvador
Colombia
Brazil
Latin America
Sri Lanka
Pakistan
Country
Nepal
Indonesia
India
Bangladesh
Asia (including China)
Zambia
Swaziland
Morocco
Gambia
Cote d’lvoire
Africa
0 10 20 30 40 50 60 70
Percent
Figure 5 Population below poverty line
Urban areas in developing countries experience such extremes of wealth and poverty
that they can be characterized as having dual economies. One serving the needs of the
affluent and featuring modern technologies, formal markets, and outward appearance
of developed countries. The other serves disadvantaged groups and is marked by
traditional technologies, informal markets and moderate to severe levels of economic
and political deprivation (Dimitrou, 1990).
Urban poverty, characterized by unemployment, dependence on the informal sector,
low wages and insecure jobs, has a direct bearing on travel and transport demand of a
large segment of the population residing in urban areas. Their dependence on transport
which enables them access to job markets becomes essential for survival. This need is
more critical for them than for those with high income and secure jobs. However, this
segment of population is also transport poor. Even a subsidized public transport remains
cost prohibitive for them.
Cities in developing countries are characterized by heterogenous traffic (mix of
non-motorized and motorized modes) and mixed land-use patterns. Non-motorized
vehicles are owned and used by a large section of the population (Figure 6).
Note: Animal carts & buses are negligible
Tokyo
George Town
Chiang Mai
Metro Manila
Surabaya
Shanghai
Kanpur
Dhaka
Hanoi
Phnom Penh
0 200 400 600 800 1000 1200
Number of vehicles per 1,000 population
Table 1 gives selected indicators for a few Indian cities. Regardless of city size, it
sho ws that nearly 40–60 per cent of households ha ve monthly incomes of
approximately US $50–60. In large cities like Mumbai, Delhi, Chennai, more than
60 per cent of people are employed in the informal sector. F or this population walking
and bicycling to work is the only mode of transport available. Assuming a minimum
of 4 trips per household per day at the cost of Rs 2 (US$ 0.05) per trip by public
transport, a household would need to spend Rs.320 (US$ 8) per month on transport.
For low-income people living in the outskirts of the city, the cost per trip may be two
or three times this amount depending on the number of transfers. On an average,
low-income households canno t spend more than 10 per cent of its income on
transpor t. This implies that a household’s income must be at least Rs.3200 (US$ 80)
to be able to use the public transport system at minimum rates. According to a
survey (ORG, 1994), approximately 28 per cent of households in Delhi ha ve a
monthly household income of less than Rs.2000(US$ 50).
Table 1
Indian city indicators
INDICATOR MUMBAI DELHI MADRAS BANGALORE LUCKNOW V ARANSI HUBLI / MYSORE GULBARGA TUMKUR
DHARWAD
Population(million)
10.26 8.96 5.65 4.47 1.8 1.08 0.68 0.7 0.33 0.19
Household Income Distribution (Quintile Boundaries US $)
I (poorest 20%)
374 290 347 385 291 268 284 373 258 287
V (richest 20%)
2497 3292 2781 2487 2181 2084 2009 2372 1951 1761
Informal Employment(%)
68 66 60 32 48 49 31 31 27 63
Motorized Vehicles(per 1000 pop.)
51 205 102 130 130 85 49 123 60 63
Data from: Society for Development Studies, Delhi
Sur vey results show that nearly 60 per cent of respondents find the minimum
cost of work trips by public transport (less than Rs.2 per trip) unacceptable (CRRI,
1988). Even at minimum costs, public transport trips account for 20 to 30 per cent
of family income for nearly 50 per cent of people living in unauthorized settlements.
This segment is very sensitive to the slightest variation in the cost of public transport
trips.
The data above show that an estimated 30 per cent of the world population living in
urban poverty in cities of developing countries is transport poor. In this segment it is
harder for individuals and households to save and build up assets, and reduce their
vulnerability to sudden changes/loss in income. Low incomes also make it difficult for
households to ‘invest’ in social assets such as education that can help reduce their
vulnerability in the future. Therefore, access to affordable transport is necessary for
survival. A sustainable transport system must meet the demand of this captive ridership
of non-motorized transport existing in the cities of the South.
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pollution. However, the informal sector is an integral part of the urban landscape
providing a variety of services at low costs, at locations with high demand for these
services. Many view hawkers, pavement shops, cycle and motor vehicle repair and
spareparts shops as unauthorized developments along the road that reduce the capacity
of the planned network. However, since the market demands these services, they
continue to exist and grow along arterial roads as well. It is quite clear that long term
land-use transport plans must address the needs of the informal sector.
Most developing country cities have been classified as ‘low cost strategy’ cities
(Thomson, 19 77). In comparison with cities in the West, these cities consume less
transport energy. High densities, intensely mixed land-use, short trip distances, and
high share of walking and non-motorized transport characterize these urban centres
(Newman and Kenworthy,1989) .
Heterogenous traffic flow consists of modes of varying dynamic and static
characteristics sharing the same road space. Underlying concepts of traffic flow theory
in the US, Europe, and Australia are formed by motorized four-wheel road way traffic
dominating in those areas, i.e., homogenous traffic. All car following, lane changing
logic and system’s measure of effectiveness used in microscopic simulation programmes
ultimately use field data from these countries for caliberation.
In LMC cities, the road network is used by at least seven categories of motorized
and non-motorized vehicles. Vehicles ranging in width from 60 to 2.6 m, and capable
of maximum speeds ranging from 15 to 100 kph, share the same road space. All these
vehicles which have varied dynamic and static characteristics share the same carriageway.
This traffic is characterized by lack of any effective channelization, mode segregation
or control of speeds. To the formally trained planner it looks like chaos moving towards
total gridlock. Yet people and goods keep getting through. And may, by some measures
actually be doing better than in some controlled conditions.
In Delhi different traffic modes are not segregated and there is minimal enforcement
of speed limits. In this situation flow patterns result in a natural optimization of road
use due to self organization by road users. Though aggregate conflict data do not correlate
with fatalities, our data show that Delhi has high number of VRU fatalities. Therefore,
segregation and traffic calming techniques developed for Delhi conditions with special
reference to motorized two-wheelers are desirable. Techniques developed in HMCs do
not address the high volume of motorized two-wheelers and large variations in traffic
composition from site to site.
The peak hour motor vehicle flows in traffic with mix of MVs—cars, buses, two-
wheeler scooters, three-wheeler scooter— have been observed to be very high compared
to homogenous traffic sites of similar street width (Fazio et al., 1998). Having vehicles
of narrow widths in the traffic stream greatly increases the capacity of streets. Narrow
vehicles fill-in the lateral and longitudinal gaps between wide vehicles; heterogenous
traffic uses on-street space more efficiently than homogenous traffic (Figures 8, 9 and
10). Homogeneous traffic flow is modeled on the basis of lane discipline logic. An
ideal lane capacity is estimated of only passenger cars by using passenger car units or
equivalents.
For heterogenous traffic, having an ideal capacity by lane is mis-conceptual because
lane discipline is very loose. Vehicles have varying static and dynamic characteristics.
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These share the same road space and move by sharing the lateral
as well as the linear gaps. For example, a motorcycle rider judges
whether the lateral distance (width) between a motor scooter and
bus is acceptable to progress on the roadway. Another motorcycle
rider in the same situation would have a different critical width
acceptance. If the width is unacceptable, then an entity is
constrained by preceding entities. Critical width acceptance
depends on three items. First, the travel speed of the vehicle/
entity itself. The next item is the physical width of the vehicle.
Distribution of the width acceptances of specific entity groups is
the third item, i.e., driver/rider/pedestrian behaviour. Each
vehicle/entity group has its own critical width acceptance.
Heterogeneous traffic can have many motorized two-wheelers,
motorized three- wheelers, bicycles, non-motorized three-wheelers,
cars, buses, trucks, animal-drawn carts, and human-powered push
and pull carts. Additionally, if sidewalk facilities are inadequate
or lacking, this diverse mixture contains significant on-road
pedestrian traffic. In homogeneous traffic, traffic entities form
one-dimensional queues (Figure 8); in heterogeneous traffic, mass
queues develop. These queues grow lengthwise as well as laterally.
Lane
discipline is
deficient in Homogeneous traffic has one dimensional queues Heterogeneoustraffichastwodimensionalormassqueues
heterogenous Figure 8Queuing theory
traffic not
because The ‘car following’ notion used in homogeneous traffic flow
driver models is not applicable in heterogenous traffic (Figure 9). Since
behaviour is cars do not comprise most of the traffic mixture, ‘car following’ is
significantly an incorrect term for heterogenous traffic. Secondly, since width
of entities vary greatly in heterogenous traffic, figuring out which
different, but leading entity/vehicle it is following is difficult. Leading entities
because may run parallel or staggered.
heterogeneous
traffic
consists of
entities of Homogeneous traffic has lane discipline
various
widths and
varying
dynamic Heterogeneous traffic has parallel/staggered entity-following
characteristics Figure 9 Car following
Tiwari /81
Professionals have extensively derived models and algorithms from the ‘lane
changing’ notion of homogeneous traffic (Figure 10). Microscopic studies of this traffic
shows that the time headway between vehicles is an important flow characteristic that
affects safety, level of service, driver behaviour and capacity of a transportation system.
A minimum time headway must always be present to provide safety in the event that the
lead vehicle suddenly decelerates. The percentage of time that the following vehicle
must follow the vehicle ahead is one indication of level or quality of service. The
distribution of time headways determines the requirement and the oppurtunity for
passing, merging, and crossing. The capacity of the system is governed primarily by the
minimum time headway and the time headway distribution under capacity-flow
conditions.
Clearly, underlying these concepts is the notion of lane discipline or lack of it.
Lane discipline is deficient in heterogenous traffic not because driver behaviour is
significantly different, but because heterogeneous traffic consists of entities of various
widths and varying dynamic characteristics. With homogeneous traffic, the width range
is approximately 2.1 m for cars to 2.6 m for trucks and buses. Homogeneous traffic
drivers find it optimal and advantageous to adopt lane discipline to traverse the roadway
space given the narrowness of the width range. For heterogeneous traffic, the width
range is approximately 6 m for pedestrians to 4.9 m for overburdened truck trailers.
Drivers, pedestrians, riders and animals find it optimal to advance by accepting lateral
gaps (widths) between preceding entities. Heterogeneous traffic uses road space more
efficiently than homogenous traffic. For this traffic, models based on width acceptance
can ultimately produce a good estimate of roadway capacity and assessments of
operations and safety of various facility designs.
This specific characteristic of heterogeneous traffic highlights the limitations of
conflict technique which has been developed for homogeneous traffic (Tiwari G e t
al.,1998). There are very few detailed studies on traffic patterns and their influence on
accidents in LMCs. We use here a study conducted in Delhi which involved conflict
analysis for prediction of fatal crash locations. Peak hour traffic at fourteen selected
locations were videotaped. Trained observers recorded traffic compositions at mid-
block, average space, mean speeds by mode and conflicts by type, reactor mode and
cause mode. The study showed a weak crash-conflict association. Definitions of conflict
developed in HMCs where motorized vehicles are the dominant modes are inadequate
in heterogeneous traffic situations like Delhi. In heterogeneous traffic streams, bicyclists,
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U.S.A. (1995)
people do
not have
Delhi, India (1994)
access to
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Table 2
Vehicle Registration and Proportions
US $ /1,000 PERSONS
Japan 34 630 640 20 58
USA 24 780 740 2 88
Germany 23 980 570 9 89
France 23 420 520 10 87
UK 18 340 410 3 86
Australia 18 000 610 3 76
Republic of Korea 8 260 206 24 33
Malaysia 3 140 340 56 34
Thailand 2 410 190 66 16
Philippines 950 32 26 28
Indonesia 810 58 69 15
Sri Lanka 600 50 60 13
China 530 21 40 24
India 320 30 67 14
Vietnam 210 27 91 9
These figures suggest two different phenomena that are relevant to road safety policies.
It appears that total vehicle registration levels remain below 100 per thousand persons in
countries that have per capita incomes of less than US $ 1,000 and that motorcycle
registrations decrease belo w 20 per cent of the total vehicle fleet only when per capita
incomes are much greater than US $ 8,000. The only exceptions are countries like China
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paratransit modes thus serving a useful role in the context of existing social system
(Tiwari, 1994).
In HMCs a very large proportion of the population owns motorized vehicles.
In addition, these countries can afford to have roads parallel to expressways to be
used by local traffic and vehicles not allowed on expressways. In many LMCs
highways run through rural areas with high density populations where most people
do not have access to motor vehicles. Also, many expressways in LMCs do not
have parallel road links for slow and non-motorized traffic. This forces slow and
non-motorized traffic to use expressways and to cross them illegally where that
majority of the victims of road accidents on intercity highways are the vulnerable
road users.
FUTURE DIRECTIONS
Various road users have different and often, conflicting requirements. Motorized
vehicles need clear pavements and shoulders, while bicyclists and pedestrians need
shaded trees along the pavement to protect them from the summer sun. Owners
of private transport modes like MTW and automobiles prefer uninterrupted flow,
fewer stops and minimum delays at intersections, whereas public transport buses
require frequent stops for picking and discharging passengers. Motorized four-
wheeled vehicles like cars, buses, etc., perform better if they move in queues with
minimum braking and acceleration. Since our infrastructure design does not
account for the existing conflicting requirements of different modes, all modes
have to share the road space and operate in sub-optimal conditions.
Experience of past decades of long-term integrated land-use transport plan
exercise suggests that the existence of informal sector and their travel needs must
be recognized for preparing effective plans. This should encourage mixed land-use
patterns and transport infrastructure especially designed for bicycles and other
non-motorized modes.
Future traffic models must account for the users of different transport modes
having conflicting requirements. These models must account for the needs of
motorized vehicles for clear roads for uninterrupted traffic flow, at the same time
they must address the needs of bicyclists and pedestrians for shady trees, kiosks
for drinks, food and bicycle repair shops, etc., at shorter distances. Highway
planning standards provide for services needed by motorized vehicle users. However,
there are no standards for providing services needed by NMT. These services
mushroom along urban or inter-city highways to fulfill the demand of road users,
however their existence is viewed as ‘illegal encroachment’ on the designed road
space.
Motorized vehicles are designed to operate at much higher speeds for better fuel economy
and emission levels. Roads are also designed to increase throughput of motorised vehicles
only. These measures decrease safety of NMV occupants and pedestrians sharing the same
road space. Therefore, safe facilities—segregated lanes, convenient crossing opportunities
from the point of view of NMV users should form an integral part of the road designs. At
present these facilities are viewed as cost increasing measures which many developing
countries cannot afford due to resource crunch.
Urban streets passing through the commercial development and highways
passing through small towns serve multiple purposes. They carry through traffic.
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REFERENCES
Tiwari G., Mohan, Dinesh and Fazio, J, 1998, Conflict Analysis for prediction fatal
crash locations in mixed traffic streams, Accident Analysis and Prevention, Vol.30,
No.2, pp. 207–215.
University of Zurich and Swiss Federal Institute of Technology, 1986, The Car Pedestrian
Collision. Interdisciplinary Working Group for Accident Mechanics (Zurich: Switzerland).
World Bank, 1995, Non-Motorised Transport in Ten Asian Cities, Report TWU 20,
(Washington, DC, USA: The World Bank: Washington DC).
World Resource Institute, 1996, World Resource: A Guide to the Global Enviroment .
(Washington,DC, USA: The World Resources Institute).