Forecasting the evolution of urban mobility: the influence of anthropomorphism and social responsiveness in the transition from human to automated driving
The transition to automated driving has prompted efforts to anthropomorphize urban transportation, aiming to replicate traditional driver-pedestrian interactions and enhance safety when human drivers are absent. However, prior research on anthropomorphism has shown inconsistency, potentially hinderi...
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Main Authors: | , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2025
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/182384 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | The transition to automated driving has prompted efforts to anthropomorphize urban transportation, aiming to replicate traditional driver-pedestrian interactions and enhance safety when human drivers are absent. However, prior research on anthropomorphism has shown inconsistency, potentially hindering its practical implementation in pedestrian-vehicle interactions. This study addressed these inconsistencies by examining the contingent role of social responsiveness. Using a 2 × 2 between-subjects experimental design, this study investigated the crossover interaction effects of anthropomorphism and social responsiveness on pedestrian-vehicle interactions at urban crossings. Two sequential studies were conducted: Study 1 examined the crossover interaction effects on cognitive factors and behavioral consequences (responsibility attribution and behavioral intention). Study 2 delved into the underlying mechanisms and contingencies of these interactions. Results reveal: (1) combining anthropomorphism and social responsiveness is crucial for effective pedestrian crossing and communication in the absence of human drivers; (2) the positive effects of this combination on responsibility attribution and behavioral intention are mediated by cognitive factors; and (3) non-responsive humanoid vehicles may not measure up to non-responsive, non-humanoid vehicles, yet responsive humanoid vehicles can outperform responsive, non-humanoid vehicles. These findings support the theory and guide the development of secure, interactive designs for the next generation of urban mobility in the transition to automated driving. |
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