Insights into the effect of traffic congestion on distribution network characteristics – a numerical analysis based on navigation service data

Abstract

This research studies effects that the average increase in travel times due to road traffic congestion has on characteristics of an existing distribution network. It presents the most detailed estimate of ‘on-the-road’ effects on distribution network characteristics up to now, from the network modelling perspective and from the processed data point of view. A concrete network model allowing for the representation of all relevant transportation flows is presented. The processed traffic information relies on navigation service data. The use of such data allows the requirements that arise for the traffic analysis of a whole distribution network to be met. It is shown that this data source may considerably contribute in forthcoming research. The effects of traffic congestion are quantified to get insights into the extent to which regular traffic congestion affects distribution network characteristics and to understand the mitigating effect when the number of distribution centres is increased.

Keywords:

• distribution network
• road freight transportation
• traffic congestion
• road traffic
• navigation service data

Notes

1. Navigation and traffic information providers are, for instance, Bing Maps, Google Maps, INRIX, HERE, and TomTom.

2. Leduc (2008) gives an overview of these techniques. Treiber and Kesting (2013) give an overview of traffic data collection and aggregation methods.

3. See the terms of use of the different providers.

4. Deardoff, Wiesner, and Fazio (2011) and TRB (2010) define ‘free-flow speed’ as the speed of drivers travelling as desired given prevailing conditions (lane width, weather, sight distance, behaviour, adjacent environment, … ) such that no preceding vehicle influences the drivers’ speeds.

5. Miebach (2012) reports results from a recent survey among logistics managers of German FMCG manufacturers and retailers that indicate that in the German FMCG industry, more than 90% of transportation and about 50% of storage/picking operations have been outsourced. Reasons for logistics outsourcing in the FMCG industry are numerous, ranging from the possibility to improve shipment density/load utilisation (economies of scale, cost reduction) to the reduction of opportunity costs (focus on core competences) (Bretzke 1989; Langley and Capgemini 2010). The notably high share of logistics outsourcing in the FMCG industry may be explained with the relatively high share of transportation costs in overall logistics costs and the relatively high share of the logistics costs in total costs (Miebach 2012).

6. To know the exact routes, each one of the more than 20 logistics service providers must deliver the exact routing of the delivery tours by which the focal company's shipments are delivered.

7. In the case studied, no situation occurred where a round trip had a time limit constraint with fewer than 2.5 customers in a delivery trip. This may be explained by the dense network of transshipment points and the geographical density of the customer destinations. This finding is in line with preceding research: Figliozzi (2007) reports three real-world cases where the average number of tour stops is between 5 and 6.

8. This rough estimate clearly ignores some aspects that are relevant for GHG generation, such as stop-and-go situations. Figliozzi (2011) presents a case study that explicitly focuses on this topic.