Network-wide on-line travel time estimation with inconsistent data from multiple sensor systems under network uncertainty

ABSTRACT

This paper proposes a new modeling approach for network-wide on-line travel time estimation with inconsistent data from multiple sensor systems. It makes full use of both the available data from multiple sensor systems (on-line data) and historical data (off-line data). The first- and second-order statistical properties of the on-line data are investigated together with the data inconsistency issue to estimate network-wide travel times. The proposed model is formulated as a generalized least squares problem with non-linear constraints. A solution algorithm based on the penalty function method is adopted to solve the proposed model, whose application is illustrated by numerical examples using a local road network in Hong Kong.

KEYWORDS:

• Travel time estimation
• Intelligent Transportation Systems
• on-line data
• off-line data
• generalized least squares

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This paper was jointly supported by grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project Nos. PolyU 152074/14E and PolyU 152628/16E), National Natural Science Foundation of China (Project Nos. 71671184, 71271205 and 71371175), Qing Lan Project of Jiangsu Province, China (Project No. 04150030) and Research Institute for Sustainable Urban Development (RISUD) of The Hong Kong Polytechnic University (Project Nos. 1-ZVBY and 1-ZVBZ).