nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
1 |
A Deep Reinforcement Learning Based Ramp Metering Control Method Considering Ramp Outflow ⁎ ⁎ This work was supported by:(1) The SDHS Science and Technology Program Projects: Research on Key Technologies for Safety Design and Parallel Management and Control of Operational Risks of Highway Composite Hub Interchange Groups (HS2023B044) (2)The Provincial Key Research and Development Program of Zhejiang (project number: 2022C01129) (3)Ningbo International Science and Technology Cooperation Project: Theoretical and Technological Research on Cooperative traffic Control of Port Collection and Distribution Highway(2023H020)
|
Cheng, Junwei |
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58 |
10 |
p. 200-205 |
artikel |
2 |
A Diagnostic Machine Learning Algorithm for Air Brakes in Commercial Vehicles⁎
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Ganeshan, Reyshwanth |
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58 |
10 |
p. 75-80 |
artikel |
3 |
Alleviating morning commute congestion through school start time optimization: An exhaustive search approach
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Georgantas, Antonios |
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58 |
10 |
p. 219-224 |
artikel |
4 |
A Mobility Equity Metric for Multi-Modal Intelligent Transportation Systems ⁎ ⁎ This research was supported by NSF under Grants CNS-2149520 and CMMI-2219761.
|
Bang, Heeseung |
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58 |
10 |
p. 114-119 |
artikel |
5 |
Analysis of Driver Aggression’s Effects on Safety-Related Microscopic Traffic Behaviors Using Driving Simulator and Surrogate Measures
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Hong, Dawei (David) |
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58 |
10 |
p. 243-248 |
artikel |
6 |
Analyzing Transportation Equity in the D.C. Metropolitan Area Using Large-Scale Agent-Based Modeling and Simulation
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Paudel, Akshaya |
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58 |
10 |
p. 249-254 |
artikel |
7 |
A Region-wide Deployment of an Automated Real-time Truck Parking Availability Detection and Information Dissemination System ⁎ ⁎ This material is based upon work partially supported by Kansas DOT, the Minnesota Robotics Institute (MnRI), Honeywell, and the National Science Foundation through grants CNS-1439728, CNS-1531330, CNS-1939033, and CNS-1919631. USDA/NIFA has also supported this work through grants 2020-67021-30755 and 2023-67021-39829.
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Morris, Ted L. |
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58 |
10 |
p. 267-272 |
artikel |
8 |
Assessing the Impacts of Merge and Speed Control Strategies on Highway Work Zone Safety and Operations Using Artificial Intelligence and Advanced Sensors
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Liu, Ruifeng |
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58 |
10 |
p. 194-199 |
artikel |
9 |
A Subsumption Scheme for Emergent Collaboration of Self-Driving Vehicles in Intersections ⁎ ⁎ The research leading to these results has been performed in part within the project “VeDi 2025 – Veicolo Digitale 2025” co-funded by MIMIT (Fondo Crescita Sostenibile) and Provincia Autonoma di Trento, Project nr. F/040026/00/X31 grant agreement number 2049 dated 07/05/2020 and in part within the EU-funded program FSE REACT EU, D.M.1062 by the Italian Ministry of Education.
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Cherubini, Antonello |
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58 |
10 |
p. 43-47 |
artikel |
10 |
A System Dynamics Model Promoting Active Transportation Modes for Urban Sustainability
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Papageorgiou, George |
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58 |
10 |
p. 255-260 |
artikel |
11 |
Automatic Drawbridge Scheduling by Integrating Highway and Waterway Traffic Flow Information
|
Mooij, M.J. |
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58 |
10 |
p. 290-295 |
artikel |
12 |
Collision Avoidance Safety Filter for an Autonomous E-Scooter using Ultrasonic Sensors ⁎ ⁎ F. Allgöwer is thankful that this work was funded by the Ministry of Science, Research and the Arts of the State of Baden-Württemberg (MWK) in the context of the “MobiLab” Project. R. Strässer, D. Meister, M. Seidel thank the Graduate Academy of the SC SimTech for its support. F. Brändle thanks the International Max Planck Research School for Intelligent Systems (IMPRS-IS) for its support.
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Strässer, Robin |
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58 |
10 |
p. 22-28 |
artikel |
13 |
Contents
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58 |
10 |
p. i-vii |
artikel |
14 |
Decentralised Motion Planning for Autonomous Mining Haulage Trucks using Prioritised Multi-Agent MPPI
|
Matsui, Kenta |
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58 |
10 |
p. 154-161 |
artikel |
15 |
Distributed event-triggered constrained control for linear homogeneous vehicle platoons
|
Gaagai, Ramzi |
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58 |
10 |
p. 48-54 |
artikel |
16 |
Dynamic origin-destination matrix estimation for networks operating under free-flow conditions using macroscopic flow dynamics
|
Englezou, Yiolanda |
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58 |
10 |
p. 213-218 |
artikel |
17 |
Efficient Mixed Traffic Intersection Management under Uncertainty ⁎ ⁎ This work is supported by the European Union (i. Horizon 2020 Teaming, KIOS CoE, No. 739551, and ii. ERC, URANUS, No. 101088124) and the Government of the Republic of Cyprus through the Deputy Ministry of Research, Innovation, and Digital Strategy. Views and opinions expressed are, however, those of the authors only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.
|
Pappas, Michail Angelos |
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58 |
10 |
p. 162-167 |
artikel |
18 |
eMob-Twin: A Digital Twin for Electromobility Flexibility Forecast ⁎ ⁎ Funds from PoC eMob-Twin 2023-24, and from the ERC-AdG Scale-Free Control for Complex Physical Network Systems. Scale-FreeBack, Canudas-de-Wit (2017-23)
|
Canudas-de-Wit, Carlos |
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58 |
10 |
p. 29-36 |
artikel |
19 |
Energy-efficient torque distribution strategy for four wheel drive electric vehicles based on Traffic zone ⁎ ⁎ This work is funded by the ANR (National Research Agency). It falls within the framework of the V3EA research project (Véhicule Electrique, Econome en Energie et Autonome)
|
Achdad, Reda |
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58 |
10 |
p. 1-6 |
artikel |
20 |
Energy-optimal Speed Regulation for CAVs in Urban Mixed Traffic with Induced Lane Changes
|
Hu, Yonghui |
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58 |
10 |
p. 55-60 |
artikel |
21 |
Frequency Based Supervisory Power Management Approach for Battery-Supercapacitor Electric Vehicle Considering Road Slope
|
Upadhyaya, Ashruti |
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58 |
10 |
p. 7-13 |
artikel |
22 |
Goal Programming using the A* Algorithm to Optimize Energy Consumption in Train Operations
|
Aredah, Ahmed |
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58 |
10 |
p. 126-133 |
artikel |
23 |
Hierarchical Probabilistic Decision-making for Intelligent Heavy Vehicles in Freight Transportation Networks
|
Feng, Qi |
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58 |
10 |
p. 273-278 |
artikel |
24 |
Highly Interactive Self-Supervised Learning for Multi-Modal Trajectory Prediction ⁎ ⁎ This work was supported by the National Key R&D Program of China under Grant 2022ZD0162200, the National Natural Science Foundation of China under Grant 62271485, and the Fundamental Research Funds for the Central Universities, CHD, under Grant 300102343513
|
Xie, Wenda |
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58 |
10 |
p. 231-236 |
artikel |
25 |
Impacts of g-g-v Constraints Formulations on Online Minimum-Time Vehicle Trajectory Planning ⁎ ⁎ This work was supported by the European Union Next-GenerationEU (Piano Nazionale di Ripresa e Resilienza (PNRR) -Missione 4 Componente 1, Investimenti 3.4 e 4.1 - Decreto del Minis-tero dell’Universit à e della Ricerca n.351 del 09/04/2022) within the Italian National Ph.D. Program in Autonomous Systems (DAuSy).
|
Piccinini, Mattia |
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58 |
10 |
p. 87-93 |
artikel |
26 |
Implications of Alternative Communications and Sensing Technologies for Implementing Variable Speed Limit Control through Connected Vehicles: Sag Curve as a Case Study
|
Nezafat, Reza Vatani |
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58 |
10 |
p. 108-113 |
artikel |
27 |
Improving Risk-averse Distributional Reinforcement Learning with Adaptive Risk-seeking Exploration
|
Wang, Zhidong |
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58 |
10 |
p. 237-242 |
artikel |
28 |
IMTRAC: Image-Based Modeling for Transformative Traffic Control via Foundation Models
|
Dai, Xingyuan |
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58 |
10 |
p. 225-230 |
artikel |
29 |
Integrated Reinforcement Learning and Optimization for Railway Timetable Rescheduling
|
Zhang, Hengkai |
|
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58 |
10 |
p. 310-315 |
artikel |
30 |
Investigating the Significance of 4.0 Digital Transformation on the Improvement of Railway Transport System in South Africa.
|
Olalere, I.O |
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58 |
10 |
p. 316-320 |
artikel |
31 |
Joint Vehicle Path Planning for Interruptible 1-D Snake-like Platoons and 2D Flocks in Lane-free Traffic
|
Dabestani, Niloufar |
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58 |
10 |
p. 61-68 |
artikel |
32 |
Max-Pressure Control utilizing Total Movement Delay ⁎ ⁎ This research was supported by the Technion - Israel Institute of Technology and ISTRC transportation research fund.
|
Zoabi, Razi |
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58 |
10 |
p. 206-212 |
artikel |
33 |
Modelling Yielding of Slow-Moving Vehicles: Application of Drone Data ⁎ ⁎ This work was supported by the Ministry of Human Resources and Development, Government of India, under the Prime Minister Research Fellowship (PMRF) scheme and the Ministry of Skill Development and Entrepreneurship, Government of India, through the grant EDD/14-15/023/MOLE/NILE.
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Raj, Abhishek |
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58 |
10 |
p. 279-284 |
artikel |
34 |
MPTree: A Sampling-based Vehicle Motion Planner for Real-time Obstacle Avoidance
|
Piazza, Mattia |
|
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58 |
10 |
p. 146-153 |
artikel |
35 |
On Accessibility Fairness in Intermodal Autonomous Mobility-on-Demand Systems ⁎ ⁎ This publication is partially supported by the project NEON (with project number 17628 of the research program Crossover, which is (partly) financed by the Dutch Research Council (NWO)), and by Eindhoven Artificial Intelligence Systems Institute (EAISI).
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Salazar, Mauro |
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58 |
10 |
p. 327-333 |
artikel |
36 |
Optimal control of electric automated buses in intercity lines: scenario-based analysis of the Pareto-optimal solutions
|
Pasquale, C. |
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58 |
10 |
p. 37-42 |
artikel |
37 |
Overview and Perspectives of Air Mobility Operations and Simulation Tools
|
Safadi, Yazan |
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58 |
10 |
p. 296-301 |
artikel |
38 |
Parallel distributed collision avoidance with intention consensus based on ADMM
|
Tran, Hoang Anh |
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58 |
10 |
p. 302-309 |
artikel |
39 |
Performance-Barrier-Based Event-Triggered Boundary Control of Congested ARZ Traffic PDEs ⁎ ⁎ This is a conference version of the manuscript currently under review in the IEEE Transactions on Automatic Control, titled “Performance-Barrier Event-Triggered PDE Control of Traffic Flow”. The work of M. Diagne was funded by the NSF CAREER Award CMMI-2302030 and the NSF grant CMMI-2222250. The work of M. Krstic was funded by the NSF grant ECCS-2151525 and the AFOSR grant FA9550-23-1-0535.
|
Zhang, Peihan |
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58 |
10 |
p. 182-187 |
artikel |
40 |
Performance Evaluation of Reinforcement Learning-Based Adaptive Signal Control Deployment in Urban Network
|
Allison, Jake |
|
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58 |
10 |
p. 120-125 |
artikel |
41 |
REAL-TIME TELEOPERATION CONTROL SYSTEM FOR AUTONOMOUS VEHICLE
|
Ding, Ning |
|
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58 |
10 |
p. 168-175 |
artikel |
42 |
Reducing Emission Peaks in a Port Terminal through Optimized Truck Arrivals
|
Hoxha, Rexhina |
|
|
58 |
10 |
p. 321-326 |
artikel |
43 |
Robust Reinforcement Learning-based Vehicle Control with Object Avoidance
|
Lelkó, Attila |
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58 |
10 |
p. 134-139 |
artikel |
44 |
Safety in e-Scooters: a Machine-Learning Approach for Online Second Passenger Detection
|
Leoni, Jessica |
|
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58 |
10 |
p. 14-21 |
artikel |
45 |
Signal Detection Method Based on Social Relationship Strength in Vehicular Ad-hoc Networks ⁎ ⁎ This work was financially supported by the Open Fund Project of Key Laboratory of Ocean Observation Technology, MNR (No. 2023klootA01). (Corresponding author: Shuangshuang Han)
|
Li, Yi |
|
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58 |
10 |
p. 176-181 |
artikel |
46 |
Smart Urban Systems Planning for Active Mobility and Sustainability
|
Papageorgiou, George |
|
|
58 |
10 |
p. 261-266 |
artikel |
47 |
Spatial Decision Support Systems for Study Critical Freight Corridors
|
Machado, A. |
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58 |
10 |
p. 81-86 |
artikel |
48 |
Statistical Analysis and Modelling of Pedestrian Behaviour at Railway Platform
|
Singh, Rahul Kumar |
|
|
58 |
10 |
p. 285-289 |
artikel |
49 |
Supervised reinforcement learning based trajectory tracking control for autonomous vehicles ⁎ ⁎ The research was supported by the European Union within the framework of the National Laboratory for Autonomous Systems (RRF-2.3.1-21-2022- 00002). The research was also supported by the National Research, Development and Innovation Office through the project ”Cooperative emergency trajectory design for connected autonomous vehicles” (NKFIH: 2019-2.1.12-TÉT VN).
|
Mihály, András |
|
|
58 |
10 |
p. 140-145 |
artikel |
50 |
The Mixed Fleet Hybrid Truck Platoon Network Design Problem
|
Ioannou, I.P. |
|
|
58 |
10 |
p. 69-74 |
artikel |
51 |
Towards Safer Highway Work Zones: Insights from Deep Learning Analysis of Thermal Footage
|
Bhuyan, Zubin |
|
|
58 |
10 |
p. 188-193 |
artikel |
52 |
Trajectory Tracking for Autonomous Vehicles Using Robust Model Predictive Control
|
Shen, Dan |
|
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58 |
10 |
p. 94-101 |
artikel |
53 |
Urban Arterial Traffic Volume and Travel Time Estimation with Use of Data Driven Models
|
Konstantinidis, Chris |
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|
58 |
10 |
p. 102-107 |
artikel |