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The Empirical Pareto Frontier of Automated Driving: Consensus Across Safety, Interaction, and Traffic

https://doi.org/10.2139/ssrn.5601917
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.aap.2017.04.012openalex-snapshot
Can vehicle longitudinal jerk be used to identify aggressive drivers? An examination using naturalistic driving data
inferredcites →https://doi.org/10.1016/j.commtr.2021.100019openalex-snapshot
Pro-social control of connected automated vehicles in mixed-autonomy multi-lane highway traffic
inferredcites →https://doi.org/10.1016/j.trc.2024.104969openalex-snapshot
Human-automated vehicle interactions: Voluntary driver intervention in car-following
inferredcites →https://doi.org/10.1016/j.trf.2023.10.006openalex-snapshot
A comparison of pedestrian behavior in interactions with autonomous and human-driven vehicles: An extreme value theory approach
inferredcites →https://doi.org/10.1108/febe-05-2021-0025openalex-snapshot
Tradeoffs between safe/comfortable headways versus mobility-enhancing headways in an automated driving environment: preliminary insights using a driving simulator experiment
inferredcites →https://doi.org/10.1109/access.2020.2987959openalex-snapshot
A Modified Post Encroachment Time Model of Urban Road Merging Area Based on Lane-Change Characteristics
inferredcites →https://doi.org/10.1109/ccta49430.2022.9966123openalex-snapshot
Comfort-Aware Trajectory Planning in Autonomous Driving via Multi-Objective Nonlinear Model Predictive Control
inferredcites →https://doi.org/10.1109/jas.2023.123378openalex-snapshot
Towards Energy-Efficient Autonomous Driving: A Multi-Objective Reinforcement Learning Approach
inferredcites →https://doi.org/10.1109/lra.2024.3440834openalex-snapshot
Modifying Adaptive Cruise Control Systems for String Stable Stop-and -Go Wave Control
inferredcites →https://doi.org/10.1109/mcs.2024.3498552openalex-snapshot
Traffic Control via Connected and Automated Vehicles (CAVs): An Open-Road Field Experiment with 100 CAVs
inferredcites →https://doi.org/10.1109/ojits.2022.3155126openalex-snapshot
Real-Time Pedestrian Conflict Prediction Model at the Signal Cycle Level Using Machine Learning Models
inferredcites →https://doi.org/10.1109/tits.2021.3056122openalex-snapshot
Eco-Platooning for Cooperative Automated Vehicles Under Mixed Traffic Flow
inferredcites →https://doi.org/10.1109/tits.2022.3211272openalex-snapshot
A Convex Optimal Control Framework for Autonomous Vehicle Intersection Crossing
inferredcites →https://doi.org/10.1109/tte.2024.3400461openalex-snapshot
Ecological Electric Vehicle Platooning: An Adaptive Tube-Based Distributed Model Predictive Control Approach
inferredcites →https://doi.org/10.1111/mice.12787openalex-snapshot
Ride comfort assessment for automated vehicles utilizing a road surface model and Monte Carlo simulations
inferredcites →https://doi.org/10.1155/2024/3835831openalex-snapshot
Investigating the Impact of Automated Vehicles on the Safety and Operation of Low‐Speed Urban Networks
inferredcites →https://doi.org/10.55329/pjax7195openalex-snapshot
Bridging the gap: understanding the factors affecting pedestrian safety perceptions in the age of driverless vehicles

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1109/iv66570.2026.11624067openalex-snapshot
Learning the Pareto Space of Multi-Objective Autonomous Driving: A Modular, Data-Driven Approach
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