No abstract

No abstract

Clustering, Probabilistic clustering, Mahalanobis distance, Harmonic mean, Joint distance function, Weiszfeld method, Similarity matrix,

No abstract

The problem of finding the optimal roadway segment configuration for road-based surveillance technologies to estimate route travel times accurately is addressed. This problem is inherently a space discretization problem regardless of which travel time estimation function is used. Its ad hoc solution is the equidistant segment configuration, such as every half mile or every 1 mi. It is shown that the space discretization problem can be expressed as the common clustering problem. The novelty of the proposed approach is the use of preliminary vehicle trajectory data to obtain statistically significant traffic regime at the study route. Clustering of sample space-time trajectory data is proposed as a viable methodology for solving the optimal roadway segment configuration problem.