OOIR: Observatory of International Research

Papers

(The H4-Index of Transportation Research Part C-Emerging Technologies is 61. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-03-01 to 2024-03-01.)

Article	Citations
Drone-aided routing: A literature review	221
Stacked bidirectional and unidirectional LSTM recurrent neural network for forecasting network-wide traffic state with missing values	203
Automated vehicle acceptance in China: Social influence and initial trust are key determinants	193
A graph CNN-LSTM neural network for short and long-term traffic forecasting based on trajectory data	192
Safe, efficient, and comfortable velocity control based on reinforcement learning for autonomous driving	172
Forecasting road traffic speeds by considering area-wide spatio-temporal dependencies based on a graph convolutional neural network (GCN)	129
Urban air mobility: A comprehensive review and comparative analysis with autonomous and electric ground transportation for informing future research	126
Trajectory data-based traffic flow studies: A revisit	126
Joint optimization of customer location clustering and drone-based routing for last-mile deliveries	116
An ensemble deep learning approach for driver lane change intention inference	114
Truck-drone team logistics: A heuristic approach to multi-drop route planning	113
Risk assessment based collision avoidance decision-making for autonomous vehicles in multi-scenarios	113
Analyzing the impact of automated vehicles on uncertainty and stability of the mixed traffic flow	110
A survey on autonomous vehicle control in the era of mixed-autonomy: From physics-based to AI-guided driving policy learning	107
A big-data driven approach to analyzing and modeling human mobility trend under non-pharmaceutical interventions during COVID-19 pandemic	106
Mobility-on-demand: An empirical study of internet-based ride-hailing adoption factors, travel characteristics and mode substitution effects	104
OpenACC. An open database of car-following experiments to study the properties of commercial ACC systems	99
Yard crane and AGV scheduling in automated container terminal: A multi-robot task allocation framework	96
An automated driving systems data acquisition and analytics platform	95
Explaining shared micromobility usage, competition and mode choice by modelling empirical data from Zurich, Switzerland	95
Decision making of autonomous vehicles in lane change scenarios: Deep reinforcement learning approaches with risk awareness	95
Passenger comfort and trust on first-time use of a shared autonomous shuttle vehicle	93
Mitigate the range anxiety: Siting battery charging stations for electric vehicle drivers	92
An analytical optimal control approach for virtually coupled high-speed trains with local and string stability	92
Mixed platoon control of automated and human-driven vehicles at a signalized intersection: Dynamical analysis and optimal control	92

Real-time crash prediction on expressways using deep generative models	91
GE-GAN: A novel deep learning framework for road traffic state estimation	88
A nonconvex low-rank tensor completion model for spatiotemporal traffic data imputation	84
Automated vehicle-involved traffic flow studies: A survey of assumptions, models, speculations, and perspectives	83
Predicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional network	83
Multi-vehicle routing problems with soft time windows: A multi-agent reinforcement learning approach	82
Cooperative merging control via trajectory optimization in mixed vehicular traffic	82
Battery-electric transit vehicle scheduling with optimal number of stationary chargers	81
A review of bicycle-sharing service planning problems	80
Joint optimization of vehicle-group trajectory and signal timing: Introducing the white phase for mixed-autonomy traffic stream	78
A variational autoencoder solution for road traffic forecasting systems: Missing data imputation, dimension reduction, model selection and anomaly detection	76
Macroscopic modeling and dynamic control of on-street cruising-for-parking of autonomous vehicles in a multi-region urban road network	75
Analytical analysis of the effect of maximum platoon size of connected and automated vehicles	73
Examining the effects of emotional valence and arousal on takeover performance in conditionally automated driving	72
Large-scale pavement roughness measurements with vehicle crowdsourced data using semi-supervised learning	72
Field experiments on longitudinal characteristics of human driver behavior following an autonomous vehicle	72
On the inefficiency of ride-sourcing services towards urban congestion	71
Classifying travelers' driving style using basic safety messages generated by connected vehicles: Application of unsupervised machine learning	71
Graph Markov network for traffic forecasting with missing data	70
Behavioural intention to use autonomous vehicles: Systematic review and empirical extension	70
Urban ride-hailing demand prediction with multiple spatio-temporal information fusion network	70
Multi-community passenger demand prediction at region level based on spatio-temporal graph convolutional network	68
Modeling and analyzing cyberattack effects on connected automated vehicular platoons	68
Automated taxis’ dial-a-ride problem with ride-sharing considering congestion-based dynamic travel times	67
A data driven typology of electric vehicle user types and charging sessions	67
The multiple flying sidekicks traveling salesman problem with variable drone speeds	67
Optimizing bike sharing systems from the life cycle greenhouse gas emissions perspective	67
Learning traffic as a graph: A gated graph wavelet recurrent neural network for network-scale traffic prediction	66
A residual spatio-temporal architecture for travel demand forecasting	64
Cooperative adaptive cruise control for connected autonomous vehicles by factoring communication-related constraints	64
Modeling the fundamental diagram of mixed human-driven and connected automated vehicles	64
Joint optimization of scheduling and capacity for mixed traffic with autonomous and human-driven buses: A dynamic programming approach	63
Charging station location problem: A comprehensive review on models and solution approaches	63
Hybrid deep reinforcement learning based eco-driving for low-level connected and automated vehicles along signalized corridors	62
Dynamic holding control to avoid bus bunching: A multi-agent deep reinforcement learning framework	61
Consumer preferences for Mobility-as-a-Service (MaaS) in Australia	61