Minglu Li

TL;DR: An extensive experiment involving thousands of operational taxies in Shanghai city establishes an exponential model that can accurately depict the tail behavior of the inter-contact time in VANETs and provides fundamental guidelines on design of new vehicular mobility models in urban scenarios, new data forwarding protocols and their performance analysis.

TL;DR: The multiple directional cover sets problem (MDCS) of organizing the directions of sensors into a group of non-disjoint cover sets to extend the network lifetime is addressed and the MDCS is proved to be NP-complete and three heuristic algorithms for theMDCS are proposed.

TL;DR: Two types of traffic status-estimation algorithms, i.e., the link-based and the vehicle-based, are introduced and analyzed and the results show that estimations of the traffic status based on imperfect data are reasonably accurate.

TL;DR: Experimental results show that using 0.3% of vehicles as the samples, mobility-based clustering can accurately identify hot spots which can hardly be obtained by the latest representative algorithm UMicro.

TL;DR: An approach for metropolitan-scale traffic estimation with probe vehicles that periodically send location and speed updates to a monitoring center that can achieve an estimate error of as low as 20 percent even when more than 80 percent of probe data are missing.