Traffic network uncertainties such as accident may affect the travel journey time.
Taking traffic network uncertainties and on-time arrival probability into account, a PolyU-developed intelligent transportation system helps drivers to identify the most reliable routes.
Consider two people who take two different routes, A and B, to the same destination every day. Route A has shorter average journey time than B, but the person taking route A arrives late more often than the person taking route B. This situation is quite common in Hong Kong given adverse weather and traffic accidents. Thanks to a novel system, drivers can now opt for a more reliable route which better facilitates them to arrive at their destinations on time.
Over the years, PolyU has assisted the HKSAR Government in developing and applying numerous real-time intelligent transportation systems, including Real-time Traffic Information System, Hong Kong eRouting, Hong Kong eTransport, Journey Time Indication System and Speed Map Panels. These systems can provide users with information about average journey times and traffic speeds.
However, uncertainties such as adverse weather and traffic accidents can delay the arrival time at a destination. In view of this, Prof. William Lam and his research team at the Department of Civil and Environmental Engineering developed a novel intelligent transportation system that helps drivers to identify personalised reliable driving routes.
Taking traffic network uncertainties and the probability of arriving on time into consideration, the system uses an integrated algorithm to optimise three types of traffic data for estimation of journey time – offline travel time forecasts, filtered real-time automatic vehicle identification data, and real-time video detector data.
Offered in both desktop and mobile versions, this new system enables users to pre-set criteria such as preferred departure time, arrival time and petrol cost etc., and then identifies the most reliable personalised driving route. Drivers will not only save valuable time and petrol, but also help reduce carbon emissions and ease traffic jams.
Looking ahead, the team will extend the system to cover the public transportation network and develop a people-oriented urban traffic control system, to assist transport management authorities to establish appropriate transportation strategies. ♦