Case Studies

Dynamic Autonomous Road Transit

Dynamic Autonomous
Road Transit

All-encompassing study of various public
transport networks in Singapore

Study of Large-Scale Transport Systems

Study of Large-Scale Transport Systems

With a growing urban population and an increasing demand in public transport, research into novel public transport solutions becomes increasingly important. Simulation studies can offer an insight into the performance, bottlenecks, and potentials of the public transport system and act as an enabler to improve the efficiency and thereby the passenger experience. With CityMoS, we present a novel methodology for the modelling and simulation of large-scale public transport systems, including passenger assignment, routing, as well as bus and train operation. Contrary to related work in the field, we utilize high-performance parallel computing to follow a microscopic approach, simulating each passenger and vehicle individually to provide more flexibility in the decision-making process.


The selected area highlights the deployment area for the DART system. We modelled this area in detail in CityMoS, including existing bus lines, the mass rapid transit network as well as the proposed DART corridors. Entry and exit points to the target area (highlighted in triangles) were modelled to carry all passenger demand expected to enter and exit the area. Passenger demand was modelled on a zonal basis and mode assignment was carried out during run-time.

We modelled the entire public transport network in the form of a directed graph where nodes represent bus stops, platforms, MRT stations, etc and edges denote connectivity with an assigned travel time. We created 98 of these graphs to capture how connections change over time, with each graph occupying around 2.5mb of memory. With the help of contraction hierarchies, each query only took a few microseconds to execute, allowing us to simulate behaviour and preferences for every single commuter.


CityMoS provided insights into passenger choices as well as the performance of the system. Furthermore, we investigated how experiences made by passengers affect their next choices and how those would impact the transportation system. Our simulation study supported the original hypothesis that DART can alleviate bus crowding and improve commute times for passengers.
For more information on the DART system, please visit

A publication of our findings will follow.

Case Studies

Large-Scale Modelling of Electric Public Bus Operation and Charging

Large-Scale Modelling of
Electric Public Bus Operation
and Charging

Advanced evaluation of electrification pathways for public transport at scale



With climate change concerns in mind, many transportation authorities in the world are pushing towards the electrification of road transport in the coming decades. In particular, public transport networks are considered for early electrification. Converting an existing public bus system to operate with electric buses can be challenging, as existing bus schedules might not be directly feasible with the limited range of electric buses. Moreover, the charging infrastructure for an electric bus fleet involves the sharing of chargers between many buses, thus necessitating finding the appropriate charging strategy and the corresponding number of chargers to install.

CityMoS Application

With CityMoS, entire public bus networks can be simulated with the desired fleet composition and charging infrastructure for depot-charging and/or opportunity-charging at end-stations. Optimization of the number of chargers through simulation-driven optimization ensures the feasibility of the operation at each stage of the optimization. Trip dispatching verifies that sufficient energy is available to the vehicles, otherwise they are directed to a charging station to replenish their battery. The energy demand of both service trips and off-service trips is accounted for and depends on the driving profile, air-conditioning load and the number of passengers in the bus.


In the SITEM project, we applied this model and built a digital twin of the entire bus network of Singapore, which consists of more than 500 bus routes and 5800 buses. In cooperation with the local transport authority, several electrification scenarios have been evaluated and compared. The impact on the power grid of the electrification of the bus fleet was assessed and recommendations were derived.

Case Studies

CiLo Charging


Optimized integration of charging, logistics, energy and
traffic management for the operation of electric vehicles in
logistics depots close to cities

City Logistics Charging (CiLo Charging)

City Logistics Charging (CiLoCharging)

The project focuses on the development, prototypical implementation and evaluation of a corresponding solution both in a simulation and in a field trial at the site of a newly built terminal. Leading partners are working in the individual domains together with recognized research institutions to develop an optimized, flexible and demand-oriented solution for requirements-based integration.


The CiLoCharging project aims to enable an optimized, flexible and demand-oriented solution for the use of electric vehicles in the distribution service of a logistics terminal from an economic, technical and environmental perspective by taking into account the requirements from the domains of energy, logistics, charging infrastructure and mobility management.
In order to be able to adequately take into account the framework conditions typical for general cargo logistics and to ensure the scalability of the fleet terminals in an economical manner, both charging management must be integrated into the existing logistics processes and smart energy management must be provided for integrating electrified logistics terminals into the electrical distribution network.

Application of CityMoS in CiLoCharging Project

The use of a powerful simulation platform enables the cost-efficient exploration of large parameter space and the analysis of a wide variety of what-if scenarios. CityMoS serves as the digital twin of the entire logistics operation including depot, fleet vehicles, other traffic and in the target area (Frankfurt am Main). The covered topics include:
  • Study of various fleet parameters (fleet composition, vehicle types, cargo space, battery sizes)
  • Study of various depot parameters (number of charging stations, charging speed, auxiliary consumers)
  • Research into the effect of second-life battery use as local energy storage
  • Evaluation of novel vehicle-to-grid communication
  • Connect to existing fleet management tools
  • Analysis of all fleet relevant metrics (delivery delay, electricity costs, etc.)
In collaboration with:
Case Studies



Singapore Integrated Transport and Energy Model

Citymos and Mesmo-01 1

Commissioned by the Prime Minister’s Public Sector Science and Technology Policy and Plans Office (S&TPPO) and in collaboration with all relevant agencies, researchers from TUMCREATE and A*STAR’s Institute of High Performance Computing (IHPC) set out to create the first high-fidelity, island-wide simulation of electric vehicle (EV) transport in Singapore, called SITEM, short for Singapore Integrated Transport and Energy Model.

SITEM integrates multiple aspects of mobility and energy modelling, including the movements of individual vehicles, drivers’ decisions where and when to charge, as well as the interaction of EV charging demand with the capacity of the power grid. The project conducts a comprehensive analysis of projected electric vehicle charging patterns and energy demand, which will support policymaking on Singapore’s budget 2040 vision for all vehicles to run on cleaner energy. Such initiative will greatly contribute towards Singapore’s decarbonisation commitments.

SITEM Project Builds on Two Primary Simulation Technologies Developed by TUMCREATE in Singapore:


This collaboration between the research teams and relevant government agencies allows for integration of the best from two research institutes to address national level challenges.”

Er Pang Chung Khiang, Group Chief Systems Officer of S&TPPO, PMO
  • CityMoS, the City Mobility Simulator utilises high-performance computing techniques to enable high-detail transport simulation of the entire island of Singapore, while maintaining short turnaround times. This enables the efficient exploration of wide parameter spaces.

  • Multi Energy System Modelling and Optimisation (MESMO) is an advanced software framework that combines simulation of electrical grids and optimisation techniques to mitigate the grid impact of distributed energy resources (such as photovoltaics) and new types        of loads (such as EV charging).

The live coupling of the mobility simulator CityMoS and the power grid simulator MESMO provides insights into the inter- dependencies of both systems. These advanced scenario modelling capabilities have enabled regulatory agencies to explore and evaluate various pathways to vehicle electrification. For example, given that private electric cars will generally park longer than the actual duration required for the car to fully charge, smart charging management can help reduce grid infrastructure upgrade costs without compromising the overall energy provisioned to the electric cars. 

SITEM makes it possible to estimate the efficiency gains from such systems and to model their impact alongside or in combination with other mechanisms such as incentive-based demand shifting, smart scheduling, and local energy storages.

Winner of the 2022 Ministry of Trade and Industry (MTI) Borderless Silver Award.
In collaboration with:
In collaboration with: