Intelligent Transportation System (ITS)

Intelligent transportation system (ITS) is the application of detection, analysis, control and communication technologies for transportation services in order to improve safety mobility and efficiency.

The European Commission encourages the use of information and communication technologies (ICT) in passenger and freight transport as Intelligent Transportation Systems (ITS) improve safety, reduce traffic congestion and reduce emissions. In this regard, the Intelligent Transportation System is defined as the application of detection, analysis, control and communication technologies to transport services with the object of increase safety, mobility and effectiveness.

Intelligent Transportation System covers a wide variety of applications that process and share information to reduce congestion, develop traffic management, reduce environmental impacts and provides effective transportation services to commercial users and the general public. Intelligent Transportation System, with these features, brings a fresh breath to the sector in overcoming various issues such as traffic congestion in transport, road safety issues, accidents, delays and environmental pollution.

What is necessary today in urban life: a safe, fast, comfortable and profitable transport infrastructure is provided with the use of technology. The pioneer of that technology is obviously ICT. Smart systems used in digital transformation have also allowed the development of Intelligent Transportation System technology. While ITSs use ICTs to gather, organize, analyse, use and share real-time information on transportation systems, Intelligent Transportation System applications offer proactive, user-driven solutions with a decision support system infrastructure. They are not just ICTs, but also decision-making systems using analysis and artificial intelligence.

Scope of the Intelligent Transportation System

Intelligent Transportation systems (ITS) are expected to benefit all stakeholders in line with their objectives. These benefits include faster travel times for vehicles, better governance of municipal authorities, safer transportation for citizens, and a reduction in fuel consumption. Although these systems are extremely costly to implement, they have many benefits for the public, such as reducing fuel imports, reducing accidents, fatalities, waste disposal, safety, etc., making public services more efficient. Additionally, Intelligent Transportation System increases driver comfort and reduces road maintenance costs. These benefits are expected to enhance the economic attractiveness of cities as a result of higher labour productivity.

With the developing opportunities of technology, the use of smart systems in the services offered in cities is becoming widespread. In order for policy makers to make strategies and action plans on this issue, accepted methods are needed to evaluate the effectiveness and sustainability of Intelligent Transportation System (ITS). It should be aimed that the concrete parameters defining the level of the services provided within the scope of smart city, show the level of intelligent systems supported by the services or production process, and implies that this evaluation method should be accepted.

Transportation services in local administrations are provided by the competent public institution (Metropolitan Municipality or Provincial Municipality) in each city. The services offered today need to be supported by intelligent systems within the scope of Smart Urbanism. It is necessary to measure the level of Intelligent Transportation System Transformation independently, to plan and evaluate its needs.

The solution of transportation problems in smart cities is an important subsystem. Transportation problems directly affect the quality of life of citizens. There are many independent index studies to measure the problem. Moovit and tomtom, which are widely used and the most well-known public transport statics and traffic measurement indexes around the world, make traffic comparisons categorized between cities. These indices can be used in traffic-related assessments.

Traffic measurement indexes and value losses

Many city data can be analysed in a comparative manner with digital measurement tools and data processing science. The most common index used in this respect is that of traffic density. With the information provided for real-time vehicle data, periodic evaluations of data such as traffic congestion, average time spent in traffic, average travel time and average speed are made with index values.

The traffic index established by tomtom and public transit statics by moovit, which is accepted for this purpose, is widely used. The literature indicates that these index values directly affect the quality of life in this city and there is a negative relationship between them.

The Tomtom Traffic Index provides drivers, city planners, auto manufacturers and policy makers with unbiased statistics and information about congestion levels in 403 cities across 56 countries on 6 continents. According to the Tomtom Traffic index, the 10 cities with the highest traffic congestion in the world between 2020 and 2018 are as in Table 1.5.

Traffic congestion ranking and rates between 2020 and 2018 according to Tomtom traffic index

Traffic congestion is a continuing problem in large-scale cities. However, in an accessible urban context, it is necessary to provide a continuous and constant transport alternative for public transport throughout the city. Istanbul is one of the busiest cities in the world with a population of over 14 million. People usually commute 91 minutes’ average in İstanbul by public transit every day. It is seen that average transit travel time is 76 minutes in similar metropolitan cities (New York, Moscow, Paris, London and Rome) on Istanbul scale. There is a difference of 15 minutes in terms of average travel time between metropolitan cities where the rail system infrastructure has been completed and Istanbul.

Traffıc measurement systems

Traffic measurement systems consist of a variety of solutions such as radar-based sensors, BT sensors, Image Processing Sensors, mobile application users’ data and FCD. Since Istanbul’s traffic is heavily affected by weather conditions, Istanbul Metropolitan Municipality (IMM) collects real time weather status information to take necessary precautions and informs drivers via internet, mobile apps and VMS especially during winter.

Traffic measurement system solutions

The transport sector has environments in which the most data can be produced about people’s daily activities. People are constantly moving around the city. In this context, significant data is generated. Storing this data and generating transportation strategies from these, updating the main transportation plans, establishing sound reasons for investment plans and so on benefits.

Many mobile applications offer people the experience of previous customers in choosing restaurants and hotels easily. People who plan a holiday usually benefit from these recommendations. This system forces businesses to virtual competition. Even if it is known that every customer will not receive service again, he receives services from the company as a continuous customer who must be satisfied. For example, customer reviews such as a non-clean hotel room, a noisy room reduce the hotel’s customers.

To give an example for urban transportation; mobile navigation applications can provide alternative routes to vehicles without using sensor data. You can plan a more efficient journey by choosing one of the alternatives offered, such as the shortest route, the shortest time or the cheapest fare. This infrastructure is also active for public transport users. With Google Maps, you can plan your public transportation journeys in almost all major cities of the world.

Assessment of Intelligent Transportation System studies framework

Intelligent Transportation System helps the city build sustainable, safe, timely, comfortable and economic transportation infrastructure. ICT is the reference technology for implementing such technologies. Smart systems used with digital transformation have also promoted the development of Intelligent Transportation System systems.

While Intelligent Transportation System’s use the ICT to collect, organize, analyses, use and share real-time information about, the respective applications provide proactive solutions based on user needs with a decision support system infrastructure. These are not only information systems, but also the self-determination capabilities of the system could be achieved by artificial intelligence (AI).

During the past two decades, developments in Intelligent Transportation System have been systematically examined. In particular, the framework presented by Lee et al. It is important to note that this framework recommends the use of intelligent traffic brokers that incorporate heterogeneous traffic information and data sources and a historical traffic database to predict traffic status in real time using knowledge base systems.

There have been a number of applications such as an warning system to improve the efficiency of the traffic signal system, analyse and evaluate the information obtained by measuring traffic situations using telematics, digital tachographs and road data in a cloud-based system. In an additional study by Lei et al. (2017) a secure framework for a heterogeneous network with vehicle communication systems (VCS) is offered.

There are two main components to this framework. The first part presents a new network topology based on a decentralised blockchain structure. In part two, a dynamic structure supported by a thorough simulation and analysis is given.

As expected, these studies focus mainly on highway infrastructure. A general framework involving specific expertise from government capabilities seems to be lacking and the maturity of Intelligent Transportation System implementation remains to be developed. Though, there are a few initiatives to evaluate the intelligence of a city through a weighting system such as that proposed by Tay et al. (2018), a comprehensive model to ensure that the level of sustainable maturity is achieved has yet to be developed.

At a minimum, decision-making and systems, behavioural analysis is not clearly addressed. A maturity model would not be sufficiently comprehensive without operational decision-making assistance for smart indicators and city capabilities.

With the innovation brought by the concept of smart mobility, it can be said that all modes of transport (rail, land, sea and river and airway) must be managed in an integrated manner in order to increase mobility. In addition, there is a need to assess the transformation of management components in certain aspects with an integrated architecture or infrastructure in a holistic way.

It is understandable that the quantification of certain qualitative data can produce consistent and useful advantages, but in most cases, different types of qualitative data are hard to quantify satisfactorily. An assessment model that uses indicators based on expert advice and containing quantitative values will thus be preferable to guide cities in the digital transformation.

Intelligent Transportation System new trends

Many services such as Smart Mobility, Smart Health Services, Smart Environmental Management and autonomous services supported by artificial intelligence serve to urbanization, efficient resource use and contribute to increasing the quality of life. In this context, the use of personal digital assistant services has already started. Many of the concepts in the Intelligent Transportation System industry continue to evolve as they relate to smart mobility. While the transportation sector grows digitally with Smart mobility, digitalization leads the economic growth of the sector.

Business intelligence approach is used in the development of these services. In business intelligence approach; Managers typically determine what they want to monitor based on their main performance Indices (KPIs) or their main result areas (CRAs). Customized reports are designed to provide each manager with the necessary information. These reports can be converted into customized dashboards that present information in fast and easy to understand formats. Personal transport services assistant creates alternative routes according to the needs of a person by using data mining facilities with business intelligence approach.

Blockchain, widely known as one of the disruptive technologies emerged in recent years, is experiencing rapid development and has the full potential of revolutionizing the increasingly centralized intelligent transportation systems (ITS) in applications.

According to statistics , while the average daily use of private vehicles is 1 hour, this value is about 8 hours per day for shared cars. Research shows that by 2025, 12 million vehicles will be in the sharing system in the world. In 2040, 40% of the journeys will be made with autonomous vehicles. Integrated transportation will allow us to use sharing systems and different types of vehicles at different times.

The most important component of transportation demand management in the future; the mobility of internet and block chain will co-operate (Urban Tide, 2018). This new generation service; sharing vehicles, and allow digital interaction between all modes of transport.

The company “your -now” has created a new membership system that brings together all the car sharing operators in Europe. Members of this system can use the entire vehicle sharing system throughout Europe. The stakeholders of the mobile application service provided by the company are as follows; Car2Go, DriveNow, Beat, Olever, Kapten, Mytaxi, Moovel, ReachNow, Park-Line, ParkMobile, ParkNow, RingGo, ChargeNow. According to “Your now”; every shared car takes up to 11private cars off the streets and saves up to 14 metric tons of greenhouse gases a year. As every 7th car in our fleet is electric — driving has never been more eco-friendly.

Mobility as a Service (MaAS) services are predicting to redesign future public transport systems with blockchain technology. The use of cryptology in the transportation sector needs to be expanded for Blockchain technology, which will create a disruptive innovation. Mobility as a service is a service concept aimed at achieving the intelligent transport system.

Its aim is to connect and bring service modes together on a unique platform to enhance the travel experience. Passengers using MaAS only pay for the entire journey at a time, and the maximum advantage is achieved for service optimization. Service operator resources are integrated across the entire transport system. For cities to overcome the transportation challenges they face, they need to increase mobility. A

s mobility increases, transport services become more effective. Leading-edge technological tools (artificial intelligence, the Internet of Things, emotional intelligence, big data and analytics, etc.) are widely used in business models developed to increase mobility. The sharing economy, multimodal and intermodal transportation are key issues for increasing mobility.

As part of the transition from Mobility 3.0 to Mobility 4.0, cities must provide resources for this infrastructure return, plus, economic benefits can be maximized through business model opportunities. It is recommended that cities transform their transportation management infrastructure according to the MaAS system to provide an economic benefit. Integrated service management has made this transformation possible.

Figure 1.8 presents a management transformation proposal that will provide shared planning and interactive management. The shared MaAS platform is possible with end-to-end encrypted data sharing and data security by utilizing blockchain technology. It is essential to guarantee the safety of business and personal data and the integration of services.

Suggested structure for MaAS platform and integrated management.

It is also possible to use the concept of business intelligence in a similar sense with the concept of competitive intelligence. The main reason for this is that business intelligence is also directly involved in decision-making processes and makes competitive definitions among alternative decisions. Similar to competitive intelligence, Intelligent Transportation Services (ITS) offers users a choice of competitive alternative routes.

Intelligent transportation system (ITS) are complex systems that apply communications and information systems technology in a transportation infrastructure to improve the efficiency, safety, and security of the transportation system. The Research and Innovative Technology Administration of the Department of Transportation lists several research initiatives to accomplish effective Intelligent Transportation System. Some of these are the following;

  • Vehicle-to-vehicle (V2V) communications for safety: It refers to the use of a dynamic wireless exchange between two or more vehicles. Anonymous data interchange such as speed, distance and direction of travel allows vehicles to detect unsafe conditions to mitigate adverse circumstances.
  • Vehicle-to-infrastructure (V2I) communications for safety: It is the wireless sharing of information between vehicles and road infrastructure to prevent car accidents and improve environmental conditions.
  • Real-time data capture and management: This is a management tool in access to real-time and archived multimodal transportation information that is extracted from vehicles, infrastructure and mobile devices.
  • Dynamic mobility applications: This effort aims to identify, develop, and implement applications that enable vehicles and transportation infrastructure to enhance their current operational configuration.
  • Applications for the environment of real-time information synthesis (AERIS):This program includes the use of a vehicle, infrastructure and real-time transportation data to create green transportation systems. AERIS uses a multi-modal approach and works collaboratively with the vehicle-to-vehicle initiative.
  • Road weather management: It includes the use of real-time vehicle and infrastructure data as well as weather data to improve decision-making and forecasting capabilities.

Intelligent Transportation System uses artificial intelligence systems. System engineering methodologies should be adopted in the design of the sites.

The new trend in which all these vehicle communication systems are combined is known as Vehicle to everything (V2X). V2X communication systems allow the vehicle to interact with other vehicles, pedestrians, infrastructure and network. This provides a safe, efficient and greener mobility system.

Other well-known new trend is crowd management. It is primarily a methodology developed to monitor security and crowd behaviour. Its use in other fields is increasing with various source data provided by developing technology.
Crowd management is used as a new approach model in transportation management. RFID-based data increases the efficiency of crowd management.

One of the areas of use in transportation management is IoT based crowd management system for Public Transport. It is possible to develop the data collected with the support of decision support systems on urban space by using a framework for developing and managing applications as shown in the Figure 1.9

Urban applications using crowd management

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