Vehicle trajectory prediction based on motion model and maneuver recognition

By Adam Houénou, P. Bonnifait, V. Berge-Cherfaoui, W. Yao. 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2013

390 citations recorded by the source corpus.

Subfields: Automotive Engineering, Building and Construction, Signal Processing

View Paper: https://www.semanticscholar.org/paper/dd1d355aabe98a856137fc11ed996563ed1848f5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Fawzi Nashashibi
2. Anne Verroust-Blondet
3. Kaouther Messaoud
4. Itheri Yahiaoui
5. Nachiket Deo
6. Mohan Manubhai Trivedi
7. Mooi Choo Choo Chuah
8. Xin Li

In Building and Construction

1. Mohan Manubhai Trivedi
2. Nachiket Deo
3. Anne Verroust-Blondet
4. Kaouther Messaoud
5. Fawzi Nashashibi
6. Itheri Yahiaoui
7. Mooi Choo Choo Chuah
8. Xin Li

In Signal Processing

1. Anne Verroust-Blondet
2. Kaouther Messaoud
3. Fawzi Nashashibi
4. Itheri Yahiaoui
5. Mohan Manubhai Trivedi
6. Florent Altch'e
7. Peng Liu
8. Nachiket Deo

Citations in the corpus

• Vehicle Trajectory Prediction by Integrating Physics- and Maneuver-Based Approaches Using Interactive Multiple Models (2018, methodology): “The invariable coefficient model integrates the physics- and maneuver-based models with a fixed coefficient function [8].”
• GRIP: Graph-based Interaction-aware Trajectory Prediction (2019, background): “Prior works [1], [2], [3], [4], [5] proposed to predict future locations by recognizing maneuver”
• Multi-Modal Trajectory Prediction of Surrounding Vehicles with Maneuver based LSTMs (2018, methodology): “Polynomial fitting [13], maneuver specific motion models [14], Gaussian processes [11], [15], Gaussian mixture models [10] have been used for trajectory prediction.”
• An LSTM network for highway trajectory prediction (2017, methodology): “Many techniques have already been explored for behavior prediction, such as hidden Markov models [3], [4], Kalman filtering [5], Support Vector Machines [6], [7] or directly using a vehicle model [8]; more recently, artificial neural network approaches have also been proposed [9]–[11].”
• How Would Surround Vehicles Move? A Unified Framework for Maneuver Classification and Motion Prediction (2018, methodology): “Most approaches involve using heuristics [25] or training classifiers such as SVMs [21], [22], HMMs [14], [19], [20], [23], LSTMs [24] and Bayesian networks [26] using motion based features such as speed, acceleration, yaw rate and other context information such as lane position, turn signals, dista”
• Convolutional Social Pooling for Vehicle Trajectory Prediction (2018, methodology): “Heuristic based classifiers [8], Bayesian networks [21], hidden Markov models [6, 14], random forest classifiers [20] and recurrent neural networks have been used for maneuver recognition.”
• Attention Based Vehicle Trajectory Prediction (2020, background): “Houenou et al. [16] conceive a maneuvers recognition module, then, generate different continuous realizations of the predicted maneuver.”
• Spacetime Gaussian Feature Splatting for Real-Time Dynamic View Synthesis (2023, neutral): “Motivated by [24, 35], we choose polynomial function: where µ i ( t ) denotes the spatial position of an STG at time t .”
• Classification of Highway Lane Change Behavior to Detect Dangerous Cut-in Maneuvers (2015, methodology): “For the second portion, with the predicted maneuver, the future trajectory of a perceived vehicle is generated using trajectory prediction approaches ( 4–6 ).”