Intelligent Transportation Systems

The Intelligent Transportation Systems (ITS) aims to develop intelligent transportation solutions covering land, sea and air segments that would immensely benefit a large segments of users or key stakeholders/organizations from both social and economic angles. One of the major solutions that we intend to work on is the development of an AI-based next generation traffic control system. Presently, many cities rely on coordinated traffic responsive systems which depend on inductive loop detectors to detect vehicles to control and manage the road traffic. These inductive-loop-based control approaches have been applied for several decades and exhibit major drawbacks such as reliability of loops, limited data, inaccurate data, no data such as queue lengths, etc.

CoopeRative and UnIfied Smart Traffic SystEm (CRUISE)

I2R is working with LTA to develop a locally-built next generation smart traffic light control system for Singapore, also known as CoopeRative and UnIfied Smart Traffic SystEm (CRUISE). CRUISE is designed to pick up the physical presence of vehicles (via DSRC and 4G probe data) and pedestrians. By harnessing near real-time datasets from new technologies such as global navigation satellite system (GNSS) and advance sensors for pedestrians, we are able to track various modes and classes of vehicles including autonomous vehicles, and apply advance AI and predictive capabilities to develop a comprehensive and intelligent traffic light system. Through accurate detection of road users and application of coordinated distributed control, CRUISE algorithms will help to enhance the optimisation of traffic light and pedestrian crossing timings for smoother traffic and pedestrian flow. CRUISE will also leverage of AI techniques to provide real-time traffic flow conditions for the entire road network, fast and automated detection of abnormal events such as incidents, congestion build-up, etc. As part of the CRUISE effort, we are also developing a network wide route guidance system that aims to provide a more systemic controlled and management of user route decision to coordinate the management of congestion due to unplanned incidents such as accidents.

Integrated Intelligence Driven Public Transport System (IID-PTS)

Extending the work on CRUISE, we are also leveraging on our expertise to develop new traffic control and detection strategies to improve movement of public transport. This will utilize CRUISE, ERP2, Central Fleet Management System (CFMS), new infrastructure sensors placed at bus stops and EZLINK fare card data to intelligently derive insights. Machine learning techniques will be used to carry out in-depth analysis that enables prediction of bus load and passenger demand at bus stops, which can be used to estimate and regulate total time spent at bus stops. New control schemes for regulating/facilitating the processes of bus entering and leaving bus stops/bus bays with signal control, adaptive bus lane control and pre-signaling operations for busses to bypass queues will be introduced. Besides the solutions mentioned above, the Division aims to work on the development of a city wide short term traffic prediction solution that aims to carry out fast and accurate prediction of traffic state for time-scales of up to 30 minutes. Such a solution can be used to support many other ITS systems such as traffic control, fleet management systems, route guidance, etc.

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