Road Network Operations
& Intelligent Transport Systems
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Intelligence in Transport

Economic growth generates pressure for society to organise its mobility requirements in more intelligent ways. In the global economy of the 21st century, failure to address inefficiencies in the transport system will have an adverse effect on a country’s competitive position as well as its quality of life. Security concerns are also likely to become more prominent and may impact on transport services and international trade in ways that are unexpected and challenging. The potential for applying greater intelligence in transport is considerable

The concept of intelligence has its origins in psychology. There is no single definition of human intelligence but a variety of viewpoints. One interpretation is that it represents a single general ability to act. Another is a multidimensional cognitive ability that includes reasoning, planning, solving problems, thinking abstractly and comprehending complex ideas. In terms of transport services and products intelligence means ensuring they anticipate and respond to user needs and can be delivered efficiently and effectively - always recognising the diversity of needs and the pressure for compromise and trade-offs.

Several qualities of transport intelligence have been described:

  • connective intelligence: connectivity with the transport user or operator – for example through touch-screens, speakers and speech recognition
  • self-recognition intelligence: the system knows the state it is in - a kind of consciousness, for example automatic fault detection on traffic control equipment
  • spatial intelligence: an understanding of location and positioning requirements and spatial expression – for example turn-by-turn route guidance
  • kinaesthetic intelligence: flexible, moveable and adjustable technology for “smart moving” – for example adaptive cruise control
  • logic: embedded sensors to monitor technology and users’ daily activities – for example goods ordering and dispatch systems.
  • Intelligent Transport Systems already exhibit many of these qualities as shown by the work that the USDOT has sponsored on connected vehicles.

Transport intelligence has relevance to two main categories of stakeholders – the transport operators or “producers” and the transport users. The first group apply their intelligence to construct, maintain and operate transport networks and provide transport services. The second group uses its intelligence to make use of these networks and services for personal and collective travel needs and for the transport of goods.

The needs of these two sets of stakeholders – the producers (which includes road owners and operators) and the users – are often very different and their interrelationships need to be considered when implementing new transport systems. These different requirements are addressed throughout this website( See Measuring Performance).

Any future vision for ITS needs to take account of a number of external factors, the characteristics of systems themselves and the risk of catastrophic failure.

The development of intelligence characterised by these qualities, responsive to stakeholder needs and external factors can be illustrated with the following concepts:

C-ITS Technologies and Applications for Intelligent Transport

ITS Europe (ERTICO), a partnership of around 100 companies and institutions involved in the development, production and deployment of Intelligent Transport Systems (ITS), published in March 2015:

  • a report on Cooperative ITS (C-ITS or cooperative systems) service scenarios;
  • supported by a “Guide about technologies for future C-ITS scenarios”.

The Report makes recommendations on the roll-out of C-ITS services – in particular, how appropriate use of communication technologies can increase the quality of mobility services, safety and reliability whilst minimising costs. It covers three C-ITS deployment areas – for cities, corridors and traffic management/navigation. It presents relevant existing and maturing communication technologies – and describes their characteristics, cost structures and deployment models. It also maps services to the performance of communication technologies.

The Guide complements the report and is intended as a tutorial or guidance for those who would like a more detailed insight into C-ITS technologies, standards and initiatives.

The Report and the Guide are aimed at policy makers, procurers, operators, service providers and anyone with an interest in ITS. The goal is to support decision making about the most appropriate communication technologies for providing services.

Ambient Intelligence

The concept of Ambient Intelligence is relevant to ITS. It builds on the idea that we are surrounded by communications and computer technology embedded in everyday objects such as mobile phones, homes, vehicles and roads. Ambient intelligent systems, services and products are designed to include features that are sensitive and responsive to people’s needs and presence in an intelligent way. Ambient intelligence is fundamental to the concept of ubiquitous services as illustrated in the diagram below by the Korean Transport Institute.

Ubiquitous Services (Source: Korean Transport Institute)

With ambient intelligence comes an expectation of greater user-friendliness, more efficient services support, user-empowerment, and support for human interactions. This means working towards systems and technologies that are not only sensitive, responsive and intelligent but also interconnected, contextualised and transparent. Key enablers are:

  • unobtrusive hardware (miniaturisation and nano-technology, smart devices, embedded computational power, power consumption, sensors, activators)
  • a seamless mobile and fixed web-based communications infrastructure that is interoperable and dynamically reconfigurable for wired and wireless networks
  • dynamic and widely distributed device networks that are interoperable and can be networked on an ad hoc configuration with embedded intelligence
  • human interfaces that are natural to use (such as intelligent agents, multi-modal interfaces, models of context awareness)
  • dependability and security (meaning robust and reliable systems, self-testing and self-organising/repairing software, privacy-ensuring technologies)

Human Factors

Getting the human factors right is essential to the successful adoption of new ITS systems (See Human Factors). This requires an understanding of human psychology and what factors influence people’s behaviour. A number of human behaviour issues impact on the roll-out of Information and Communication Technologies (ICTs) – and are highly pertinent to the application of ITS:

  • people do not accept everything that is technologically possible and available
  • people need resources/capabilities to buy and use ICTs (money, time, skills, attitudes, language) that are not evenly distributed in society
  • people make use of new technologies in ways that are very different from the uses intended by developers and suppliers (such as the Internet, SMS texts)
  • new uses mainly emerge in the interaction between users and producers. User demands will only be met if costs are attractive for the suppliers
  • there is no such thing as a typical, standard user or use – but rather a diversity of users and uses
  • there is a difference between ownership, usage and familiarity. People own technologies but may not use them; people use technologies but may not have trust and confidence in them

Political factors in society are also important. New technologies for instance, may become a source of social exclusion. Security, trust and confidence are also potential bottlenecks limiting the deployment of Ambient Intelligence.

Privacy and human rights issues are significant. People are distrustful of having their movements monitored or being charged for services without immediate feedback. There may be a trade-off between privacy and service convenience. Some users will expect a degree of control over whether the systems report or conceal their identity and location.

Designers must also anticipate the possibility of hacking, sabotage, vandalism and criminal misuse, and a number of other “worst case scenarios”, not least regular accidental or wilful non-compliance with operating procedures. Self-recognition security systems will incorporate measures for detection, correction, prevention and elimination of these negative aspects. Flexibility to respond “on the fly” in crisis situations should also be written into the design. The consequences of a catastrophic failure must be assessed.

Support Systems

As support systems become more complex, they present the user with the problem of knowing and understanding what the system is currently doing. The driver who misinterprets the action of a complex or automated system may end up “fighting” the system. This is potentially very dangerous. There have been examples of incidents in civil aviation where pilots have tried to take manual control of the aircraft without first disengaging the autopilot.

Another potential problem with complex systems is that it becomes more difficult for a user to determine accurately whether the system functionality is deteriorating and has become substandard. Gradual deterioration combined with rarely used functions may lead to unpleasant surprises and dangerous situations.

When ITS reduces the operator’s role to supervision instead of active control, the supervisory activities can easily be neglected or omitted entirely, to make way for other activities. What can happen is illustrated by research with driving simulators. Drivers readily adapt to the use of anti-collision devices and may rely completely on the device after only a short learning period. If the simulated device is then made to fail, more than half of the drivers tested do not take effective action and crash. These simulations have been made under motorway conditions. A similar level of non-response in urban conditions - with a multitude of moving and stationary obstacles – would be far more dangerous.

System Failure

What happens in the event of system failure is a critical safety issue. Reliability analysis of systems is essential to be able to deliver good products or services and avoid catastrophic events due to failure of component(s). In communication networks, for instance, it is important to have duplicate circuits, mirror servers and reliable components that are fault-reporting to avoid frequent interruption in communications or unavailability for long periods.

In some cases government agencies have a responsibility to ensure the safety, security and reliability of the system. In the interests of mitigating any risk to traffic safety, the authorities will require computerised traffic control systems to be designed to allow “graceful degradation” from centralised network-wide control to autonomous local control at each intersection. This means that even if a small number of computational and communication units fail, traffic control does not collapse but remains satisfactory. Service can be maintained, although possibly at a slower pace and at reduced capacity.

The consequences of system failure for some of the more futuristic developments - such as automated vehicle platoons – are harder to imagine and will require research.


Reference sources

Miles J.C. and Walker A.J. (2006) The potential application of Artificial Intelligence in Transport IEE Procedings - Intelligent Transport Systems Vol 153 (3)