Context-aware taxi dispatching at city-scale using deep reinforcement learning
Proactive taxi dispatching is of great importance to balance taxi demand-supply gaps among
different locations in a city. Recent advances primarily rely on deep reinforcement learning …
different locations in a city. Recent advances primarily rely on deep reinforcement learning …
Context-Aware Taxi Dispatching at City-Scale Using Deep Reinforcement Learning
Z Liu, J Li, K Wu - IEEE Transactions on Intelligent Transportation …, 2022 - trid.trb.org
Proactive taxi dispatching is of great importance to balance taxi demand-supply gaps among
different locations in a city. Recent advances primarily rely on deep reinforcement learning …
different locations in a city. Recent advances primarily rely on deep reinforcement learning …
[PDF][PDF] Context-Aware Taxi Dispatching at City-Scale Using Deep Reinforcement Learning
Z Liu, J Li, K Wu - IEEE TRANSACTIONS ON INTELLIGENT …, 2022 - liuzhidan.github.io
Proactive taxi dispatching is of great importance to balance taxi demand-supply gaps among
different locations in a city. Recent advances primarily rely on deep reinforcement learning …
different locations in a city. Recent advances primarily rely on deep reinforcement learning …
Context-Aware Taxi Dispatching at City-Scale Using Deep Reinforcement Learning
Z Liu, J Li, K Wu - IEEE Transactions on Intelligent Transportation …, 2022 - repository.ust.hk
Proactive taxi dispatching is of great importance to balance taxi demand-supply gaps among
different locations in a city. Recent advances primarily rely on deep reinforcement learning …
different locations in a city. Recent advances primarily rely on deep reinforcement learning …
[PDF][PDF] Context-aware taxi dispatching at city-scale using deep reinforcement learning
Z Liu, J Li, K Wu - IEEE Transactions on Intelligent Transportation …, 2020 - drive.google.com
Proactive taxi dispatching is of great importance to balance taxi demand-supply gaps among
different locations in a city. Recent advances primarily rely on deep reinforcement learning …
different locations in a city. Recent advances primarily rely on deep reinforcement learning …