Trend shifts in road traffic collisions - An application of Hidden Markov Models and Generalised Additive Models to assess the impact of the 20mph speed limit policy in Edinburgh

Popov, Valentin, Nightingale, Glenna, Williams, Andrew James, Kelly, Paul, Jepson, Ruth, Milton, Karen ORCID: https://orcid.org/0000-0002-0506-2214 and Kelly, Michael P. (2021) Trend shifts in road traffic collisions - An application of Hidden Markov Models and Generalised Additive Models to assess the impact of the 20mph speed limit policy in Edinburgh. Environment and Planning B: Urban Analytics and City Science, 48 (9). pp. 2590-2606. ISSN 2399-8091

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Abstract

Empirical study of road traffic collision (RTCs) rates is challenging at small geographies due to the relative rarity of collisions and the need to account for secular and seasonal trends. In this paper, we demonstrate the successful application of Hidden Markov Models (HMMs) and Generalised Additive Models (GAMs) to describe RTCs time series using monthly data from the city of Edinburgh (STATS19) as a case study. While both models have comparable level of complexity, they bring different advantages. HMMs provide a better interpretation of the data-generating process, whereas GAMs can be superior in terms of forecasting. In our study, both models successfully capture the declining trend and the seasonal pattern with a peak in the autumn and a dip in the spring months. Our best fitting HMM indicates a change in a fast-declining-trend state after the introduction of the 20 mph speed limit in July 2016. Our preferred GAM explicitly models this intervention and provides evidence for a significant further decline in the RTCs. In a comparison between the two modelling approaches, the GAM outperforms the HMM in out-of-sample forecasting of the RTCs for 2018. The application of HMMs and GAMs to routinely collected data such as the road traffic data may be beneficial to evaluations of interventions and policies, especially natural experiments, that seek to impact traffic collision rates.

Item Type:	Article
Uncontrolled Keywords:	road traffic collisions,speed limits,state-space models,time series,trend shifts,geography, planning and development,urban studies,architecture ,nature and landscape conservation,management, monitoring, policy and law ,/dk/atira/pure/subjectarea/asjc/3300/3305
Faculty \ School:	Faculty of Medicine and Health Sciences > Norwich Medical School
UEA Research Groups:	Faculty of Medicine and Health Sciences > Research Centres > Lifespan Health Faculty of Medicine and Health Sciences > Research Centres > Population Health
Related URLs:	http://www.scopus.com/inward/record.url?...
Depositing User:	LivePure Connector
Date Deposited:	02 Dec 2020 00:50
Last Modified:	03 Jan 2024 02:29
URI:	https://ueaeprints.uea.ac.uk/id/eprint/77853
DOI:	10.1177/2399808320985524

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