[AMI] Adaptive Mobility

Project A

Overview of structure research conducted of AMIL (Nov 2022-Now)

Description:
Our module focuses on conducting cutting-edge studies and can be summarised into three pillars:

1. Transforming and forecasting city-wide mobility patterns,
2. Decision support and planning processes for transport infrastructure in the face of uncertainties, and
3. Sustainable and interactive land-use planning.

Our research endeavours span the global scope, with a particular emphasis on contributing to the development of Singapore and Zurich. Our ultimate objective is to develop adaptive plans that can effectively navigate uncertainties and lead to long-term desirable outcomes aligned with carbon neutrality and sustainability targets by 2050.

Project B

Proof-of-Concept of Modelling the Future Mobility under Uncertainty, Using Tanjong Pagar Neighborhood as A Case Study (Jan2023-Now)

Description:
Planning future cities to embrace new technologies such as automated, connected and electric vehicles is challenging due to complex interactions between mobility, infrastructure and land use. Furthermore, the timing for technologies to be ready, to what extent they are going to be adopted and how people interact with such technologies are highly uncertain. In this regard, the extensive study of current and future mobility changes and their potential impact on people’s behaviour and society allows an improved understanding of urban systems. However, despite the increasing recognition that cities face deep uncertainty, traditional spatial planning tools are inadequate to deal with it. Most research efforts have focused on increasing the granularity and complexity of models to gain accuracy, which further impedes a wide exploration of future scenarios.

In this work, we explore the potential of using complex models that are capable of capturing the spatial interactions between mobility, infrastructure and land use, such as the agent-based MATSim, under deep uncertainty. We study potential urban measures (network configurations, Pick-Up/Drop-Off points, parking strategies and intersection designs) in response to the technological shift in transportation using the Tanjong Pagar fictive neighbourhood, in Singapore, as the test site. The model was evaluated under three main uncertainties over time: travel demand, automation development and vehicle-sharing preferences and then fit with a surrogate model. The surrogate was then used to search for optimal sequencing, timing and grouping of interventions (i.e. adaptive pathways) to provide guidance on planning urban transitions.

Project C

Adaptive Planning Review: State of the Art and Future Directions (Mar 2023-Now)

Description:
Given the uncertainties faced by planners and decision-makers, plans that can be adapted over time have the potential to improve long-term outcomes, particularly as increasing knowledge changes the landscape of uncertainties. In recent years, many studies on adaptive planning principles have been advanced and published. To map past and present scientific themes as well as identify central works in the field, a meta and bibliometric analysis is implemented on a comprehensive corpus of publications dating back to 1984. The identified works will be studied via a systematic literature review to identify core trends related to the theory and practice of adaptive planning.
 

Project D

Adaptive Planning Charging Infrastructure for Shared Electric Autonomous Vehicle (SEAV) Mobility (Apr 2023-Now)

Description:
This research addresses the strategic problem of planning and optimising charging infrastructure for Shared Electric Autonomous Vehicles (SEAVs) in the context of Singapore. The major contribution is an adaptive planning framework that utilises Reinforcement Learning (RL) and a dual optimisation model. By incorporating RL methods, the framework determines the optimal location and capacity of charging points at different deployment stages. The study provides valuable insights and decision support to city planners by assisting in optimal charging infrastructure deployment, efficient resource allocation, adaptive planning, and future-proofing infrastructure. The research leverages data-driven approaches and AI-based tools to enhance analysis and decision-making processes in transportation systems.
 

Project E

Impact of inter-household social activities on travelling behaviours in Singapore (Jan 2023-Now)

Description:
We have conducted a pair-level survey on the impact of inter-household social networks on transportation choices. Based on our findings, which utilize latent class variable modelling, we plan to present this new research topic at the upcoming IATBR conference. Our study sheds light on the relationship between social networks and transportation decisions, providing valuable insights into how these dynamics influence individuals' travel behaviour within inter-household contexts. Through our participation, we aim to contribute to the field of transportation research and engage in meaningful discussions with experts in the field.

Project F

Impacts of Work-from-Home (WfH) on Shift of the Travel Mode for Commuting Trips in Singapore (Jan 2023-Now)

Description:
This research study aims to investigate the effects of the post-pandemic period, characterized by relaxed travel restrictions due to COVID-19, on traffic demand recovery. As working from home (WFH) continues to be embraced by companies, individuals' travel behaviours and lifestyles are influenced by the working pattern established during the pandemic. Consequently, their attitudes towards time and money have undergone notable shifts. This study seeks to explore How significantly WFH levels will alter these perceptions and how sensitively these changes will work on travel mode choices. To achieve this, two stated preference surveys were conducted to gather valuable insights into the evolving dynamics of travel preferences in the context of WFH and post-pandemic conditions.

Project G

Responsiveness of infrastructure planning organisations: Embracing adaptive planning methods to meet societal needs (Zurich-based Project, Nov 2022-Now)

Description:
Infrastructure is continually constructed and modified to meet changing needs of stakeholders. However, this is sometimes completed later than expected, resulting in unmet stakeholder needs for unnecessarily long periods. This delay is related to long duration of the planning process, length of time during which infrastructure is to be used and uncertainty associated with change in stakeholder needs over time. Improvement in speed with which changing needs can be met is likely to yield substantial benefits for stakeholders. The responsiveness of infrastructure planning organisations describes their ability to meet stakeholder needs quickly.

This research (1) maps the planning process of the relevant decision-makers planning regional transport infrastructure in practice, (2) identifies the potential of adaptive planning methods in planning practice, (3) develops state-of-the-art tools to plan regional infrastructure development considering future uncertainties, e.g., impact of automated, connected and electric vehicles and the complex interactions between mobility, infrastructure and land use.

Project H

MATSIM for Singapore: Exploring the Mobility Patterns of Singapore using Agent-based Modelling Techniques (Project completed, FCL Phase 2)

Description:
In 2011, we developed the first large-scale implementation of an activity-and-agent-based MATSim transport simulation model of the entirety of Singapore. During the following 10 years, we re-iterated and improved our implementation in projects commissioned by the URA and MND, with cooperation of LTA, URA and HDB. We are now working on a re-implementation of this model for the post-covid Singapore.