Joint modeling of arrivals and parking durations for freight loading zones: Potential applications to improving urban logistics
Journal article, 2022

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.

Urban Freight

Truck Parking Zones

Joint Modeling of Counts and Survival

Freight Parking Management


Lokesh Kumar Kalahasthi

Chalmers, Technology Management and Economics, Service Management and Logistics

Ivan Sanchez-Diaz

Chalmers, Technology Management and Economics, Service Management and Logistics

Juan Pablo Castrellon

Chalmers, Technology Management and Economics, Service Management and Logistics

National University of Colombia

Jorge Gil

Chalmers, Architecture and Civil Engineering, Urban Design and Planning

Michael Browne

University of Gothenburg

Simon Hayes

Edifici NEC

Carles Sentís Ros

Edifici NEC

Transportation Research Part A: Policy and Practice

0965-8564 (ISSN)

Vol. 166 307-329

Using data analytics for smart loading zones management in cities

VINNOVA (2019-03093), 2019-11-19 -- 2020-10-20.

Subject Categories

Transport Systems and Logistics

Water Engineering

Vehicle Engineering



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