mlsanityData to 7 Oct 2026

Self-Driving like a Human driver instead of a Robocar: Personalized comfortable driving experience for autonomous vehicles

arXiv 2001.03908 ↗First posted 12 Jan 2020eess.SY cs.RO cs.SYcited by 20

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Abstract (arXiv)

This paper issues an integrated control system of self-driving autonomous vehicles based on the personal driving preference to provide personalized comfortable driving experience to autonomous vehicle users. We propose an Occupant's Preference Metric (OPM) which is defining a preferred lateral and longitudinal acceleration region with maximum allowable jerk for users. Moreover, we propose a vehicle controller based on control parameters enabling integrated lateral and longitudinal control via preference-aware maneuvering of autonomous vehicles. The proposed system not only provides the criteria for the occupant's driving preference, but also provides a personalized autonomous self-driving style like a human driver instead of a Robocar. The simulation and experimental results demonstrated that the proposed system can maneuver the self-driving vehicle like a human driver by tracking the specified criterion of admissible acceleration and jerk.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Jan 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 4; 2023: 3; 2024: 5; 2025: 5; 2026: 1.

20 papers.

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  1. 2024AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Drivingcited by 35
  2. 2024LimSim++: A Closed-Loop Platform for Deploying Multimodal LLMs in Autonomous Drivingcited by 32
  3. 2024On-Board Vision-Language Models for Personalized Autonomous Vehicle Motion Control: System Design and Real-World Validationcited by 15
  4. 2022Meta-Learning with Less Forgetting on Large-Scale Non-Stationary Task Distributionscited by 14
  5. 2025V2X-UniPool: Unifying Multimodal Perception and Knowledge Reasoning for Autonomous Drivingcited by 14
  6. 2022Driver Digital Twin for Online Prediction of Personalized Lane Change Behaviorcited by 13
  7. 2021Meta Learning on a Sequence of Imbalanced Domains with Difficulty Awarenesscited by 8
  8. 2023CRITERIA: a New Benchmarking Paradigm for Evaluating Trajectory Prediction Models for Autonomous Drivingcited by 8
  9. 2022An Empirical Bayes Analysis of Object Trajectory Representation Modelscited by 5
  10. 2023Kinematics-aware Trajectory Generation and Prediction with Latent Stochastic Differential Modelingcited by 5
  11. 2021Pedestrian Emergence Estimation and Occlusion-Aware Risk Assessment for Urban Autonomous Drivingcited by 3
  12. 2023DeepQTest: Testing Autonomous Driving Systems with Reinforcement Learning and Real-world Weather Datacited by 3
8 more
  1. 2025Getting SMARTER for Motion Planning in Autonomous Driving Systemscited by 3
  2. 2025Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Drivingcited by 3
  3. 2022Rationale-aware Autonomous Driving Policy utilizing Safety Force Field implemented on CARLA Simulatorcited by 1
  4. 2024Situation Awareness for Driver-Centric Driving Style Adaptationcited by 1
  5. 2025Latent Embedding Adaptation for Human Preference Alignment in Diffusion Plannerscited by 1
  6. 2025EP-Diffuser: An Efficient Diffusion Model for Traffic Scene Generation and Prediction via Polynomial Representationscited by 1
  7. 2024Maneuver Decision-Making with Trajectory Streams Prediction for Autonomous Vehiclescited by 0
  8. 2026Comfort by Construction: Adaptive, Comfort-Bounded Action Spaces for Learned Driving Policiescited by 0