ABSTRACT
Freeways were built originally to provide almost unlimited mobility to road users for a number of years to come. No one predicted the dramatic increase in car ownership that has led to the current situation where congestion during rush hours often converts a smooth traffic flow to a virtual parking lot. The negative effects of congestion go beyond the obvious one, the travel time that drivers experience, to include environmental and health effects, travel cost, safety, quality of life, and so forth. The need for additional capacity in order to maintain the mobility and freedom drivers used to enjoy in the past can no longer be met in most metropolitan areas by following the traditional approach of building additional highways. The lack of space, high cost of land, environmental constraints, and the time it takes to build a new highway, as well as the possible disruption to the traffic system in already congested areas, make the building of new highways in many metropolitan areas a very challenging proposition. The only way to add additional capacity is to make the current system more efficient through the use of technologies and intelligence. As characterized on page 271 of Reference [1], “the traffic situation on today’s freeways resembles very much the one in urban road networks prior to the introduction of traffic lights: blocked links, chaotic intersections, reduced safety.” In another paper [2] it is pointed out that most of the congestion is due to mismanagement of traffic rather than to demand exceeding capacity. The current highway system operates as an almost open-loop dynamic system, which is susceptible to the effect of disturbances in ways that lead to frequent congestion phenomena. The successful implementation of intelligent transportation systems will require a good understanding of the dynamics of traffic and the effect of associated phenomena and disturbances. In addition, the understanding of human interaction within the transportation system is also crucial. Transportation systems and traffic phenomena constitute highly complex dynamic problems where simplified mathematical models are not adequate for their analysis. There is a need for more advanced methods and models in order to understand the complexity of traffic flow characteristics and find ways to manage traffic better using advanced technologies and feedback control techniques. The high complexity and dynamicity of traffic systems cannot be always accurately captured by mathematical models. For this reason computer simulation models are developed and tuned to describe the traffic flow characteristics on a given traffic network.
