TY - BOOK ID - 137012401 TI - AI-Based Transportation Planning and Operation PY - 2021 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - autoencoder KW - deep learning KW - traffic volume KW - vehicle counting KW - CycleGAN KW - bottleneck and gridlock identification KW - gridlock prediction KW - urban road network KW - long short-term memory KW - link embedding KW - traffic speed prediction KW - traffic flow centrality KW - reachability analysis KW - spatio-temporal data KW - artificial neural network KW - context-awareness KW - dynamic pricing KW - reinforcement learning KW - ridesharing KW - supply improvement KW - taxi KW - preventive automated driving system KW - automated vehicle KW - traffic accidents KW - deep neural networks KW - vehicle GPS data KW - driving cycle KW - micro-level vehicle emission estimation KW - link emission factors KW - MOVES KW - black ice KW - CNN KW - prevention UR - https://www.unicat.be/uniCat?func=search&query=sysid:137012401 AB - The purpose of this Special Issue is to create an an academic platform whereby high-quality research papers are published on the applications of innovative AI algorithms to transportation planning and operation. The authors present their original research articles related to the applications of AI or machine-learning techniques to transportation planning and operation. The topics of the articles encompass traffic surveillance, traffic safety, vehicle emission reduction, congestion management, traffic speed forecasting, and ride sharing strategy. ER -