Research On Estimation Of Average Link Travel-time Of Urban Area Based On Floating Car

With the continuous economic development, urbanization process progresses, theworld’s traffic problems become increasingly serious, and it is harmful to global economicdevelopment, environmental protection and improving on people’s living standards. In thiscase, the ITS (Intelligent Transportation System) showed up, providing an effective, economicalway to solve the problem of traffic congestion and traffic accidents. The floating car technologyis an emerging field of ITS, it can effectively obtain real-time and accurate traffic informationfrom the GPS data of floating cars, it is also a hot research topic in nowadays.Main work and contributions in this paper are followed:Firstly, the principle of floating car technology is introduced, the existing technology offloating car system is summarized, and floating car data processing techniques are introduced indetail.Secondly, an estimation method of average link travel-time aiming at floating car system ofsmall sample size is proposed: using traffic volume data from loop detectors, the dynamic queuelength of signalized intersection can be calculated, in which the FCD (Floating Car Data) isexcluded. Then the delay of the intersections and the normal travel time of the floating cars areobtained, and the sum of them finds the average link travel time. At last, the detailed steps of thealgorithm is designed.Thirdly, based on the new algorithm, an urban traffic information publish system isdesigned, and the urban traffic information is displayed in the Google Maps platform.The experimental results verify the feasibility of this algorithm: the system based on thealgorithm proposed in this thesis can obtain accurate average travel time data, and does not leadto instability in the average travel time data because of the floating car sample size is small. Andthis system is also able to publish the real-time, accurate urban traffic information, which isusefull to the travelers in the city.