A Time-Efficiency Study of Medium-Duty Trucks Delivering in Urban Environments

Abstract

This paper uses data from a major logistics service provider in Gothenburg (Sweden) to (i) identify the different activities in a typical urban distribution tour, (ii) quantify the time required by drivers to perform each of these activities, and (iii) identify potential initiatives to improve time efficiency. To do so, the authors collected GPS data, conducted a time-study of the activities performed by the drivers for a week, conducted a focus group with the drivers, and a set of interviews with managers. The results show that driving represents only 30% of the time, another 15% is spent on breaks, and the remaining 55% is used to perform activities related to customer service, freight handling, and planning. The latter are subdivided into multiple activities, each taking a small amount of time. A focus group with the drivers and some interviews revealed several initiatives to improve time efficiency. Most initiatives can bring small gains, but when aggregating all potential time savings there is a big potential to improve overall time efficiency. Initiatives with highest potential and low cost are: providing better pre-advice on upcoming customers, improving route planning, having hand-free cell phone use, and enhancing handling equipment.

Diffusion of blockchain in logistics and transportation industry: an analysis through the synthesis of academic and trade literature

“…For the information segment, the trend has been to adopt blockchain to make the information transparent and reduce the processing of paperwork. The trends in transportation grouping have been focused mainly on reducing the time and effort in delivering the goods (Sanchez-Diaz et al , 2020). This is done with the help of faster processing of approvals and custom clearances, thereby enabling the possibility of same-day delivery.…”

Electric vehicle charging strategies for Urban freight transport: concept and typology

“…Second, it is a fact that drivers make decisions onthe-fly in the absence of, and sometimes in spite of detailed route planning. While there is a low level of adoption of fleet management systems, especially among small fleet carriers (Perego, Perotti, & Mangiaracina, 2011;Rincon-Garcia, Waterson, & Cherrett, 2017), even large companies may not use them to develop detailed route planning, leaving it instead to their experienced drivers to decide, based on "their existing knowledge on where customers are located and their respective opening hours" (Sanchez-Diaz et al, 2020). This is in line with Orlikowski's model, which describes human action as influenced, but not dictated by "rules and norms" (Orlikowski, 2000), taken here to mean also designated route plans.…”

“…The activities that drivers do during operation time are driving, stationary work activity, or resting. Sanchez-Diaz et al (2020) find in a detailed time-study that driving and breaks take up only 30% and 15% of the time, respectively, while the remaining 55% is "used to perform activities not related to driving but to customer service and freight handling". This would mean that 70% of the time, the vehicle is parked or idle while being in the responsibility of the driver, which offers opportunity for being charged.…”

“…The second shortcoming is the implicit assumption that charging activity is always planned, which contradicts studies that have identified spontaneous decisions leading to refuelling and recharging behaviour of car drivers (Kitamura & Sperling, 1987;Philipsen, Brell, Brost, Eickels, & Ziefle, 2018). While UFT routes and schedules are to a large extent planned, drivers are also given the freedom to optimise their own routes and delivery based on their situation and tacit knowledge (Sanchez-Diaz, Palacios-Argüello, Levandi, Mardberg, & Basso, 2020). It is risky to only rely on pre-planned charging activities, when situations like congestion, forced detour or unexpected queues at customers could happen, and lead to insufficient battery capacity or range anxiety.…”

Route optimization for city cleaning vehicle

“…Another factor affecting the operating costs of a municipal cleaning company is the choice of an optimal route [24,25]. The choice of the route and the resulting travel costs depend on the urban development pattern [26,27]. Choosing a vehicle with low consumption of inexpensive fuel and an optimal route for the transport task of collecting municipal waste may result in the lowest possible operating costs of the vehicle fleet [28].…”