Relationship between Application Scale and Maximum Time Latency in Intelligent Transport Solutions

Abstract

Congestion is a major problem in large, urbanized areas. Intelligent transport solutions aim to reduce this problem. In general, traffic is monitored with the use of sensors, the resulting data are processed, a traffic state is estimated, and a control measure is computed and implemented. The availability and the quality of the data and the processing time of the algorithms are possible limiting factors in this pattern. The study reported in this paper examined the data requirements for various traffic control measures. In particular, the relationship between the spatial scale of the control measure and the time delay between the measurement and the control action, that is, the latency, was examined. A set of 17 applications showed that the larger the spatial scale of the control measure, the larger the latency could be. This relationship can be used to determine the latency quality criteria for a certain application. Alternatively, the relationship can be used to analyze which types of applications are possible when data with a specific quality can be collected. The latter analysis was carried out in the province of Delft, Netherlands. The analysis also showed the difference between the availability with respect to information and communication technology and useful data for applications. In particular, if no vehicles passed, information and communication technology systems were available, but no realistic measurements were produced.