Multi-Objective Optimization Model for P + R and K + R Facilities’ Collaborative Layout Decision

In order to reduce the pressure on urban road traffic, multi-modal travel is gradually replacing single-modal travel. Park and ride (P + R) and kiss and ride (K + R) are effective methods to integrate car transportation and rail transit. However, there is often an imbalance between supply and demand...

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Bibliographic Details
Published inSustainability Vol. 12; no. 21; p. 8833
Main Authors Wang, Wei, Sun, Zhentian, Wang, Zhiyuan, Liu, Yue, Chen, Jun
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.11.2020
Subjects
Central business districts
Cities
Collaboration
Commuting
Cost analysis
Decision making
Efficiency
Layouts
Multiple objective analysis
Occupancy
Optimization
Optimization models
Overflow
Public transportation
Site selection
Supply & demand
Sustainability
Traffic congestion
Traffic flow
Transfer facilities
Travel
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Summary:In order to reduce the pressure on urban road traffic, multi-modal travel is gradually replacing single-modal travel. Park and ride (P + R) and kiss and ride (K + R) are effective methods to integrate car transportation and rail transit. However, there is often an imbalance between supply and demand in existing car occupant transfer facilities, which include both P + R and K + R facilities. Therefore, we aim to conduct a research on P + R and K + R facilities’ collaborative decision. It first classifies car occupant transfer facilities into types and levels and sets the service capacity of each category. On the premise of ensuring the occupancy of parking spaces, our model aims to maximize the intercepted vehicle mileage and transfer utility and establishes an optimal decision model for car occupant transfer facilities. The model collaboratively decides the facilities in terms of location selection, layout arrangement, and overflow demand conversion to balance the supply and demand. We choose Chengdu as an example, apply the multi-objective optimization model of car occupant transfer facilities, give improved schemes, and further explore the influence of the quantity of facilities on the optimization objectives. The results show that the scheme obtained by the proposed model is significantly better than the existing scheme.
ISSN:2071-1050
2071-1050
DOI:10.3390/su12218833