Growth in e-commerce has led to increasing use of light goods vehicles for parcel deliveries in urban areas. This paper provides an insight into the reasons behind this growth and the resulting effort required to meet the exacting delivery services offered by e-retailers which often lead to poor vehicle utilisation in the last-mile operation, as well as the duplication of delivery services in urban centres as competitors vie for business. A case study investigating current parcel delivery operations in central London identified the scale of the challenge facing the last-mile parcel delivery driver, highlighting the importance of walking which can account for 62% of the total vehicle round time and 40% of the total round distance in the operations studied. The characteristics of these operations are in direct conflict with the urban infrastructure which is being increasingly redesigned in favour of walking, cycling and public transport, reducing the kerbside accessibility for last-mile operations. The paper highlights other pressures on last-mile operators associated with managing seasonal peaks in demand; reduced lead times between customers placing orders and deliveries being made; meeting delivery time windows; firsttime delivery failure rates and the need to manage high levels of product returns. It concludes by describing a range of initiatives that retailers and parcel carriers, sometimes in conjunction with city authorities, can implement to reduce the costs associated with last-mile delivery, without negatively impacting on customer service levels.
44Word count: Abstract (176), Text (5314), References (997) 45 Number of figures: 2 = 500 words 46 Number of tables: 2 = 500 words 47 Total = 7487 words 48 49 ABSTRACT 1The UK parcel sector generated almost £9 billion in revenue in 2015, with growth expected to 2 increase by 15.6% to 2019 and is characterised by many independent players competing in an 3'everyone-delivers-everywhere' culture leading to much replication of vehicle activity. With road 4 space in urban centres being increasingly reallocated to pavement widening, bus and cycle lanes, there 5is growing interest in alternative solutions to the last-mile delivery problem. We make three 6 contributions in this paper: firstly, through empirical analysis using carrier operational datasets, we 7 quantify the characteristics of last-mile parcel operations and demonstrate the reliance placed on 8walking by vehicle drivers with their vans being parked at the curbside for, on average 60% of the 9 total vehicle round time; secondly we introduce the concept of 'portering' where vans rendezvous 10 with porters who operate within specific geographical 'patches' to service consignees on-foot, 11potentially saving 86% in driving distance on some rounds and 69% in time; finally, we highlight the 12 wider practical issues and optimisation challenges associated with operating driving and portering 13 rounds in inner urban areas. 14 15
The analysis of social media content for the extraction of geospatial information and event-related knowledge has recently received substantial attention. In this article we present an approach that leverages the complementary nature of social multimedia content by utilizing heterogeneous sources of social media feeds to assess the impact area of a natural disaster. More specifically, we introduce a novel social multimedia triangulation process that uses both Twitter and Flickr content in an integrated two-step process: Twitter content is used to identify toponym references associated with a disaster; this information is then used to provide approximate orientation for the associated Flickr imagery, allowing us to delineate the impact area as the overlap of multiple view footprints. In this approach, we practically crowdsource approximate orientations from Twitter content and use this information to orient Flickr imagery accordingly and identify the impact area through viewshed analysis and viewpoint integration. This approach enables us to avoid computationally intensive image analysis tasks associated with traditional image orientation, while allowing us to triangulate numerous images by having them pointed towards the crowdsourced toponym location. The article presents our approach and demonstrates its performance using a real-world wildfire event as a representative application case study.With the general public nowadays having at its fingertips technology that a few years ago was available only to advanced computing laboratories, it is only natural that the amount of crowdsourced information of computational merit is rapidly growing, with volunteered geographical information (VGI) being a large portion of this content (Goodchild 2007). Both domain experts and amateurs alike can now generate and disseminate geospatial content 2 G Panteras, S Wise, X Lu, A Croitoru, A Crooks and A Stefanidis
Pedestrian movement is woven into the fabric of urban regions. With more people living in cities than ever before, there is an increased need to understand and model how pedestrians utilize and move through space for a variety of applications, ranging from urban planning and architecture to security. Pedestrian modeling has been traditionally faced with the challenge of collecting data to calibrate and validate such models of pedestrian movement. With the increased availability of mobility datasets from video surveillance and enhanced geolocation capabilities in consumer mobile devices we are now presented with the opportunity to change the way we build pedestrian models. Within this paper we explore the potential that such information offers for the improvement of agent-based pedestrian models. We introduce a Scene-and Activity-Aware Agent-Based Model (SA 2 -ABM), a method for harvesting scene activity information in the form of spatiotemporal trajectories, and incorporate this information into our models. In order to assess and evaluate the improvement offered by such information, we carry out a range of experiments using
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