Autonomous driving paper index
Exploring Ride-Sourcing Usage Among Older Adults: A Case Study of DKI Jakarta
One-line summary
Mobility is a critical determinant of the quality of life for older adults, particularly in urban areas where limited physical capacity and economic constraints reduce their accessibility to transportation.
Engineering notes
Key topics: autonomous driving, perception. See the paper for implementation details and experimental results.
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
Mobility is a critical determinant of the quality of life for older adults, particularly in urban areas where limited physical capacity and economic constraints reduce their accessibility to transportation. Ride-sourcing services offer more flexible and independent mobility options; however, their adoption among older adults remains limited due to technological barriers and concerns regarding safety and security aspects. This study explored ride-sourcing usage among older adults in DKI Jakarta and identified the factors influencing their adoption. A quantitative approach was employed using revealed preference survey data collected from 408 older adult respondents. The dataset covered socioeconomic characteristics, health condition, technology response, safety and security perceptions. Descriptive statistics, factor analysis (principal component analysis), and discrete choice modeling (multinomial logit and nested logit) were conducted to analyze user preferences and identify significant factors. The findings indicate that while most older adults have positive perceptions on smartphones, many still require assistance in booking ride-sourcing services, and the majority are classified as inactive users. The nested logit model reveals a potential behavioral transition from assisted booking to independent usage. PCA reduced 28 perception indicators into six factors: driver safety and behavior, trip support, driver characteristics, technological barriers, travel risk, and personal security risk. Discrete choice models identified age, gender, employment status, vehicle ownership, presence of young dependents, physical condition, and user perceptions as significant predictors of ride-sourcing usage.
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