Do E-Scooter Speed Governance Policies Reduce Harsh Acceleration and Deceleration? Evidence from 19.5 Million Trips Around a Regulatory Ban
Seongjin Choi, Sunbin Yoo, Sugie Lee

TL;DR
This study examines whether e-scooter speed governance policies reduce harsh acceleration and deceleration events, finding evidence that such policies lead to measurable safety improvements through mechanical constraints.
Contribution
It provides causal evidence that firmware-based speed limits decrease harsh riding behaviors beyond mechanical effects, using a large-scale GPS trip dataset and a difference-in-differences approach.
Findings
Speed governance policies significantly reduce harsh acceleration events.
Speed governance policies significantly reduce harsh deceleration events.
The reduction is driven by mechanical constraints, not behavioral offsetting.
Abstract
Do e-scooter speed governance policies yield behavioral safety gains beyond the mechanical cap they impose? A firmware ceiling mechanically prevents speeding, but whether the same riders also generate fewer harsh accelerations and harsh decelerations when the ungoverned mode is withdrawn remains open. We analyze 19.5 million GPS-instrumented trips from 52 South Korean cities (February to November 2023). Our two-stage predict-then-validate design targets two trip-level binary outcomes, any harsh-acceleration event and any harsh-deceleration event. In Phase~I, we predict each outcome's within-user reduction under an ungoverned-to-governed substitution, using a rider-heterogeneous random-parameters binary logit on the pre-ban period. In Phase~II, we validate these predictions using a difference-in-differences specification that exploits the operator's system-wide December~2023 removal of…
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