SWAT
On-demand Fleet Optimization
Jarrold Ong, CEOSWAT offers a solution that facilitates a high-capacity bus pooling service to reduce traffic congestions, improve traveling convenience for commuters, and optimize resources for bus operators. The company employs a dynamic routing smart mobility engine, which proves vital in offering a comfortable journey for both the riders and the bus operators. It even allows vehicles to react to incidents such as road closures in real time and accurately predict the estimated time of arrival (ETA). Such an information set assures the riders a reliable, fast, affordable, and convenient journey. SWAT’s solution can be applied to various use cases for both commuters and operators. These include first and last mile services to commuters, off-peak fleet optimisation and path planning for autonomous vehicles. One of the key elements of SWAT’s solution is the driver application, which helps the operators navigate through dynamic routes with real-time stop changes.
It’s a future-proof application, which will even support autonomous vehicles when they hit the road.
SWAT customizes its solution for the employers by analyzing the employee databases. They study the unique shift patterns of employees and develop an understanding of the traveling needs of every individual. Subsequently, the firm draws up simulations to find out the most efficient way to arrange bus pooling service. Such dynamic routing is accomplished using big data and machine learning to effectively solve the problems of traffic congestion and reduce the number of vehicles on the road, while simultaneously enabling commuters to enjoy closer-to-door transport. The company’s capabilities and continuous efforts to ensure convenient travel have helped them top multiple entries in the global Li & Lim benchmark.
Unlike their competitors, SWAT hasn’t adopted the traditional approach for arranging fixed shuttle service; they rather employ sophisticated algorithms to assist clients across various industries in assuring utmost convenience to their employees in daily commute. For instance, one of the firm’s clients had their office located at a relatively inaccessible part of Singapore. With a majority of the employees living far from the office, the client earlier used to provide shuttle service for a minimal number of employees. Consequently, a majority of their employees took more than an hour for a one-way commute to work. Using SWAT’s technology, the client could provide on-demand bus pooling service with greater stops coverage to their employees, and in turn, reduce their travel time. Eventually, the employees were much happier coming to work as they could now enjoy a faster and more convenient way of commuting.
Currently working with both corporations and government bodies around the world, SWAT continues to improve commuters’ journeys worldwide. Recently, the firm and Singapore’s government have announced the launch of first on-demand public bus services trial, as a part of the government’s initiative to improve the public transportation system. “Following the announcement, different governments across the globe have expressed interest in exploring how we can work with them to improve their local transportation systems,” says Jarrold Ong, CEO of SWAT. The firm is excited about the utilization of its algorithm to remove as a central command system that enables the use of on-demand fleet and orchestrates the movements of the fleets by controlling and optimizing how commuters travel. Subsequently, the firm is working towards supporting autonomous vehicles in the foreseeable future.
SWAT customizes its solution for the employers by analyzing the employee databases. They study the unique shift patterns of employees and develop an understanding of the traveling needs of every individual. Subsequently, the firm draws up simulations to find out the most efficient way to arrange bus pooling service. Such dynamic routing is accomplished using big data and machine learning to effectively solve the problems of traffic congestion and reduce the number of vehicles on the road, while simultaneously enabling commuters to enjoy closer-to-door transport. The company’s capabilities and continuous efforts to ensure convenient travel have helped them top multiple entries in the global Li & Lim benchmark.
Unlike their competitors, SWAT hasn’t adopted the traditional approach for arranging fixed shuttle service; they rather employ sophisticated algorithms to assist clients across various industries in assuring utmost convenience to their employees in daily commute. For instance, one of the firm’s clients had their office located at a relatively inaccessible part of Singapore. With a majority of the employees living far from the office, the client earlier used to provide shuttle service for a minimal number of employees. Consequently, a majority of their employees took more than an hour for a one-way commute to work. Using SWAT’s technology, the client could provide on-demand bus pooling service with greater stops coverage to their employees, and in turn, reduce their travel time. Eventually, the employees were much happier coming to work as they could now enjoy a faster and more convenient way of commuting.
Currently working with both corporations and government bodies around the world, SWAT continues to improve commuters’ journeys worldwide. Recently, the firm and Singapore’s government have announced the launch of first on-demand public bus services trial, as a part of the government’s initiative to improve the public transportation system. “Following the announcement, different governments across the globe have expressed interest in exploring how we can work with them to improve their local transportation systems,” says Jarrold Ong, CEO of SWAT. The firm is excited about the utilization of its algorithm to remove as a central command system that enables the use of on-demand fleet and orchestrates the movements of the fleets by controlling and optimizing how commuters travel. Subsequently, the firm is working towards supporting autonomous vehicles in the foreseeable future.
