Impacts of Intelligent Transport Systems on Traffic Behaviour

Traditional approaches to limit the number of road traffic have taken the form of the “three Es” of Education, Enforcement and Engineering. These types of interventions have shown varying amounts of success, but they are often limited in time and space. An example of this is the use of speed humps, High occupanct vehicle measures and intelligent transport systems. While speed humps reduce the vehicles speed locally, the driver is free to increase the vehicle speed in between humps. Similarly bus lanes and high occupancy vehicles (HOV) measures have been introduced to encourage the use of buses and reduce the car dependency. The problem however is that in many situations the bus lanes are observed to be under used while a huge increase in traffic congestion and delays are observed in the rest of the traffic lanes. These situations might also result in that the private car drivers make illegal use of the bus lanes as they perceive them as waste of space use. Moreover, while such measures might encourage the use of public transport over the private cars, the increase in overall traffic, delays and the global level emissions and fuel consumptions will be very detrimental on the environment. Intelligent Transport Systems (ITS) is the name given to an advanced systems which can be used in various ways to monitor traffic, detect vehicle location or detect the weight of the vehicles or the number of persons in any vehicle. This type of system can be achieved via a number of technical solutions, including using sensors and inductive loops. While the technology for providing such systems is available, an increasing number of applications are still under examination and testing. This paper aims at investigating possible utilization of Intelligent Transport System (ITS) to optimize the success of the greenways and the HOV measures and to improving the conditions in the urban areas. To achieve that, Glasgow road in Edinburgh has been modeled using the micro-simulation model, VISSIM (PTV, 2006) for three different types of scenarios on the same network.