[HTML][HTML] How machine learning informs ride-hailing services: A survey
In recent years, online ride-hailing services have emerged as an important component of
urban transportation system, which not only provide significant ease for residents' travel …
urban transportation system, which not only provide significant ease for residents' travel …
Deep dispatching: A deep reinforcement learning approach for vehicle dispatching on online ride-hailing platform
The vehicle dispatching system is one of the most critical problems in online ride-hailing
platforms, which requires adapting the operation and management strategy to the dynamics …
platforms, which requires adapting the operation and management strategy to the dynamics …
Review of shared online hailing and autonomous taxi services
As the technology of autonomous vehicle develops, online hailing autonomous taxi system
is regarded as one of the most popular public transportation services in the future. Studies …
is regarded as one of the most popular public transportation services in the future. Studies …
Graph neural network reinforcement learning for autonomous mobility-on-demand systems
Autonomous mobility-on-demand (AMoD) systems represent a rapidly developing mode of
transportation wherein travel requests are dynamically handled by a coordinated fleet of …
transportation wherein travel requests are dynamically handled by a coordinated fleet of …
Profit model for electric vehicle rental service: Sensitive analysis and differential pricing strategy
Electric vehicle rental service is an effective operation mode to promote the application of
EVs in terms of the energy conservation and the environmental protection for urban …
EVs in terms of the energy conservation and the environmental protection for urban …
PassGoodPool: Joint passengers and goods fleet management with reinforcement learning aided pricing, matching, and route planning
K Manchella, M Haliem, V Aggarwal… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The ubiquitous growth of mobility-on-demand services for passenger and goods delivery
has brought various challenges and opportunities within the realm of transportation systems …
has brought various challenges and opportunities within the realm of transportation systems …
Deep reinforcement learning with graph representation for vehicle repositioning
On-demand ride services, eg, taxi companies, ridesourcing/transportation network
companies (TNCs), play a vital role in nowadays transportation modes. The relocation …
companies (TNCs), play a vital role in nowadays transportation modes. The relocation …
Rebalancing and charging scheduling with price incentives for car sharing systems
G Guo, M Kang - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
This paper studies the joint problem of optimal pricing, charging scheduling and rebalancing
for one-way car sharing systems. Firstly, a price driven customers travel mechanism is given …
for one-way car sharing systems. Firstly, a price driven customers travel mechanism is given …
A systematic literature review on machine learning in shared mobility
J Teusch, JN Gremmel, C Koetsier… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
Shared mobility has emerged as a sustainable alternative to both private transportation and
traditional public transport, promising to reduce the number of private vehicles on roads …
traditional public transport, promising to reduce the number of private vehicles on roads …
Evaluating crisis perturbations on urban mobility using adaptive reinforcement learning
The objective of this study is to propose and test an adaptive reinforcement learning model
that can learn the patterns of human mobility in a normal context and simulate the mobility …
that can learn the patterns of human mobility in a normal context and simulate the mobility …