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A Generic Approach to Estimate Freeway Traffic Time Using Vehicle ID‐Matching Technologies
Author(s) -
Li Pengfei,
Souleyrette Reginald R.
Publication year - 2016
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/mice.12159
Subject(s) - matching (statistics) , outlier , computer science , map matching , travel time , data mining , anomaly detection , induction loop , transport engineering , real time computing , artificial intelligence , engineering , statistics , mathematics , global positioning system , telecommunications , detector
New technologies have emerged to estimate the travel time on freeways by matching certain unique identifications of passing vehicles at different locations. These types of technologies share many similarities despite having different mechanisms. In this article, a generic method is presented to estimate freeway travel times using vehicle ID‐matching technologies. In particular, the new method addresses two long‐standing challenges: outlier screening and travel time estimation. Innovations include (1) using both statistical methods and traffic flow theory to screen outliers; and (2) accounting for mechanisms of various equipment measurement errors. The effectiveness of the proposed method is demonstrated using simulation and shown to be more accurate and responsive to travel time changes than methods based on the use of traditional inductive loops.