Central Business District Of Singapore Research Articles

Optimal Railway Disruption Bridging Using Heterogeneous Bus Fleets

Mass Rapid Transit (MRT) systems, i.e. subway systems, all over the world, are experiencing an increase in ridership. This also means that in case of an unplanned MRT service disruption, the number of affected passengers is larger, requiring a fast and comprehensive response. In this paper, we thus study the disruption management of MRT systems. We develop an optimization model to identify the optimal bridging plan in response to an MRT disruption, so that the negative effects of a disruption could be minimized. Our approach supports deployment of multiple types of bridging buses, reflecting the diversity of vehicle types in a typical public transportation provider's vehicle fleet. The optimization objective of our approach is to decrease the travel delay of passengers and increase the number of passengers who can be served. We demonstrate the effectiveness of our approach on a hypothetical case study in the central business district of Singapore. Moreover, we validate our analytical results with microscopic simulation, showing that our simplified analytical optimization approach can be used for disruption response planning. Some deviations indicate, however, that a combined simulation and optimization approach yields better results to obtain an effective bridging plan.

District cooling network optimization with redundancy constraints in Singapore

This study presents a mathematical optimization model for planning topology and capacity of a district cooling network. The model relies on a mixed-integer linear programming formulation to find the most economic network layout while satisfying redundancy criteria against unavailability of cooling stations. The simplicity of the formulation makes it easy to embed in other models or to extend it to other redundancy cases.The model is applied to a case study in the central business district of Singapore. Results show that district cooling is a profitable option for Singapore, especially due to its constant high cooling demand that is currently satisfied mainly through decentralized cooling units. This result generalizes to tropical cities world-wide with high cooling demand density.

District cooling network optimization with redundancy constraints in Singapore

This study presents a mathematical optimization model for planning topology and capacity of a district cooling network. The model relies on a mixed-integer linear programming formulation to find the most economic network layout while satisfying redundancy criteria against unavailability of cooling stations. The simplicity of the formulation makes it easy to embed in other models or to extend it to other redundancy cases. The model is applied to a case study in the central business district of Singapore. Results show that district cooling is a profitable option for Singapore, especially due to its constant high cooling demand that is currently satisfied mainly through decentralized cooling units. This result generalizes to tropical cities world-wide with high cooling demand density.

Dwelling in different localities: Identity performances of a white transnational professional elite in the City of London and the Central Business District of Singapore

ABSTRACTBesides being mobile, migrant professionals dwell at specific localities. It is in this article that identity performances of one social group with equal identity dimensions, white, male German financial manager, are compared in two different local contexts of their dwelling: in the City of London and in the Central Business District of Singapore. This article demonstrates that by comparing similar social groups in different localities, the effects of locality become clearly visible. As the managers are temporal migrants, their dwelling practices are to arrange themselves with locality for the time of their delegation. Everyday practices and the specific symbolic labelling of localities are expressions and producers of identity. The mobile managers encounter the two localities with unique images rooted in the colonial period; as a centre and an outpost, respectively. As these images have an impact on their identity performances today, this article demonstrates that the mangers perform whiteness and being transnational elite with different emphasis regarding locality.

Effect of Street Design on Outdoor Thermal Comfort in an Urban Street in Singapore

AbstractOutdoor thermal comfort in urban spaces is an important indicator of the quality of life in an urban environment. This paper attempts to investigate the effect of street design on outdoor thermal comfort in an urban street in the central business district in Singapore, focusing on the design variables of street orientation, height-to-width ratio (H/W), and vegetation. A comprehensive field measurement with multiple points is presented and used to validate a widely used computer software holistic microclimate modeling system. The significance of the research is that real field data from multiple measurement points on microclimate parameters are produced and the effect of street design parameters on outdoor thermal comfort is quantified. It is found in the paper that the NW-SE oriented street is more stressful than the NE-SW street in the afternoon in terms of thermal comfort in Singapore, and that a H/W of 3 can be considered a threshold with respect to outdoor thermal comfort. The paper concludes ...

Thermal Comfort in High-rise Urban Environments in Singapore

Outdoor thermal comfort in urban spaces is an important indicator of the quality of life in urban environment. This paper attempts to investigate outdoor thermal comfort in an urban street surrounded by high-rise commercial buildings in the central business district in Singapore, focusing on the effect of height-to-width ratio (H/W) on outdoor thermal comfort. The microclimatic parameters of different H/W scenarios were determined by ENVI-met numerical simulation. Field measurement was conducted to validate the results from the numerical simulation and they were in good agreement. The physiologically equivalent temperature (PET) was utilized as the thermal index to assess outdoor thermal comfort. It has been approved quantitatively that shading provided by high aspect ratios can improve outdoor thermal comfort in urban streets and H/W of 3 can be considered as a threshold with respect to outdoor thermal comfort in Singapore.

The Effect of Urban Design on Outdoor Thermal Environment in a Central Business District Area in Singapore

Outdoor thermal environment in urban spaces is important for people to enjoy the urban environment. This paper investigated the effect of urban design on outdoor thermal environment in an urban street in the central business district in Singapore, focusing on street orientation and height-to-width ratio. The microclimatic parameters of different street design scenarios were determined by ENVI-met numerical simulation. Field measurement was conducted to validate the results from the numerical simulation and they were in good agreement. For different design scenarios, it is found that (1) The air temperature differences did not exceed 0.8°C; (2) The mean radiant temperature differences could exceed 40°C; (3) The maximum wind speed difference was 0.6 m/s; (4) No distinct relative humidity differences could be found. The results show that shading is the key strategy for improving outdoor thermal environment in Singapore because it leads to reduction on the air temperature and mean radiant temperature simultaneously. N-S orientated street had the best thermal environment condition.Outdoor thermal environment in urban spaces is important for people to enjoy the urban environment. This paper investigated the effect of urban design on outdoor thermal environment in an urban street in the central business district in Singapore, focusing on street orientation and height-to-width ratio. The microclimatic parameters of different street design scenarios were determined by ENVI-met numerical simulation. Field measurement was conducted to validate the results from the numerical simulation and they were in good agreement. For different design scenarios, it is found that (1) The air temperature differences did not exceed 0.8°C; (2) The mean radiant temperature differences could exceed 40°C; (3) The maximum wind speed difference was 0.6 m/s; (4) No distinct relative humidity differences could be found. The results show that shading is the key strategy for improving outdoor thermal environment in Singapore because it leads to reduction on the air temperature and mean radiant temperature simultaneously. N-S orientated street had the best thermal environment condition. Shading achieved by means of high aspect ratios can improve thermal environment at street level.

Modified Symbiotic Evolutionary Learning for Type-2 Fuzzy System

This paper proposes a new modified symbiotic evolutionary learning method (SET2) for fine-tuning the parameters of a type-2 fuzzy system. The paper uses a group-based symbiotic evolutionary approach. Instead of evolving the individual rules and assigning the fitness values for each rule, the membership function parameters and the rules are evolved as individual groups. This method improves the exploration of the solution space, and optimizes the rule, base count and the most influencing input parameters in each rule which is difficult to obtain in conventional symbiotic evolutionary learning approach. The paper also proposes a method to obtain the similarity measure of the membership functions. In order to demonstrate the efficiency of the proposed learning method, it is deployed in a simulated urban traffic network to obtain the optimal signal timings in a distributed manner. The proposed SET2 signal control was tested for various traffic conditions experienced in a section of the Central Business District of Singapore. A comparison of the average time delay and speed of vehicles indicated that SET2 signal control performed significantly better than the benchmark signal controls such as GLIDE, hierarchical multiagent system, and geometric fuzzy multiagent system. The test bed also showcased the performance of the modified learning method in a distributed environment.

Distributed Geometric Fuzzy Multiagent Urban Traffic Signal Control

Rapid urbanization and the growing demand for faster transportation has led to heavy congestion in road traffic networks, necessitating the need for traffic-responsive intelligent signal control systems. The developed signal control system must be capable of determining the green time that minimizes the network-wide travel time delay based on limited information of the environment. This paper adopts a distributed multiagent-based approach to develop a traffic-responsive signal control system, i.e., the geometric fuzzy multiagent system (GFMAS), which is based on a geometric type-2 fuzzy inference system. GFMAS is capable of handling the various levels of uncertainty found in the inputs and rule base of the traffic signal controller. Simulation models of the agents designed in PARAMICS were tested on virtual road network replicating a section of the central business district in Singapore. A comprehensive analysis and comparison was performed against the existing traffic-control algorithms green link determining (GLIDE) and hierarchical multiagent system (HMS). The proposed GFMAS signal control outperformed both the benchmarks when tested for typical traffic-flow scenarios. Further tests show the superior performance of the proposed GFMAS in handling unplanned and planned incidents and obstructions. The promising results demonstrate the efficiency of the proposed multiagent architecture and scope for future development.

Urban traffic signal control using reinforcement learning agents

This study presents a distributed multi-agent-based traffic signal control for optimising green timing in an urban arterial road network to reduce the total travel time and delay experienced by vehicles. The proposed multi-agent architecture uses traffic data collected by sensors at each intersection, stored historical traffic patterns and data communicated from agents in adjacent intersections to compute green time for a phase. The parameters like weights, threshold values used in computing the green time is fine tuned by online reinforcement learning with an objective to reduce overall delay. PARAMICS software was used as a platform to simulate 29 signalised intersection at Central Business District of Singapore and test the performance of proposed multi-agent traffic signal control for different traffic scenarios. The proposed multi-agent reinforcement learning (RLA) signal control showed significant improvement in mean time delay and speed in comparison to other traffic control system like hierarchical multi-agent system (HMS), cooperative ensemble (CE) and actuated control.

Neural Networks for Real-Time Traffic Signal Control

Real-time traffic signal control is an integral part of the urban traffic control system, and providing effective real-time traffic signal control for a large complex traffic network is an extremely challenging distributed control problem. This paper adopts the multiagent system approach to develop distributed unsupervised traffic responsive signal control models, where each agent in the system is a local traffic signal controller for one intersection in the traffic network. The first multiagent system is developed using hybrid computational intelligent techniques. Each agent employs a multistage online learning process to update and adapt its knowledge base and decision-making mechanism. The second multiagent system is developed by integrating the simultaneous perturbation stochastic approximation theorem in fuzzy neural networks (NN). The problem of real-time traffic signal control is especially challenging if the agents are used for an infinite horizon problem, where online learning has to take place continuously once the agent-based traffic signal controllers are implemented into the traffic network. A comprehensive simulation model of a section of the Central Business District of Singapore has been developed using PARAMICS microscopic simulation program. Simulation results show that the hybrid multiagent system provides significant improvement in traffic conditions when evaluated against an existing traffic signal control algorithm as well as the SPSA-NN-based multiagent system as the complexity of the simulation scenario increases. Using the hybrid NN-based multiagent system, the mean delay of each vehicle was reduced by 78% and the mean stoppage time, by 85% compared to the existing traffic signal control algorithm. The promising results demonstrate the efficacy of the hybrid NN-based multiagent system in solving large-scale traffic signal control problems in a distributed manner

Cooperative, hybrid agent architecture for real-time traffic signal control

This paper presents a new hybrid, synergistic approach in applying computational intelligence concepts to implement a cooperative, hierarchical, multiagent system for real-time traffic signal control of a complex traffic network. The large-scale traffic signal control problem is divided into various subproblems, and each subproblem is handled by an intelligent agent with a fuzzy neural decision-making module. The decisions made by lower-level agents are mediated by their respective higher-level agents. Through adopting a cooperative distributed problem solving approach, coordinated control by the agents is achieved. In order for the multiagent architecture to adapt itself continuously to the dynamically changing problem domain, a multistage online learning process for each agent is implemented involving reinforcement learning, learning rate and weight adjustment as well as dynamic update of fuzzy relations using an evolutionary algorithm. The test bed used for this research is a section of the Central Business District of Singapore. The performance of the proposed multiagent architecture is evaluated against the set of signal plans used by the current real-time adaptive traffic control system. The multiagent architecture produces significant improvements in the conditions of the traffic network, reducing the total mean delay by 40% and total vehicle stoppage time by 50%.

A case study of two tunnels driven in the Singapore ‘Boulder Bed’ and in grouted coral sands

Abstract As part of the construction of the Singapore Mass Rapid Transit, two tunnels had to be driven from a shaft to Raffles Place Station. Each drive was approximately 170 m long and was mostly in the Singapore ‘Boulder Bed’. This formation underlies much of the Central Business District of Singapore, and is thought to be a colluvial deposit comprising sandstone boulders in a stiff clay matrix The first 60 m of the upper tunnel had a mixed face with an old coral reef above axis and the Boulder Bed below it. The corals and sands of the reef were highly permeable and had to be injected with chemical grout before tunnelling commenced. The Raffles Place area is in the commercial heart of Singapore and the tunnels passed close to two high-rise buildings. One of these buildings had an underground car park within 5 m of the upper tunnel. Shield drives in the Boulder Bed had recorded high surface settlements, and there was concern about the underground car park which was known to be sensitive to settlement. It was proposed to drive the tunnels using the New Austrian Tunnelling Method, and one of the justifications for choosing the technique was that the resulting soil movements could be minimized. In order to check this claim surface settlement arrays, inclinometers and extensometers were installed to monitor movements caused by the tunnelling. Records of ground movements measured are presented, and compared with the movements recorded above shield driven tunnels in the same deposit. Methods of grouting and testing used in the coral and sands are also reported.