JPL's Wireless Communication Reference Website

Chapter: Network Concepts and Standards
Section: Intelligent Transportation Systems

Road Traffic Models

Advanced Traffic Management Systems (ATMS) and Traveler Information Systems (ATIS) are based on mathematical models on the behavior of road traffic flows.

Traffic Flow Parameters of Interest

Three elementary parameters are commonly discerned that collectively determine the status of the actual macroscopic traffic process, viz. traffic density k, traffic flow q and traffic speed v. The following definitions are given for these three elementary macroscopic traffic flow parameters.
The traffic density k
is defined as the number of vehicles occupying a section of roadway in a single lane and is expressed on a per kilometer and a per lane basis (veh/km/lane).
The traffic flow q
is defined as the number of vehicles passing a specific point or short section in a given period of time in a single lane and is expressed as an hourly rate on a per lane basis (veh/hr/lane).
The speed v
is defined as the average rate of motion and is expressed in kilometers per hour (km/hr).

Figure: typical v,q-diagram

It is generally accepted that the contribution of ATMS and ATIS to an optimal utilization of the available road infrastructure will be relatively small under normal conditions, but is presumed to be considerable in the case of deviant traffic conditions. For this reason, we distinguish another macroscopic traffic parameter that is of vital importance for both ATIS and ATMS and that can be derived from the three elementary traffic flow parameters: the prevailing traffic flow regime, i.e. free flow or congested traffic.

This parameter depends on the actual values of the three elementary parameters. Their coherence can best be explained by means of the well-known reciprocal relation that exist between the three elementary traffic parameters, namely q = v k. Based on this relationship the three so-called fundamental diagrams can be formulated, which outline the behaviour of the traffic flow, expressed in the elementary parameters q, v and k. Although various, dissimilar theories exist about the exact shape of the fundamental diagrams, their general outline is commonly considered to be appropriate. The Figure illustrates one possible and rather simplified appearance of one the fundamental diagrams, viz. the speed-flow (vq) diagram based on the linear speed-density model of Greenshields. In this speed-flow (vq) diagram, we can observe two distinct states of the macroscopic traffic flow. In the commencement of the first state, that of free-flow traffic, the individual vehicles that constitute the traffic flow hardly impede one another and the prevailing speed v remains well above the theoretically optimum speed vo. As the number of vehicles in the traffic flow increases, the vehicles more and more suffer from one another and the speed decreases and eventually approaches vo. In the second state, that of congested traffic, the individual vehicles impede each other in such a way that both the flow and the speed further decrease.

Free-Flow or Congestion

So, the fourth macroscopic traffic parameter that we distinguish, indicates the currently prevailing traffic regime, hence free flow or congested traffic. Although often three traffic states are discerned, the right-most part of the vq-diagram comprising of both a free-flow and congested component is often separately considered as the unstable region, for our purposes we will follow the two-regime approach.

Besides the four depicted elementary traffic flow parameters, also other characteristics of the actual traffic flows on the road network(s), might be of interest for ATMS or ATIS. Examples of such additional relevant traffic flow parameters would be the actual capacity and origin- destination data.

Relevant ATIS Parameters

From the perspective of ATIS, the most important topic is informing the (equipped) road user with respect to the optimal route from its origin to its destination, given the traffic conditions at the moment of passage. Without fixing the exact criteria that are used to determine whether a particular route is optimal (a weighed combination of travel time, distance, costs, etc. might be used), in general, the real-time link mean speed v or travel time t is the most determinative (and the most difficult to determine) component. Furthermore, ATIS should notify the (equipped) road users when a disturbance in the traffic flow has occurred that will significantly affect the travel time that they will experience on their (planned) route from origin to destination, and which is likely to eventuate in a diversion recommendation. Hence, for ATIS, also selection of the prevailing traffic regime, i.e. detecting delaying congestion, is of importance.

The other elementary macroscopic traffic flow parameters that we have distinguished, viz. the density k and the flow q, might, in some subordinate way, contribute to the ATIS objectives, but are certainly not indispensable. Therefore, we will only suggestively address obtaining and further processing data concerning the actual value of the flow q and the density k.

Relevant ATMS Parameters

From the perspective of ATMS, the most important topic is distributing the available traffic over the accessible infrastructure. For this, predominantly the actual amount of traffic, i.e. the traffic flow q (possibly also the traffic density k), and the actual performance of each part of the road network(s), i.e. link mean speed v or travel time t, are of importance. By means of infrastructure based traffic detectors the traffic flow (and more or less also the density) can be measured directly and accurately, so we will not consider the issue of obtaining the flow or density by means of infrastructure based traffic detectors for ATMS any further.

Since swift detection of disturbances in the traffic flow and deploying measures accordingly, is crucial for ATMS, also selection of the prevailing traffic regime, i.e (automatic) detection of incidents, is of major importance for ATMS. Existing Automatic Incident Detection (AID) systems basically belong to the class of ATCS (i.e., they are local-oriented).

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