4.7 Article

Improving mobility by optimizing the number, location and usage of loading/unloading bays for urban freight vehicles

Journal

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trd.2017.05.014

Keywords

City logistics; Congestion; Double-parking; Parking optimization; Parking simulation

Funding

  1. MIT Portugal Program
  2. Fundacao para a Ciencia e Tecnologia (FCT) [SFRH/BD/51575/2011]
  3. European Commission

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The role of urban freight vehicle trips in fulfilling the consumption needs of people in urban areas is often overshadowed by externality-causing parking practices (e.g., double-parking associated with traffic delays). Loading/unloading bays are generally viewed as an effective way to avoid freight vehicles double-parking, but are often misused by non-freight vehicles. We assess the potential of reducing freight vehicles double-parking mobility impacts by changing: (a) the spatial configuration (number, location, size) of loading/unloading bays and, (b) the non-freight vehicles parking rules compliance levels. Parking demand models were created with data from an establishment-based freight survey and a parking observation exercise. Two case studies were defined for 1 km(2) zones in the city of Lisbon, Portugal. Alternative bay systems were derived from an iterative implementation of the maximize capacitated coverage algorithm to a range of bays to be located. Parking operations in current and alternative bay systems were compared using a microsimulation. Bay systems' ability in reducing double-parking impacts was assessed via a set of indicators (e.g., average speed). Freight traffic causes a disproportionate amount of externalities and the current bay configuration leads to greater mobility impacts than some of the proposed systems. Enforcement was a crucial element in reducing parking operations impact on traffic flow in one of the case-studies. Road network characteristics were demonstrated to play a role in the adequate strategy of arranging the spatial configuration of bays. (C) 2017 Elsevier Ltd. All rights reserved.

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