@article{
 title = {An Assignment-Based Approach to Efficient Real-Time City-Scale Taxi Dispatching},
 type = {article},
 year = {2016},
 identifiers = {[object Object]},
 keywords = {Computational modeling,Dispatching,Heuristic algorithms,Public transportation,Real-time systems,Vehicle dynamics,Vehicles},
 pages = {68-77},
 volume = {31},
 websites = {http://ieeexplore.ieee.org/document/7389909/},
 month = {1},
 publisher = {IEEE},
 id = {e738ef03-e049-3594-9d80-eea7e2fc6b90},
 created = {2020-01-15T12:34:14.050Z},
 file_attached = {false},
 profile_id = {b8bb86b0-2c01-3ebb-b066-8c77b393d3cc},
 group_id = {8fe4ad94-b417-3a1e-85a0-b9d7ccc60bbd},
 last_modified = {2020-01-15T12:34:16.638Z},
 read = {true},
 starred = {true},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Maciejewski2016},
 folder_uuids = {ab988724-fb48-4cfc-b686-2d2750b932cc},
 private_publication = {false},
 abstract = {© 2001-2011 IEEE.This study proposes and evaluates an efficient real-time taxi dispatching strategy that solves the linear assignment problem to find a globally optimal taxi-to-request assignment at each decision epoch. The authors compare the assignment-based strategy with two popular rule-based strategies. They evaluate dispatching strategies in detail in the city of Berlin and the neighboring region of Brandenburg using the microscopic large-scale MATSim simulator. The assignment-based strategy produced better results for both drivers (less idle driving) and passengers (less waiting). However, computing the assignments for thousands of taxis in a huge road network turned out to be computationally demanding. Certain adaptations pertaining to the cost matrix calculation were necessary to increase the computational efficiency and assure real-time responsiveness.},
 bibtype = {article},
 author = {Maciejewski, Michal and Bischoff, Joschka and Nagel, Kai},
 journal = {IEEE Intelligent Systems},
 number = {1}
}

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