Article
citation information:
Caban, J., Droździel, P. Traffic congestion in
chosen cities of Poland. Scientific
Journal of Silesian University of Technology. Series Transport. 2020, 108, 05-14. ISSN: 0209-3324. DOI: https://doi.org/10.20858/sjsutst.2020.108.1.
Jacek CABAN[1],
Paweł DROŹDZIEL[2]
TRAFFIC
CONGESTION IN CHOSEN CITIES OF POLAND
Summary. The dynamic development of motoring observed in the
last two decades contributes to many negative
phenomena occurring in road transport. Distinguished among these negative
phenomena are high share of car traffic, road accidents, emission of toxic
exhaust fumes into the atmosphere, etc. For these reasons, many initiatives are
taken in the field of road transport management and city logistics. Traffic
problems are solved from many aspects, such as the development of transport
infrastructure, changing of urban transport organisation, parking organisation
in city centre and Park & Ride system, as well as the progress of
alternative means of transport. The problem of traffic congestion in urban
areas is still a current topic. This article presents the formation of
congestion in urban areas in chosen big cities in Poland. The first part of the
article deals with the theoretical issues of traffic flow and congestion formation
in the city road networks. The second part of the article outlines the
situation of transport congestion with these cities based on the worldwide
TomTom Traffic Index within the period of 2008-2016. This study is a brief
analysis of the trends relating to the transport congestion based on the TomTom
Traffic Index in Polish cities, which will allow future researchers a wider
study of this problem. The authors suggest some solutions to reduce the level
of transport congestion and harmful emissions from means of transport.
Keywords: city logistics, TomTom Traffic Index, traffic
congestion
1. INTRODUCTION
Transport plays a crucial role in the economy
and life of people. Transport infrastructure stimulates the development of the
entire economy and creates conditions for its proper development [19, 26].
Transport accessibility of the region is one of the factors that intensify its
development [19]. The dynamic development of individual motorisation observed
in the last two decades contributes to many negative
phenomena occurring in road transport safety and negative impact on air quality
in agglomerations. Environmental impacts of transport are unfavourable and they
often have unavoidable character [28]. One way to reduce pollution production
is to operate more environmentally friendly vehicles [17, 18, 30] or used alternative fuels for supply internal combustion
engines [5]. The problem of road transport safety is a constant issue
undertaken by the scientific community, as evidenced by numerous publications
in this area: [2, 3, 7, 9, 11, 13, 20-22, 25, 29, 32, 36].
Car travel is related to climate change, depending on fossil fuels, and traffic
congestion [8]. Extending travel time caused by decreasing the average vehicle
speed, unfavourable weather conditions (high ambient temperature, icing or
intense snowfalls) adversely affect the psycho-physical state of the driver,
and consequently, may lead to wrong decisions and situations of danger (traffic
accident) [6].
Road traffic congestion is arguably the main problem
of the transport system [16]. Congestion causes global concerns, such as
increased commuting times and fuel usage as well as environmental deterioration
[35]. The negative effect caused by traffic congestions is most notable in the
largest cities, where traffic density is relatively high, with
characteristically low and often variable speed (acceleration and deceleration)
[24]. While there are considerable technological and policy opportunities for
tackling detriments associated with pollution from vehicle emissions and road
traffic accidents, congestion seems a more intractable challenge [16].
Understanding the process of traffic flow and detecting traffic congestion are
important issues associated with developing urban policies to resolve the
problem. Among the causes of traffic congestion, we can differentiate physical
and psychological factors. Physical causes measure traffic, speed and density
of the street. Psychological factors are more difficult to measure and each
driver accepts a different level of congestion. Some people accept slight
traffic congestion, whereas others do not, and this causes more stress for
them.
Traffic congestion is a complex
spatial-temporal process [12]. Congestion can be recurrent (regular, occurring
on a daily, weekly or annual cycle) or non-recurrent (traffic incidents, such
as accidents and disabled vehicles) [14]. Congestion in the urban zone can be
considered as a phenomenon on a local and global scale. Local congestion, such
as single interactions, only decreases the velocity of individual vehicles,
whereas global congestion often decreases the velocity of the overall street
network and requires additional traffic control [34]. William Vickrey
identified six types of congestion [34]:
• Simple
interaction on homogeneous roads: where two vehicles travelling close together
delay each other.
• Multiple
interactions on homogeneous roads: where several vehicles interact.
• Bottlenecks:
where several vehicles are trying to pass through narrowed lanes.
• “Trigger
neck” congestion: when an initial narrowing generates a line of vehicles
interfering with a flow of vehicles not seeking to follow the jammed itinerary.
• Network control
congestion: where traffic controls programmed for peak-hour traffic inevitably
delay off-peak hour traffic.
• Congestion due to
network morphology, or polymodal polymorphous congestion: where traffic
congestion reflects the state of traffic on all itineraries and for all modes.
The cost of intervention for a given segment of roadway increases through
possible interventions on other segments of the road, due to the effect of
triggered congestion.
As earlier mentioned, congestion in the urban
transport network is common in large agglomerations as well as in medium-sized
cities. This is a phenomenon characteristic of cities with a high level of
socio-economic development on all continents. In cities, we usually deal with a
large concentration of transport needs in time and space that occur with a
certain periodicity and is particularly severe in city centres. Transport of
cargos via small commercial vehicles within Central Europe is very popular [15].
Vehicles of this type limit visibility to other road users, take up a lot of
space and need to manoeuvre, which is particularly severe in crowded city centres.
Currently, the large possibilities of
increasing the capacity of traffic flow are due to the use of intelligent
transport systems for traffic control. In many countries of Central Europe,
intelligent transport systems operate with great success, similarly, in Poland,
an increasing number of cities implement these systems to improve the
efficiency of vehicle flow control. Many cities decide on alternative means of
transport (for example, city bike system, development
of a trolleybus network). Transport companies are considering investing in
hybrid vehicles. The possibilities of minimising fuel consumption and reducing
the emission of toxic compounds from hybrid public transport vehicles are shown
in [1]. However, in the works [4, 23, 27, 31], information can be found on
selected aspects of the operation of hybrid drives in passenger cars.
Increasingly, hybrid vehicles are used in taxi corporations and car-sharing
companies. Some local governments decide to invest in the Park & Ride
system and free public transport for people who have used the Park & Ride
system (for example, Katowice), or specially designated bus lane on the road
for an urban bus (for example, Warsaw and Lublin). Some of the cities
introduced a division into paid parking zones in the city centre with a diverse
tariff (for example, Lublin) and limits access to city centres for vehicles
powered by diesel engines (for example, Berlin).
2. SHORT ANALYSIS OF TRAFFIC CONGESTION
2.1. Methodology and data
The research methodology was based
on measurement tests Worldwide Congestion Ranking data TomTom Traffic Index
(TTTI) for 6 chosen Polish cities. The TomTom Traffic Index is published to
provide drivers, industry and policy makers with unbiased information about
congestion levels in urban areas [33]. The data for the analysis was obtained
from the TomTom Traffic Index reports, published on the website [33], for the
compared cities.
To avoid misunderstandings during
data analysis, the terminology used in the research should be presented and
defined. The definitions given below are based on TTTI and used in this paper.
World rank
of TomTom Traffic Index can be defined as the rank of the cities with a
population greater than 800,000 [33] and 2 million inhabitants, however, there
are data for smaller cities in the TomTom Traffic Index program, which do not
enter the global comparison. The ranking is based on the Congestion level
(extra travel time) [33].
Congestion level can be defined as an increase in overall travel times when compared to
a Free Flow (uncongested) situation [33].
Extra travel time can be defined as extra travel time during peak hours versus an hour of
driving during a Free Flow (uncongested) situation [33]. Multiplied by 230 days
for the annual figure.
Morning peak
can be defined as an increase in morning peak travel times when compared to a
Free Flow (uncongested) situation [33].
Evening peak
can be defined as an increase in evening peak travel times when compared to a
Free Flow in an uncongested situation [33]. The hours of morning and evening
peak may vary in different cities and depending on the day of the week. In most
cases, within the week, they are the same for the city in question.
Road network length is the total length of the evaluated road network, including highways
and non-highways expressed in kilometres or miles.
Live traffic delay is the current total time of delays in all jams on all monitored roads
in the city area.
Live traffic speed is the current average speed on all monitored roads in the city area
based on the TomTom Traffic Flow information [33]. The last two parameters
include highways and major roads and minor roads.
2.2. Comparison of the
TomTom Traffic Index in 6 Polish cities
This section presents the results of
research for 6 chosen Polish cities, these are Warsaw, Wroclaw, Cracow, Poznan,
Lodz and Szczecin. A characteristic feature of all Polish metropolises is a
dynamic increase in the level of motorisation of society and a decrease in the
volume of transport in public transport. Consequently, the number of cars per
capita and the intensity of street traffic is still increasing, leading to the
occurrence of congestion and a significant increase in travel time. According
to Eurostat data, in 2015, the motorisation rate in Poland amounted to 546 cars
per 1000 inhabitants, compared to 323 in 2005. This means that currently,
statistically more than every second Pole has a car.
The examination of occurrence of
congestion was based on the measurement of the speed of passage of particular
sections of roads, determined based on GPS data collected in real-time from
moving vehicles. For individual cities, average delays were calculated due to
congestion (extra travel time), the average speed of vehicles during
communication peaks on the entire road network covered by the survey (and
optimal traffic speed) and the largest bottlenecks were examined. The delay
indicator due to congestion was calculated in relation to the free passage time
without any difficulties. Historical data on congestion in the six largest cities
in Poland are included in Tab. 1.
When analysing the data presented in
Tab. 1, it can be stated that in 5 of 6 cities there was a reduction in the
level of traffic congestion. Unfortunately, only in two cities, Wroclaw and
Cracow, the level of congestion clearly decreased by as much as 12%. In other
cities, the level of congestion decreased by much smaller values. In Warsaw by
3%, Poznan by 6% and in Szczecin by 4%. In the case of Warsaw, a slow decline
in the level of congestion since 2011 can be observed. The largest decrease in
the congestion level in year-on-year terms was recorded in the cities of
Wroclaw and Cracow amounting to 13% in 2011.
The analysis of the data shows that
the worst situation is in the city of Lodz. Over the years, the level of congestion
increased from 47 to 51% in 2016, and the highest level of congestion was
recorded in 2014. In the case of Lodz, the positive aspect is only that
compared to the previous year in 2016, there was a decrease in the congestion
level by 3%.
Tab.
1
Congestion level history in compared cities
expressed in % by Extra travel time
|
City |
2008 |
2009 |
2010 |
2011 |
2012 |
2013 |
2014 |
2015 |
2016 |
|
Warsaw |
40 |
43 |
48 |
45 |
41 |
39 |
40 |
38 |
37 |
|
Wroclaw |
47 |
47 |
50 |
37 |
30 |
32 |
35 |
35 |
35 |
|
Cracow |
48 |
41 |
50 |
37 |
31 |
33 |
34 |
35 |
38 |
|
Poznan |
40 |
39 |
43 |
41 |
36 |
33 |
35 |
34 |
34 |
|
Lodz |
47 |
51 |
53 |
47 |
46 |
52 |
56 |
54 |
51 |
|
Szczecin |
28 |
26 |
27 |
28 |
29 |
24 |
27 |
26 |
24 |
Authors’ study based on [33]
During the analysed period, it can
be stated that only for one city (Szczecin), the situation regarding extra
travel time could be considered as stable. Szczecin is also a city in which the
level of congestion is clearly the lowest compared to other cities.
In Fig. 1 is presented the
congestion level for the compared cities in 2016, including morning peak,
evening peak, length of highways and non-highways (major and minor roads).
Fig. 1. Congestion level for
compared cities in 2016
Authors’ study based on [33]
As shown in Fig. 1, in all analysed
cities, the highest level of congestion is in the Evening Peak. The lowest
level of congestion is noticeable at highways; the reason for this situation
may be much higher throughput and definitely greater fluidity of the flow of
vehicles than on other roads. Only in Lodz, the situation is different, the
greater level of transport congestion occurs here on highways. Furthermore, as
can be seen in Fig. 1, for almost all of the analysed parameters, the largest
percentage level of transport congestion occurs for the city of Lodz.
In Fig. 2, is presented Extra travel
time for the compared cities in 2016. The presented
data show that the worst situation is in the city of Lodz and Warsaw. The
average additional time expressed in minutes is over 40 minutes. The lowest
level for these parameters was recorded in Szczecin.
Fig.
2. Extra travel time per day and year, for compared cities in 2016
Authors’
study based on [33]
In Fig. 3, optimal traffic speed level for
compared cities in 2016 is presented.
Fig. 3. Optimal
traffic speed level for compared cities in 2016
Authors’
study based on [33]
In all analysed cities, during
traffic congestions, there are average speeds of trips below the optimal
traffic speed (Fig. 3).
4. CONCLUSIONS
Congestion in urban areas is currently one of the most
pressing problems in transport [12]. The phenomenon of congestion is
particularly onerous for users of traffic (individual drivers, suppliers of
stores and institutions, couriers, etc.), and indirectly affects the well-being
of agglomeration residents as well (that is, noise, air quality).
With the current level of demand for transport and the
development of individual motorisation, the complete elimination of congestion
in cities seems to be impossible to achieve. Therefore, the commonly accepted
course of action is to bring traffic congestion to an economically justified
and acceptable level. Several measurements could significantly reduce
congestion in the city: the implementation of various telematics systems as
well as the correct setup and synchronisation of traffic light signalling at
intersections (that is, creating a “green wave”); increasing the
capacity of roads and construction of others; traffic regulation; limiting the
right of entry to certain areas or charging of the traffic within the city
areas [10]. The comparison of several selected Polish cities shows that it is
possible to reduce the level of traffic congestion in the urban area. Efforts
that are made by municipal authorities bring positive effects, however, it is
an ever-changing environment, susceptible to transport disruptions. Effective
management of traffic flow in the city is a very difficult and demanding task,
nonetheless, extremely necessary to modern agglomerations.
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Received 27.03.2020; accepted in revised form 10.06.2020
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