Benefits analysis of ITS components


The measure of effectiveness of VMS with respect to congestion reduction and mobility goal is the change (D OD vms ) in overall delay between the scenario in which VMSs are operational in the corridor (OD vms ) and the scenario without the information provided by VMSs (OD b ): OD vms  =  OD vms  – OD b. The former scenario provides a baseline against which ITS elements are evaluated. In either scenario, the overall delay is defined as the aggregate increase in travel time resulting from the capacity reduction on the freeway. The following is the frame of our evaluation model.



In our model, Travel time of a motorist is modeled with the following four components:

-         The traversal time on the portion of the freeway with reduced capacity,

-         The merge delay: delay associated with the merging of traffic on blocked lanes (if any) with traffic traveling on lanes that remain unobstructed,

-         The queue delay: delay associated with the dissipation of vehicle queues (if any) formed upstream of the incident location, and this queue delay is based upon a deterministic macro traffic model.

-         The diversion time: travel time on an alternate route, for motorists who made the decision to exit the highway corridor upstream of the incident location and to divert to an alternate route.


The network analyzed is a simplified freeway corridor presenting two route choices to be considered by travelers: the first represents the route where the disruption of free-flow traffic occurred while the second is a composite alternative representing all the other routes motorists could divert to. See following figure.



Suppose an incident happens along the main corridor. Driver will choose to divert to the alternative route or stay on the main corridor. The basic idea behind our evaluation models is that the ITS components will supply traveler with information with different details and therefore affect driver’s decision-making. In our model, we just simply use one parameter, diversion rate, to capture the estimated benefits, like delay saving, safety benefit, emission saving and fuel consumption saving. Basically our model is sort of a macro traffic simulation model.



My job is mainly to develop a package as an interface for these evaluation models. And the developing environment is MicroSoft’s Visual Basic:



Input & interface


Main menu


              General parameters



                           General variables



          Route type and Safety characteristics



              Variables for Value of time



Sample output



Delay savings are increased with more travelers diverting to alternate route, but the magnitude drops. Eventually once too many unnecessary vehicles diverted, the delay savings will decrease. This can be confirmed by the below figure also. Traversal time and queue delay on the main route decline and traversal time on the alternate route increase with increasing diversion rate. At some point when the decreases on main route cann’t compensate the increase on the alternate route, the delay savings drops.



Delay benefit



Inter-medium summary chart




Safety benefits

Safety benefit increases with more travelers diverting to alternative route when the diversion rate are small, but this does not make sense when the diversion rate are large. This is one of the limitations of ITSOAM because the potential of occurrence of accidents caused by congestion on the alternate route is not fully considered in this model.



Surprisingly, when the diversion rate is small the environmental benefits decline with more travelers diverting to alternative route. A possible explanation is diversion rate is too small to reduce enough queue delay on the main to make up the increase of emission and fuel consumption of traveling 15% longer. Only if the diversion rate is large enough, environmental benefits tend to increase. This is consistent with the trend on delay benefits.

Environmental benefits