Historical manifest data from a parcel carrier undertaking 'next-day' (i.e. non-express) deliveries in an area of central London (mainly EC2 postcode district) were used to quantify the potential benefits of switching from the current van-based deliveries to one where porters or cycle couriers are used for the last-mile delivery, working from set drop-off points.The results suggested that over the business-as-usual case for the area of London studied, the carrier could reduce CO2 emissions by 45% (9500kg/year) and NOx emissions by 33% (7.64kg/year). Annual driving distance could be reduced by 78% (48,100km) and the amount of time spent stationary at the curbside by 45% (2558 hours/year). Scaling up the modelled emissions savings to London's Central Activities Zone, an area approximately 10 times bigger than the modelled case study area and with estimated total annual parcel delivery distance of 15 million km, could see annual emissions savings in the region of 2 million kgCO2 and 1633kgNOx if all carriers utilised porters or cycle couriers. Overall cost savings to the carrier were estimated to be in the range 34%-39%. Some practical operating challenges are identified including sorting and packing of items, parcel handover arrangements, how to deal with failed deliveries, and how to incorporate express items.
e scale of parcel delivery is increasing rapidly, with indications that it will continue to do so. is presents a challenge both to those in the industry who wish to understand how they might adapt and change their ways of doing delivery and the policymakers who would like to encourage this in order to positively impact urban areas in terms of tra c and pollution. We present an early implementation of an agent-based modelling framework of parcel delivery processes, exible enough to be extended to explore a variety of scenarios. We apply it to a baseline case study to begin the process of exploring the e ectiveness of switching to a di erent method of delivery. CCS CONCEPTS •Computing methodologies → Modeling methodologies; •Applied computing → Transportation; Command and control;
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