Joint optimisation of park-and-ride facility locations and alternate traffic restriction scheme under equilibrium flows

Abstract

Alternate traffic restriction (ATR) schemes manage traffic congestion by prohibiting a proportion of cars from entering a predetermined ATR area during specific time periods. Under the ATR scheme, Park-and-Ride (P&R) often becomes more popular as travelers can park cars at P&R facilities and avoid driving into the ATR area. This paper proposes a multi-objective bi-level model that jointly optimizes the P&R facility locations and the ATR scheme (the ATR areas and the proportion of restricted private cars). The upper-level model minimizes the total travel cost and total emission cost, and maximizes consumer surplus. The lower-level model characterizes the user equilibrium of travel modes and route choices. The non-dominated sorting genetic algorithm is adapted to solve the proposed multi-objective bi-level model, where a gradient project algorithm is used for solving the lower-level model. Numerical studies are conducted to test and illustrate the applicability of the model and algorithms.

KEYWORDS:

• Park-and-ride location
• alternate traffic restriction
• multi-objective optimisation
• bi-level programming

Acknowledgement

Dr. Wei Liu would like to acknowledge the support from The Hong Kong Polytechnic University (P0039246, P0040900, P0041316).

Disclosure statement

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

Notes

1 The great crawl – The Chinese love their cars but do not want to pay more for driving them, available at https://www.economist.com/china/2016/06/16/the-great-crawl?frsc=dg%7Ca, accessed on June 01, 2021.

Additional information

Funding

This research was partly supported by grants from the National Natural Science Foundation of China (72171236, 71701216, 71871226), the National Key R&D Program of China (2020YFB1600400), the Natural Science Foundation of Hunan Province (2020JJ5783).