Publication
Advanced Interaction-aware Motion Models for Motorcycle Trajectory Prediction: Experiments on pNEUMA Datasets
Publications associées (35)
L'évaporation du trafic, opportunités et défis pour la mobilité d'aujourd'hui et demain
Pauline Geneviève Thérèse Hosotte
This research is the result of four years of practical and scientific investigation of the phenomenon of traffic evaporation, which was considered and then demonstrated to be the opposite of traffic induction. It has anchored, in practice and in time, an o ...
EPFL2022Deep Learning Methods for Socially-Aware Human Trajectory Forecasting
The ability to forecast human motion, called ``human trajectory forecasting", is a critical requirement for mobility applications such as autonomous driving and robot navigation. Humans plan their path taking into account what might happen in the future. S ...
EPFL2022Dynamic control strategies for managing pedestrian flows
Pedestrians, like drivers, generally dislike congestion. This is true for most pedestrian environments: trains stations, airports, or shopping malls. Furthermore, pedestrian congestion also influences the attractiveness of public transportation networks. T ...
EPFL2021Travel Time Prediction for Congested Freeways With a Dynamic Linear Model
Nikolaos Geroliminis, Semin Kwak
Accurate prediction of travel time is an essential feature to support Intelligent Transportation Systems (ITS). The non-linearity of traffic states, however, makes this prediction a challenging task. Here we propose to use dynamic linear models (DLMs) to a ...
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021Motion planning for CAVs in mixed traffic, a study on roundabouts
Driving is a very challenging task to automatize despite how naturally and efficiently it may come to experienced human drivers. The complexity stems from the need to (i) understand the surrounding context and forecast how it is likely to evolve, (ii) plan ...
EPFL2020Motion Prediction Using Temporal Inception Module
Pascal Fua, Mathieu Salzmann, Wei Wang, Sena Kiciroglu
Human motion prediction is a necessary component for many applications in robotics and autonomous driving. Recent methods propose using sequence-to-sequence deep learning models to tackle this problem. However, they do not focus on exploiting different tem ...
Springer, Cham2020Prediction Error–Based Parameter Estimation for Multi-Region MFD Networks
Nikolaos Geroliminis, Isik Ilber Sirmatel
City-level traffic management remains a challenging problem. Model predictive perimeter control approaches employing macroscopic fundamental diagram (MFD) based models of large-scale urban road traffic represent a high-performance solution with substantial ...
2020Moving Horizon Estimation for Model Predictive Perimeter Control of Multi-region MFD Networks
Nikolaos Geroliminis, Isik Ilber Sirmatel
Management of road traffic in urban settings remains a challenging problem. Perimeter control schemes proposed to alleviate congestion in large-scale urban networks usually assume noise-free measurements of the traffic state, which is problematic since mea ...
2019Frequent walkers are multimodal in their actions and individualistic in their motivations, according to a qualitative study in two Swiss cities
Vincent Kaufmann, Emmanuel Pierre Jean Ravalet, Derek Pierre Christie
We define “frequent walkers” as people who walk over one hour in public space on most days of the week. Because they have successfully undergone mode shift, such pioneers have the potential to initiate change towards sustainable transportation at populatio ...
2016Traffic modeling, forecasting and assignment in large-scale networks
Today, the development and evaluation of traffic management strategies heavily relies on microscopic traffic simulation models. In case detailed input (i.e. od matrix, signal timings, etc.) is extracted and incorporated in these simulators, they can provid ...
EPFL2015