Intelligent Transport System and Transportation Planning in Oslo City

This project investigates the application of an Intelligent Transport System (ITS) for transportation planning in Oslo City. The study begins with a proposal outlining the aim, objectives, and research questions, focusing on understanding advanced ITS applications, feasibility in Oslo, and traffic management strategies. A literature review examines existing research on ITS, including emergency response systems, traveler information systems, and traffic management techniques. The methodology section details the research approach, philosophy, sampling methods (random sampling of 30 commuters), and data collection methods (primary via survey and questionnaire, and secondary via literature review). The results section presents the findings from the questionnaire, including mean, standard deviation, and mode for each question, revealing commuters' perspectives on the feasibility, limitations, and security aspects of ITS. The discussion of findings analyzes the survey results, highlighting commuters' belief in the feasibility of ITS for congestion control, awareness of technical limitations, knowledge of security hacks, and preference for ITS over traditional networks. The project concludes with a summary of findings, potential future work, and a list of references.

Intelligent Transport System And
Transportation Planing in Oslo City

Table of Contents
TOPIC..............................................................................................................................................1
1. PROPOSAL.................................................................................................................................1
Overview.....................................................................................................................................1
Aim..............................................................................................................................................1
Objectives....................................................................................................................................1
Question......................................................................................................................................2
Rationale of study.......................................................................................................................2
2. INTRODUCTION.......................................................................................................................3
Literature Review (500)..............................................................................................................3
3. METHODOLOGY......................................................................................................................3
4. RESULTS, READINGS AND FINDINGS.................................................................................4
5. DISCUSSION OF FINDINGS....................................................................................................8
6. CONCLUSION..........................................................................................................................11
7. FUTURE WORK.......................................................................................................................12
REFERENCES..............................................................................................................................13

TOPIC
“Transportation Planning in Oslo City”
1. PROPOSAL
Overview
Intelligent transportation network is the outrageous advancement which supports
innovative traffic management facilities to reduce congestion (Artificial Intelligence in
Transportation 2007). It is the invention which supports coordination of traffic which support
better and safe travel map. It is supported by digital society who believes to transform their city
in smart city.
Aim
“To plan intelligent transportation system: A case study on Oslo city”
Objectives
 To understand advanced application of intelligence transportation system.
1
Illustration 1: Intelligence transport system
(Source: Hamida, Noura and Znaidi, 2015 )

 To outline feasibility of intelligence transportation system in Oslo city.
 To ascertain traffic management via intelligence transportation system in Oslo city.
Question
 Explain advanced application of intelligence transportation system?
 Discuss feasibility of intelligence transportation system in Oslo city?
 How traffic management via intelligence transportation system will be done in Oslo city?
Rationale of study
The reason behind conducting this study is to gather knowledge for personal interest over
advanced application of intelligence transportation system which is the most effective and
advanced way of traffic management and transformation region into smart city. Further, the
study is conducted for academic purpose as it will help in gaining insights over need of transport
planning in Oslo city.
2
Illustration 2: Intelligence transportation system
(Source:Gentile and Noekel, 2016)

2. INTRODUCTION
Literature Review
Atzori, Iera and Morabito, 2010, designed and emergency response information and
management system for Oslo city, Norway. In this study a detailed GPS database and intelligent
database network, accident locations, ambulance, hospitals, police and fire-stations was prepared
and a spatial analysis is also carried out for the records of accident in past years. To find out the
shortest route, time saving roads and service areas were designed with a route finder.
Yu, R and et.al., 2013, proposed a similar GPS based on the emergency response
management system for Oslo city, Norway which provided a network based spatial analysis like
connectivity, finding paths, allocation, defining service areas and segmentation.
Allen, Browne and Holguin-Veras, 2010, developed a GPS based traveller information
system under the arc view GPS environment that enabled modules for shortest travelling routes,
the closest facility and city bus terminals and routes were incorporated in the system. The
developed system renders information about fundamental facilities in Norway city.
Parkes, S and et.al., 2013, described a real-time knowledge based system for decision
support in the assortment of integrated traffic control plans after happenings of non recurring
congestions. In this study information regarding intelligent transportation system that are most
effective and advanced traffic management and transformation of Oslo city is being developed.
3
Illustration 3: Intelligent transportation systems
(Source: Why are intelligent transportation systems important?, 2018)

Knowles, 2012, studied the use of GPS in traffic management and in their study
application of these intelligent transportation system was implicated in collecting traffic data
such as travel time, speed and delay on major roads in the Norway. Mean and variance of results
obtained by these study were compared and not much importance was reviewed. The intelligent
transportation systems found to be more efficient than manpower.
de Palma and Lindsey, 2011, incorporated the use of artificial intelligence and intelligent
transportation system techniques in managing traffic and rendered a multiagent structure for
intelligent traffic management systems. The systems were developed to perform decision support
for real time traffic management. The performance of both systems were evaluated and general
applicability of architectures for an intelligent transportation systems was given.
According to the study conducted by Davidrajuh and Lin, 2011, the efficiency of
intelligent transportation systems in Oslo city and in this study urban transportation systems,
socio-economic system and energy environment systems were taken as the input systems and the
road traffic management efficiency and urban transport indicators as the output systems. The
data of Oslo city were used for empirical analysis and the results showed that these intelligent
transportation systems improved the overall efficiency of Oslo city's transformation.
Attard, 2012, presented an emergency response management system based on intelligent
transportation system for Oslo city, Norway to provide useful information regarding various
facilities and optimum routes during emergency situations. In this study the probable risk zones,
accident prone roads were determined based on the use of land, building activities as per the
National Buildings Code guidelines. The efficiency and effectiveness of fire services were also
studied and based on this investigation intelligent transportation systems were developed.
3. METHODOLOGY
 Research approach: It is sequential process which helps the researcher in managing
systemic step wise process of investigating research topic. There are two type of
approaches that is inductive and deductive where in this study of transport planning
researcher will make use of deductive approach as it assist the individual in analytical
reasoning of findings and gathered research information.
 Research philosophy: It is the phenomenon of collecting, analyzing and using
information and outlined facts. There are different type of research philosophy that is
4

positivism, interpretisvism, realism etc. However, the study is based on positivist
philosophy as it supports use of scientific quantitative methods.
 Sampling: It suggests different type of method which helps the scholar in choosing small
sample for research. There are various type of sampling method that is probable,
stratified, non probable, random and cluster sampling. However, in this study the
investigator will make use of random sample which eliminates the risk of based results.
The sample of research will be 30 commuters.
 Data collection: This derives method for gathering relevant information with regard to
research topic. There are two data collection method that is primary and secondary where
in primary scholar is able to collect current and fresh information via interview, focus
group, surveys, etc. However, secondary information is facts and findings collected by
scholar in the past. This is gathered from governmental publication, books, Journals,
article, blogs, etc. Hence, in this study the researcher used both type of methods where
literature review is based secondary facts whole primary information is gathered via
survey and questionnaire.
 Data Analysis: It is the most critical and complex part of study where researcher outlines
findings with helps of analysis method. There are two data analysis method that is
qualitative and quantitative. In qualitative analysis research discusses on the basis of
themes in descriptive form. Apparently, in quantitative analysis scholar make use of
statistical tool such as SPSS. Thus, this study is based on numerical analysis for which
individual will be use of SPSS software to analyses significant relationship between
dependent and independent variables.
4. RESULTS, READINGS AND FINDINGS
Questionnaire
Name:
Age:
Gender:
1. Do you believe intelligent transport system is feasible for controlling traffic congestion?
 Yes
 May be
5

 No
2. Are you aware about the technical limitation associated with intelligent transport system?
 Yes
 May be
 No
3. Do you know any security hack which can assist in intelligence transport planning of Oslo
city?
 Yes
 May be
 No
4. Do you believe intelligent transport system is more effective than tradition transport network
of Oslo city?
 Yes
 May be
 No
5. Do you believe integration of Intelligence transport system and artificial intelligence will
help in traffic management of Oslo city?
 Yes
 May be
 No
Do you
believe
intellige
nt
transpo
rt
system
is
feasible
for
controll
ing
traffic
congesti
Are you
aware
about the
technical
limitatio
n
associate
d with
intelligen
t
transport
system?
Do you
know any
security
hack
which
can
assist in
intelligen
ce
transport
planning
of Oslo
city?
Do you
believe
intelligen
t
transport
system is
more
effective
than
tradition
transport
network
of Oslo
city?
Do you
believe
integrati
on of
Intelligen
ce
transport
system
and
artificial
intelligen
ce will
help in
traffic
6

on?
manage
ment of
Oslo
city?
Mean
1.54
8387
1 Mean
1.67
7419
4 Mean
1.58
0645
2 Mean
1.67
7419
4 Mean
1.7096
774
Standar
d Error
0.14
5459
7
Standard
Error
0.14
2082
Standard
Error
0.14
4982
Standard
Error
0.15
6487
6
Standard
Error
0.1619
342
Median 1 Median 1 Median 1 Median 1 Median 1
Mode 1 Mode 1 Mode 1 Mode 1 Mode 1
Standar
d
Deviati
on
0.80
9885
2
Standard
Deviatio
n
0.79
1079
3
Standard
Deviatio
n
0.80
7225
4
Standard
Deviatio
n
0.87
1286
3
Standard
Deviatio
n
0.9016
115
Sample
Varianc
e
0.65
5914
Sample
Variance
0.62
5806
5
Sample
Variance
0.65
1612
9
Sample
Variance
0.75
9139
8
Sample
Variance
0.8129
032
Range 2 Range 2 Range 2 Range 2 Range 2
Minimu
m 1
Minimu
m 1
Minimu
m 1
Minimu
m 1
Minimu
m 1
Maxim
um 3
Maximu
m 3
Maximu
m 3
Maximu
m 3
Maximu
m 3
Sum 48 Sum 52 Sum 49 Sum 52 Sum 53
Count 31 Count 31 Count 31 Count 31 Count 31
Theme 1
7

Theme 2:
Theme 3:
8
Yes May be No
0
2
4
6
8
10
12
14
16
18
20 19
5 6
Do you believe intelligent
transport system is feasible
for controlling traffic
congestion?
Yes May be No
0 2 4 6 8 10 12 14 16 18
16
8
6
Are you aware about the
technical limitation associated
with intelligent transport
system?

Theme 4:
Theme 5:
9
Yes May be No
0
2
4
6
8
10
12
14
16
18
20 18
6 6
Do you know any security
hack which can assist in
intelligence transport
planning of Oslo city?
Yes May be No
0 2 4 6 8 10 12 14 16 18 20
18
5
7
Do you believe intelligent
transport system is more
effective than tradition
transport network of Oslo
city?

5. DISCUSSION OF FINDINGS
Theme 1: Yes, commuters believe intelligent transport system is feasible for controlling
traffic congestion
In accordance with theme 1, it is implied that mean is 1. 67 which is approximately 2
which denotes that commuters believes that implementing intelligence transport system in
transport planning of Oslo city is feasible because it will assist in reducing congestion.
According to potential travelers it is derived that it will help the transport community in addition
and removing unnecessary bus lanes. Further, it will promote building o tunnels which will direct
diverge the range of commuters traveling from one route to another. Apart from this as per
survey, it is identified that ITS is feasible because it will help in establishing control over traffic
by predicting traffic situation for future days like, festivals, occasions, changing seasons and
climatic conditions. However, from the results and discussion of survey, it can be articulated
that commuters have supportive response to advanced application of intelligence support system
in Oslo city as it will help in managing safety and coordinated traffic.
10
Yes May be No
0
2
4
6
8
10
12
14
16
18
20
18
8
4
Do you believe integration of
Intelligence transport system
and artificial intelligence will
help in traffic management of
Oslo city?

Theme 2: Yes, majority of participants were aware about the technical limitation
associated with intelligent transport system
As per theme 2, it is identified that commuters believes are aware about technical
limitation of intelligence transportation system. As per the survey it is determined that potential
travelers believe that IT is effective application for traffic management but on the other hand it is
if no use without internet (Zenina, Merkuryev and Romanovs, 2017). There are various chances
where the application can face connection problems with server satellite which can further lead
to congestion and can hamper safety of traffic. As per average commuters that 1.67 it is denoted
that ITS is used for monitoring speed of traffic and helps in maintaining up to date information
of day to day traffic therefore in case if system suffers breakdown then the situation can lead to
traffics Jam which is the most risky situation and is a barrier to safety of the commuters of Oslo
city.
11
Illustration 4: Intelligent transportation
(Source: Budiman, Walukow and Makapedua, 2016)

Theme 3: Yes, average number of people know about security hacks which can assist in
intelligence transport planning of Oslo city
In accordance with theme 2, it is implied that commuters are aware about security hacks
of intelligent transport system which is the best part of knowledge because it supports advanced
planning of transport authorities and government. As per mean number of participants, it is
demonstrated that ITS is effective for controlling speed of vehicles which is the best aspect for
managing accidents and maintaining safety at cross walks and crashing. Further, according to
many participants it is identified that the best security hack of Intelligence of transport system is
reduction in road rage which is the major reason behind accidents, crashing and unsafe road
traffic. Likewise, from the survey it is outline that advanced application of transport management
is effective change because it will help in reducing risk of theft because the vehicle are controlled
by software and can be tracked anytime anywhere.
12
Illustration 5: Intelligent transport system
(Source: Grant-Muller and Usher, 2014)

Theme 4: Yes, commuters believe that intelligent transport system is more effective than
tradition transport network of Oslo city
On the basis of theme 4, it can be articulated that majority of commuters believe that
intelligence transport system is better than traditional transportation of Oslo city because it helps
in regular monitoring of traffic and individual vehicles on road. Further, it enables tracker with
vehicles which is the best source of tracking illegal or unethical traffic activities. On the other
hand the commuters implied about improvement in road building because the system needs one
time investment which is long term which denote its cost efficiency. Apart from this, respondents
discussed about flexibility in door to door services in Oslo city which will encourage
employment and logistic management of various industries. The respondents discussed about
limitation of traditional transport system of Oslo city from where it is determined that the route
are short but travel is time consuming. Thus, on the basis of survey it is can be concluded that
traditional transport system of Oslo city is the major cause of increasing environmental concerns
like global warning, red alarm., pollution which will be controlled by implementing intelligence
transport system.
Theme 5: Participants believe that integration of Intelligence transport system and
artificial intelligence will help in traffic management of Oslo city
In accordance with theme 5, it is identified that intelligence transport planning in Oslo
city can be supported by integration of artificial intelligence and ITS, as it supports automation
which eliminates the risk of human errors. ITS came up with technological capabilities which
promotes smart connection of vehicles via smart phone application (Addressing security threats
in intelligent transportation systems, 2016). As per commuters' integration of ITS and AI will
support monitoring of roadside network, toll collection, traffic management and CCTV cameras.
Thus, it can be outlined that AI and ITS together will help in deploying security measures,
information haring and indication of validation o routes.
6. CONCLUSION
The study summarized about intelligence transport system planning for Oslo city for
which scholar conducted survey of 30 commuters with the help of questionnaire which consisted
5 relevant question. The assessment outlined the security and reduction in congestion as two
foremost aspects of managing effective transport planning in Oslo city. Thus, it concluded by
determining views of potential travelers with the helps of statistical analysis. The analysis
13

suggested that planning and implementation of ITS will be effective and feasible of Oslo city, as
it will help in reducing congestion which is beneficial for managing sustainability in
environment factors such as pollution.
7. FUTURE WORK
In accordance with the study, it can be implied that research aspects and survey was
limited to intelligence transport system and planning for Oslo city. However, forth coming
studies can be focused on other traffic management software or integration of artificial
intelligence in transportation network of Oslo city because it supports Automation which
eliminates risk of human errors. On the other future study can be based on open interview
because survey limits information collection and discussion but in open ended interview the
scholar will be collect relevant and authentic view point of each and every participants which
supports findings and final outcomes. Thus, it can be summarized by stating that current studies
helped in gaining insight over transport planning for Oslo city by determining feasibility of
intelligence network which will be assist research in forthcoming similar studies.
14

REFERENCES
Books and Journals
Allen, J., Browne, M. and Holguin-Veras, J., 2010. Sustainability strategies for city
logistics. Green logistics: Improving the environmental sustainability of logistics,
pp.282-305.
Attard, M., 2012. Reforming the urban public transport bus system in Malta: Approach and
acceptance. Transportation research part A: policy and practice. 46(7). pp.981-992.
Atzori, L., Iera, A. and Morabito, G., 2010. The internet of things: A survey. Computer
networks. 54(15). pp.2787-2805.
Budiman, M.J., Walukow, S. and Makapedua, H., 2016. Development of Intelligent Transport
System for Detection System Location Traffic Accidents. Development. 151(11).
Davidrajuh, R. and Lin, B., 2011. Exploring airport traffic capability using Petri net based
model. Expert Systems with Applications. 38(9). pp.10923-10931.
de Palma, A. and Lindsey, R., 2011. Traffic congestion pricing methodologies and
technologies. Transportation Research Part C: Emerging Technologies. 19(6). pp.1377-
1399.
Gentile, G. and Noekel, K., 2016. Modelling public transport passenger flows in the era of
intelligent transport systems. Gewerbestrasse: Springer International Publishing.
Grant-Muller, S. and Usher, M., 2014. Intelligent Transport Systems: The propensity for
environmental and economic benefits. Technological Forecasting and Social Change.
82. pp.149-166.
Hamida, E.B., Noura, H. and Znaidi, W., 2015. Security of cooperative intelligent transport
systems: Standards, threats analysis and cryptographic
countermeasures. Electronics. 4(3). pp.380-423.
Knowles, R.D., 2012. Transit oriented development in Copenhagen, Denmark: from the finger
plan to Ørestad. Journal of transport geography. 22. pp.251-261.
Parkes, S and et.al., 2013. Understanding the diffusion of public bikesharing systems: evidence
from Europe and North America. Journal of Transport Geography. 31. pp.94-103.
Yu, R and et.al., 2013. Toward cloud-based vehicular networks with efficient resource
management. IEEE Network. 27(5). pp.48-55.
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