Personalized route recommendation for ride-hailing with deep inverse reinforcement learning and real-time traffic conditions
Personalized route recommendation aims to recommend routes based on users' route
preference. The vast amount of GPS trajectories tracking driving behavior has made deep …
preference. The vast amount of GPS trajectories tracking driving behavior has made deep …
AdaBoost-Bagging deep inverse reinforcement learning for autonomous taxi cruising route and speed planning
Taxi cruising route planning has attracted considerable attention, and relevant studies can
be broadly categorized into three main streams: recommending one or multiple areas …
be broadly categorized into three main streams: recommending one or multiple areas …
Inferring travel patterns and the attractiveness of touristic areas based on fusing Wi-Fi sensing data and GPS traces with a Kyoto Case study
Y Gao, JD Schmöcker - Transportation Research Part C: Emerging …, 2024 - Elsevier
We establish a methodology that fuses point data with trajectory data leading to trip chains
that reflect whether a person has visited key locations. In our study the point data are Wi-Fi …
that reflect whether a person has visited key locations. In our study the point data are Wi-Fi …
Modelling of pedestrian movements near an amenity in walkways of public buildings
Urban living experience is centered around public buildings where many pedestrians are
engaging with services and functions provided in the form of amenities. Knowledge of …
engaging with services and functions provided in the form of amenities. Knowledge of …
Estimation of walking patterns in a touristic area with Wi-Fi packet sensors
Y Gao, JD Schmöcker - Transportation research part C: emerging …, 2021 - Elsevier
We propose a methodology for using the records from Wi-Fi packet sensors to model route
choice and time spent at different locations within a tourist area. In contrast to other route …
choice and time spent at different locations within a tourist area. In contrast to other route …
Anomalous ride-hailing driver detection with deep transfer inverse reinforcement learning
The rapid expansion in group size of online ride-hailing drivers has made anomalous driver
detection become a critical issue, which substantially affects the safety and operation …
detection become a critical issue, which substantially affects the safety and operation …
A generalized trajectories-based evaluation approach for pedestrian evacuation models
The fundamental diagram and self-organized phenomena in crowds are widely used to test
the applicability of evacuation models. These benchmarks are good indicators for the validity …
the applicability of evacuation models. These benchmarks are good indicators for the validity …
Distinguishing different types of city tourists through clustering and recursive logit models applied to Wi-Fi data
Y Gao, JD Schmöcker - Asian Transport Studies, 2022 - Elsevier
We discuss the possibilities to distinguish different types of tourists based on Wi-Fi sensor
data. The data are obtained from 20 sensors employed in Higashiyama, Kyoto, which is an …
data. The data are obtained from 20 sensors employed in Higashiyama, Kyoto, which is an …
Environment-deterministic pedestrian behavior? New insights from surveillance video evidence
The study of pedestrians' walking behavior, especially its relationship with environmental
factors, is of great theoretical and practical importance. However, at the micro-scale, the …
factors, is of great theoretical and practical importance. However, at the micro-scale, the …
Personalized origin–destination travel time estimation with active adversarial inverse reinforcement learning and Transformer
Travel time estimation is important for instant delivery, vehicle routing, and ride-hailing. Most
studies estimate the travel time of specified routes, and only a few studies pay attention to …
studies estimate the travel time of specified routes, and only a few studies pay attention to …