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Hong Kong is known for its excellent and efficient transport infrastructure. For many years, PolyU has been committed to enhancing transport efficiency in innovative ways, such as by collating real-time data on Smart City Platform to aid city planning and management, or by introducing new EV charging systems to improve traffic efficiency and better utilise electricity resource. PolyU has also established different Intelligent Transport Systems, including the Seamless Urban Navigation System, Reliable Intelligent Transportation Systems for Drivers and the mobile application "HKeTransport".  

Smart City Platform: A Comprehensive Spatial Data Infrastructure

A platform for seamless data fusion, AI-based urban object cognition, visualisation and analysis of massive 3D urban models, and spatial big data analytics

Principal Investigator: Prof. John Wenzhong SHI, Department of Land Surveying and Geo-Informatics
The platform can be used to create digital city replicas for acquiring insights into urban situations, testing solutions and conducting technological research. Incorporating 3D city modelling, AI-based urban object cognition, web-based visualisation and analytics technologies, it enables seamless fusion of massive geometrical information, 3D LiDAR data, image data and spatial big data from various sources, including public and private agencies, to provide a realistic and accurate representation of a city. A 3D spatial data acquisition system has been specially developed to enhance both outdoor and indoor 3D environment of buildings. It can identify indoor objects and automatically reconstruct a digital model (Building Information Model) of the indoor environment from raw LiDAR data. Integrating the aboveground and underground aspects of a city, we have developed a new set of 3D model specifications with multiple detail levels with reference to the standards of the underground utility industry. The specifications are included in the Smart City Platform, and have been submitted to the Open Geospatial Consortium (OGC) for the adoption as an international standard.

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HKeTransport: a Multi-modal Public Transport Route Search Platform

Providing all possible route combinations with real-time journey times and fares

Principal Investigator: Dr Lilian PUN-CHENG, Department of Land Surveying and Geo-Informatics
Public transport is the only or preferred way of local travel for most commuters in Hong Kong, yet there was a lack of an information platform that covering different modes of public transport. HKeTransport, a multi-modal public transport route search platform, was developed as a result of a collaboration between Transport Department and PolyU. It covers multiple transport modes, including railway, bus, mini-bus, ferry and tram. Key features of the system include provision of multi-modal information, operating times and route solutions using geomatics technology. Users can search for route solutions and sort search results by criteria such as time, fare, number of interchanges, etc. HKeTransport has been incorporated with in HKeMobility, a onestop platform established by the Transport Department for both road users and public transport passengers to access needed information via a mobile app or a website.

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Reliable Intelligent Transportation Systems for Drivers

Provide accurate real-time traffic information on major routes in Hong Kong

Principal Investigator: Ir Prof. William H.K. LAM, Department of Civil and Environmental Engineering
The intelligent transportation systems use an advanced algorithm to integrate and optimize three types of traffic data, including (1) filtered real-time automatic vehicle identification data; (2) realtime video detector data; and (3) offline travel time forecasts. The integrated data is used for real-time estimation of average journey time and traffic speed on selected routes which is updated once every two minutes. This integrated algorithm has been adopted in Hong Kong’s Journey Time Indication System and Speed Map Panel System, which display alternative route journey time and sectional traffic speed colour on traffic sign boards, to help motorists choose the most appropriate routes in order to avoid traffic congestion, and to help transport authorities monitor the traffic conditions for better traffic management.

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Seamless Urban Navigation System

Improve indoor and outdoor positioning performance and accuracy through multiple sensor integration

Principal Investigator: Prof. Wu CHEN, Department of Land Surveying and Geo-Informatics
Global Navigation Satellite System (GNSS) is an important infrastructure in global economic growth. However, due to signal occlusion and multipath effects in dense urban areas, the error of positioning can be as much as several hundred meters, hindering the development of smart cities. Applying our research outcomes in GNSS, this system can solve urban positioning problem via multiple system integration. It integrates the data from different GNSS (e.g. GPS, Beidou, GLONASS and Galileo) to provide outdoor positioning with high accuracy, and utilizes our positioning algorithms and models can mitigate systematic errors and inter-system differences. With the use of 3D city models, it can correct the measurements of distance and apply to dense urban areas. Besides, it can also work with smartphone built-in sensors (e.g. gyroscope, accelerometer, magnetometer, inertia measurement unit and step counter) to provide accurate indoor positioning.

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EV Charging System with Intelligent Load Management Control

Advanced control algorithms for intelligent distribution of incoming supply to all connected chargers

Principal Investigator: Dr Wai-lok CHAN, Department of Electrical Engineering
The lack of charging facilities is a common complaint among EV drivers. In fact, the number of chargers allowed for installation in a carpark depends on the size of its electricity resource. Our charging system provides intelligent load management using our advanced control algorithms. Under the condition that the incoming supply remains unchanged, the system can intelligently distribute the supply current to all connected EV chargers according to the actual electricity demand of each EV. It can optimize the utilization of electricity resource by allowing installation of more additional chargers, enabling full-power charging and reducing at least 50% of energy provision. It is expected the system will be adopted in 8 carparks in Hong Kong, involving over 100 chargers, by the end of 2019.

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PolyU showcased these research projects in Virtual InnoCarnival 2020. Come and visit our virtual booth to find out how you can be benefited from our state-of-the-art technology.
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