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Car dependence has been threatening transportation sustainability as itcontributes to congestion and associated externalities. In response, varioustransport policies that restrict the use of private vehicle have beenimplemented. However, empirical evaluations of such policies have been limited.To assess these policies' benefits and costs, it is imperative to accuratelyevaluate how such policies affect traffic conditions. In this study, we compilea refined spatio-temporal resolution data set of the floating-vehicle-basedtraffic performance index to examine the effects of a recent nonlocal vehicledriving restriction policy in Shanghai, one of most populous cities in theworld. Specifically, we explore whether and how the policy impacted trafficspeeds in the short term by employing a quasi-experimentaldifference-in-differences modeling approach. We find that: (1) In the firstmonth, the policy led to an increase of the network-level traffic speed by1.47% (0.352 km/h) during evening peak hours (17:00-19:00) but had nosignificant effects during morning peak hours (7:00-9:00). (2) The policy alsohelped improve the network-level traffic speed in some unrestricted hours(6:00, 12:00, 14:00, and 20:00) although the impact was marginal. (3) Theshort-term effects of the policy exhibited heterogeneity across trafficanalysis zones. The lower the metro station density, the greater the effectswere. We conclude that driving restrictions for non-local vehicles alone maynot significantly reduce congestion, and their effects can differ bothtemporally and spatially. However, they can have potential side effects such asincreased purchase and usage of new energy vehicles, owners of which can obtaina local license plate of Shanghai for free.

Panacea or Placebo? Exploring Causal Effects of Nonlocal Vehicle Driving  Restriction Policies on Traffic Congestion Using Difference-in-differences  Approach