Analysis reveals differing acceptance levels of road-sharing for elderly pedestrians based on digital capability in Wuhan, indicating a crucial role of technology in urban mobility aspirations.
While autonomous vehicles (AVs) are increasingly integrated into urban mobility, little is known about how digital capability shapes elderly pedestrians’ willingness to share roads with these technologies. This is especially true in the absence of explicit vehicle–pedestrian communication mechanisms. To address this gap, we combine the Theory of Planned Behavior (TPB) with the Pedestrian Behavior Questionnaire (PBQ) and segment elderly pedestrians using Latent Class Analysis (LCA). A sample of 750 older adults in Wuhan, China, was divided into two latent groups: digitally disengaged (70.8%) and digitally engaged (29.2%). Classification was based on four indicators: smart device usage, online social interaction, online entertainment, and online economic behavior. We then applied ordered logit models to estimate group-specific determinants of AV road-sharing acceptance. Results reveal clear heterogeneity across digital capability levels. For digitally disengaged seniors, positive pedestrian behaviors significantly increased willingness (β = 0.316, p = 0.001). Prior accident experience reduced willingness (0 accident: β = 0.435, p = 0.021; 1–2 accidents: β = −0.518, p = 0.012). For digitally engaged seniors, perceived behavioral control showed a marginally positive effect (β = 0.353, p = 0.066). Errors had a significant positive effect (β = 0.540, p = 0.009). Positive behaviors had a significant negative effect (β = −0.414, p = 0.007). These patterns indicate that digital capability not only modulates the strength of TPB pathways but also reshapes behavior–intention linkages captured by PBQ dimensions. Methodologically, the study contributes an integrated TPB–PBQ–LCA–OLM framework. This framework identifies digital capability as a critical moderator of AV acceptance among elderly pedestrians. Practically, the findings suggest differentiated strategies. For digitally disengaged users, interventions should build digital literacy and reinforce safe walking norms. For digitally engaged users, strategies should prioritize transparent AV intent signaling and features that enhance perceived control.
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Liu et al. (2025) studied this question.
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