Map matching is the core issue for floating car technology, which needs to be well addressed. For centralized map matching with floating car data, many general map matching algorithms are not suitable, due to the long time interval and large amount of data. To address this problem, a novel map matching algorithm is proposed, in which two new concepts, namely Confidence Point (CP) and Maximum Delay Constraint Dynamic Time Window (MDCDTW), are introduced. This algorithm integrates the simple weight matching algorithm and the optimal matching path search algorithm which takes into account the topology information of roads as well as the arrival reasonable time restriction of vehicle. Using this algorithm, we can first set the maximum delay constraint (real-time constraint), and then obtain the optimal matching result by considering minimal information of historical vehicular trajectories and delay. Besides, this algorithm has no cumulative matching error due to the CP, so it doesn't affect the subsequent matching. The proposed algorithm is tested on Guangzhou complex urban road network. The performance of the algorithm is very promising for the normal roads and the highly complicated roads, such as the elevated roads and parallel roads.
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