Maximizing space-time accessibility in multi-modal transit networks: an activity-based approach

Abstract

Over the past decades, the impact of transport operating strategy improvements on space-time accessibility, which is an important research area for network design problem, has not been explicitly investigated particularly with the use of activity-based approach. In this paper, a novel activity-based space-time accessibility measure is introduced for considering individuals’ accessibility to various activities and travels in a unified super-network framework. A bi-level programming model is proposed for optimizing time-dependent transit line headways and fares in a multi-modal transit network from the activity-based space-time accessibility perspective. In the upper level, transit line headways and fares are optimized by time of day to maximize the network-wide activity-based space-time accessibility. At the lower level, an activity-based network equilibrium model is adapted to provide the resultant activity-travel patterns as reactions to the upper level decision. A simplified network in Hong Kong selected area is used to illustrate the application of the proposed model.

KEYWORDS:

• Space-time accessibility
• activity-based approach
• daily activity-travel pattern
• bi-level programming model

Acknowledgements

The work described in this paper was supported by the National Key Research and Development Program of China (No. 2018YFB1600900), the Social Science Foundation of Jiangsu Province (16GLC008), the National Natural Science Foundation of China (71601045), and research grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (No. PolyU 152095/17E) and the Research Committee of The Hong Kong Polytechnic University (No. 4-ZZFY).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work described in this paper was supported by the National Key Research and Development Program of China [grant number 2018YFB1600900], the Social Science Foundation of Jiangsu Province [grant number 16GLC008], the National Natural Science Foundation of China [grant number 71601045], and research grants from the Research Grants Council of the Hong Kong Special Administrative Region, China [grant number PolyU 152095/17E] and the Research Committee of The Hong Kong Polytechnic University [grant number 4-ZZFY].