Using digitalisation for data-driven freight curbside management. A perspective from urban transport planning

Given trends in urbanisation, e-commerce, active mobility and modal shifts, streets have sprung up as scenes of conflict where competing demands for curbside space have increased. Because public space is limited, urban transport planners are called to solve public space conflicts by defining how much space is allocated to specific users as a means to achieve sustainable cities. In the allocation of curbside space, freight parking operations are sometimes overlooked compared to other curbside uses such as private vehicles parking. However, limited space for freight deliveries generates negative impacts on urban traffic (e.g. due to double parking), as well as on emissions and companies’ efficiency (e.g. due to the need to cruise for parking). This thesis aims to contribute to current understandings of the need for and uses of data to inform curbside management decision-making for freight parking from the perspective of urban transport planning. To that end, a case study was conducted to collect and analyse data about freight curbside operations using quantitative and qualitative methods, and a cross-sectional research design facilitated the exploration of the impacts of curbside interventions on cities’ sustainability worldwide

Enabling Factors and Durations Data Analytics for Dynamic Freight Parking Limits

Freight parking operations occur amid conflicting conditions of public space scarcity, competition with other users, and the inefficient management of loading zones (LZ) at cities’ curbside. The dynamic nature of freight operations, and the static LZ provision and regulation, accentuate these conflicting conditions at specific peak times. This generates supply–demand mismatches of parking infrastructure. These mismatches have motivated the development of Smart LZ that bring together technology, parking infrastructure, and data analytics to allocate space and define dynamic duration limits based on users’ needs. Although the dynamic duration limits unlock the possibility of a responsive LZ management, there is a narrow understanding of factors and analytical tools that support their definition. Therefore, the aim of this paper is twofold. Firstly, to identify factors for enabling dynamic parking durations policies. Secondly, to assess data analytics tools that estimate freight parking durations and LZ occupation levels based on operational and locational features. Semi-structured interviews and focus group analyses showed that public space use assessment, parking demand estimation, enforcement capabilities, and data sharing strategies are the most relevant factors when defining dynamic parking limits. This paper used quantitative models to assess different analytical tools that study LZ occupation and parking durations using tracked freight parking data from the City of Vic (Spain). CatBoost outperformed other machine learning (ML) algorithms and queuing models in estimating LZ occupation and parking durations. This paper contributes to the freight parking field by understanding how data analytics support dynamic parking limits definition, enabling responsive curbside management

Joint modeling of arrivals and parking durations for freight loading zones: Potential applications to improving urban logistics

This paper analyzes truck parking patterns in urban freight loading zones by jointly modeling the vehicle arrival rates and the parking durations. Three models were explored: 1) Count data (Negative Binomial) for vehicle arrivals, 2) Survival (Weibull) model for parking duration and 3) A joint model for arrivals and duration. The count data model estimates the parking demand i.e., the rate of truck arrival, while the survival model estimates the probability that a truck is parked for one more minute. The joint model is compared with separate models for predictability and performance. The dataset used in this research is obtained using a mobile phone parking application, at eight loading zones in the city Vic, Spain over an 18-month period from July 2018 to December 2019, comprised of vehicle parking durations, date, time of arrival and departure, professional activity, and vehicle type (weight). The parking activity data are complemented with built in environment variables of the loading zones, such as the number of establishments in a certain radius, the average walking distance to establishments, the presence of pedestrian pavement, the number of traffic lanes, among others. The joint model outperforms the models estimating the arrival rates and durations separately in goodness of fit and predictability. The model results showed that truck arrival rates vary significantly across days of the week, months, and arrival times. The parking durations are highly dependent on professional activity, vehicle type, and size. Tuesdays and Wednesdays have higher arrival rates compared to other days of a week (except Sundays). Among activities, the transport and parcels require longer parking durations. Among the vehicle types, trucks with gross weight larger than 3.5 tons park longer. This paper concludes by explaining the potential of these modeling approaches in improving urban freight operations, evaluation of various policy implications, limitations, and future research

Assessing the eco-efficiency benefits of empty container repositioning strategies via dry ports

Trade imbalances and global disturbances generate mismatches in the supply and demand of empty containers (ECs) that elevate the need for empty container repositioning (ECR). This research investigated dry ports as a potential means to minimize EC movements, and thus reduce costs and emissions. We assessed the environmental and economic effects of two ECR strategies via dry ports—street turns and extended free temporary storage—considering different scenarios of collaboration between shipping lines with different levels of container substitution. A multiparadigm simulation combined agent-based and discrete-event modelling to represent flows and estimate kilometers travelled, CO2 emissions, and costs resulting from combinations of ECR strategies and scenarios. Full ownership container substitution combined with extended free temporary storage at the dry port (FTDP) most improved ECR metrics, despite implementation challenges. Our results may be instrumental in increasing shipping lines’ collaboration while reducing environmental impacts in up to 32 % of the inland ECR emissions

Freight trip generation models: Using establishment data to understand the origin of urban freight traffic

FTG has resulted in a powerful tool to provide insights into freight transport demand that support planning and policy design processes. The chapter introduces a taxonomy of the FTG research field and a discussion of considerations for applicability purposes. The City of Stockholm serves as a case study to show practical implications in the development and application of FTG models to the accommodation, food services, manufacturing, offices, retail, and wholesale sectors. The chapter connects FTG models with the processes of drawing up urban freight strategies. Conclusions from the current state of knowledge and the case study will allow academics and practitioners to have clear foundations to use FTG models and to go further on the proposed research agenda