Optimizing Long-Term Efficiency and Fairness in Ride-Hailing under Budget Constraint via Joint Order Dispatching and Driver Repositioning
Ride-hailing platforms (eg, Uber and Didi Chuxing) have become increasingly popular in
recent years. Efficiency has always been an important metric for such platforms. However …
recent years. Efficiency has always been an important metric for such platforms. However …
Deep learning for trajectory data management and mining: A survey and beyond
Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …
mining, garnering widespread attention due to its crucial role in various practical …
Self-supervised representation learning for geographical data—A systematic literature review
P Corcoran, I Spasić - ISPRS International Journal of Geo-Information, 2023 - mdpi.com
Self-supervised representation learning (SSRL) concerns the problem of learning a useful
data representation without the requirement for labelled or annotated data. This …
data representation without the requirement for labelled or annotated data. This …
Multi-job intelligent scheduling with cross-device federated learning
Recent years have witnessed a large amount of decentralized data in various (edge)
devices of end-users, while the decentralized data aggregation remains complicated for …
devices of end-users, while the decentralized data aggregation remains complicated for …
Interpreting trajectories from multiple views: A hierarchical self-attention network for estimating the time of arrival
Z Chen, X Xiao, YJ Gong, J Fang, N Ma… - Proceedings of the 28th …, 2022 - dl.acm.org
Estimating the time of arrival is a crucial task in intelligent transportation systems. Although
considerable efforts have been made to solve this problem, most of them decompose a …
considerable efforts have been made to solve this problem, most of them decompose a …
Service time prediction for delivery tasks via spatial meta-learning
Service time is a part of time cost in the last-mile delivery, which is the time spent on
delivering parcels at a certain location. Predicting the service time is fundamental for many …
delivering parcels at a certain location. Predicting the service time is fundamental for many …
Optimizing long-term efficiency and fairness in ride-hailing via joint order dispatching and driver repositioning
The ride-hailing service offered by mobility-on-demand platforms, such as Uber and Didi
Chuxing, has greatly facilitated people's traveling and commuting, and become increasingly …
Chuxing, has greatly facilitated people's traveling and commuting, and become increasingly …
Dueta: Traffic congestion propagation pattern modeling via efficient graph learning for eta prediction at baidu maps
Estimated time of arrival (ETA) prediction, also known as travel time estimation, is a
fundamental task for a wide range of intelligent transportation applications, such as …
fundamental task for a wide range of intelligent transportation applications, such as …
CatETA: A categorical approximate approach for estimating time of arrival
Estimated time of arrival (ETA) is one of the critical services offered by navigation and hailing
providers. The majority of existing solutions approach ETA as a regression problem and …
providers. The majority of existing solutions approach ETA as a regression problem and …
DuIVA: An Intelligent Voice Assistant for Hands-free and Eyes-free Voice Interaction with the Baidu Maps App
Mobile map apps such as the Baidu Maps app have become a ubiquitous and essential tool
for users to find optimal routes and get turn-by-turn navigation services while driving …
for users to find optimal routes and get turn-by-turn navigation services while driving …