Autonomous driving paper index
When Fairness Backfires: A Chronoceptive Design Approach to Intelligent Transportation Systems
One-line summary
We introduce a chronoceptive design framework that integrates insights from cognitive psychology into traffic-control design.
Engineering notes
The results show that chronoceptive signal designs significantly improve user acceptance (by up to 12%) and reduce perceived waiting times, despite identical or slightly longer objective travel times. The source code and survey data can be found open-source on GitHub.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
Intelligent transportation systems (ITSs) and traffic control promise substantial efficiency and safety improvements but frequently face public resistance and driver compliance issues. Many drivers perceive such control measures as unfair or unnecessary, despite measurable system-wide benefits. This study investigates how chronoception—the subjective perception of time—affects user acceptance of ITS control strategies and how signal design can be adapted to reduce perceived delays. We introduce a chronoceptive design framework that integrates insights from cognitive psychology into traffic-control design. Using ramp metering as a case study, we conduct virtual experience stated preference experiments with 101 participants, comparing standard and chronoceptive ramp metering designs featuring shorter signal cycles, three-phase lights, and countdown timers. The results show that chronoceptive signal designs significantly improve user acceptance (by up to 12%) and reduce perceived waiting times, despite identical or slightly longer objective travel times. These findings reveal a systematic bias between factual and perceived benefits and highlight the potential of chronoceptive design to enhance compliance and fairness perception. This study contributes a new human-centred design paradigm for traffic control that aligns objective performance with user perception and outlines how chronoception and perceived fairness can be operationalised in traffic control. The source code and survey data can be found open-source on GitHub.
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