Autonomous driving paper index
Active Mobility Accessibility Index – Assessing Local Transport Competitiveness
One-line summary
An autonomous driving research paper: Active Mobility Accessibility Index – Assessing Local Transport Competitiveness.
Engineering notes
Key topics: autonomous driving, planning, control. 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
Abstract. Active Mobility Accessibility Index (AMAI) quantifies the competitiveness of walking and cycling relative to driving using travel-time and distance ratios on identical sampled origin-destination pairs, reflecting network structure rather than destination choice. AMAI combines time parity and distance parity in a simple diagnostic score, using equal weights as a default specification for interpretation and policy use. Applied across the five Tyne and Wear local authorities, it demonstrates that cycling is more competitive than walking against driving. The median origin-level cycling AMAI is 0.820 and the median walking AMAI is 0.645. Parity remains limited where the share of origins at or above parity is 10.0% for cycling and 1.7% for walking. Initial API-based tests suggested that time-of-day effects are limited for the short local trips studied here, supporting development of a scalable in-house routing workflow for the main analysis. Validation against OA-level Census 2021 mode shares, with controls for terrain gradient and commute-distance composition, suggests that AMAI captures a relevant behavioural signal, while its main value lies in diagnosing local network competitiveness for policy and planning.
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