A non‐parametric Hawkes process model of primary and secondary accidents on a UK smart motorway

Kieran Kalair, Colm Connaughton and Pierfrancesco Alaimo Di Loro

Journal of the Royal Statistical Society Series C, 2021, vol. 70, issue 1, 80-97

Abstract: A self‐exciting spatiotemporal point process is fitted to incident data from the UK National Traffic Information Service to model the rates of primary and secondary accidents on the M25 motorway in a 12‐month period during 2017–2018. This process uses a background component to represent primary accidents, and a self‐exciting component to represent secondary accidents. The background consists of periodic daily and weekly components, a spatial component and a long‐term trend. The self‐exciting components are decaying, unidirectional functions of space and time. These components are determined via kernel smoothing and likelihood estimation. Temporally, the background is stable across seasons with a daily double peak structure reflecting commuting patterns. Spatially, there are two peaks in intensity, one of which becomes more pronounced during the study period. Self‐excitation accounts for 6–7% of the data with associated time and length scales around 100 min and 1 km, respectively. In‐sample and out‐of‐sample validation are performed to assess the model fit. When we restrict the data to incidents that resulted in large speed drops on the network, the results remain coherent.

Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.1111/rssc.12450

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:70:y:2021:i:1:p:80-97

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().