01588176

Component

The role of urban freight in fulfilling society’s consumption needs is often overshadowed by externality-causing parking practices (e.g., double parking associated with traffic delays). Loading/unloading bays are in general viewed as an effective way to avoid double/in-lane parking of freight vehicles but enforcement of usage is crucial to assure availability. With this work the authors aim at assessing the potential of improving mobility and reducing environmental impacts of urban logistics through the spatial configuration (number, location, size) and correct usage enforcement of bays. Freight parking demand models were created from an establishment-based freight survey and a parking observation exercise. A case study (with one square kilometre) was defined in the city of Lisbon, Portugal, predominantly based on the output of land-use analyses. The authors assessed candidate locations for new bays and developed a variable to weight store demand. Optimal locations for a fixed total number of bays were explored using an iterative implementation of the “maximize capacitated coverage” algorithm. Alternative bay systems were selected to be compared with the current configuration. Freight parking operations were explored using a microsimulation framework that allows comparing bay systems performance with a set of indicators (e.g., average delay, total fuel consumption). Enforcement for non-freight vehicles parking in bays was represented by reductions in demand. The results show that freight traffic causes a disproportionate amount of externalities and the current bay configuration is clearly worse than the proposed solutions. Non-freight vehicles parking in bays might have a greater impact when occurring in specific locations rather than due to changes in total demand.

This paper was sponsored by TRB committee AT025 Standing Committee on Urban Freight Transportation. Alternate title: Decreasing Congestion by Optimizing Number, Location, and Usage of Loading and Unloading Bays for Urban Freight.

01584066

16-0784

English

17p

2016

Transportation Research Board 95th Annual Meeting

Digital/other

Figures; References; Tables

Algorithms; Case studies; Freight traffic; Loading and unloading; Loading facilities; Location; Microsimulation; Optimization; Parking demand; Traffic congestion; Traffic law enforcement; Urban areas

Lisbon (Portugal)

Freight Transportation; Highways; Planning and Forecasting; Terminals and Facilities; I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2016 Paper #16-0784

TRIS, TRB, ATRI

Jan 12 2016 4:28PM