Estimating traffic delays and network speeds from lowfrequency GPS taxis traces for urban transport modelling

Abstract

The collection of actual traffic delays and road traffic speed data is essential in modelling urban transport resource efficiency, congestion and carbon and pollutant emissions, which is in turn part of core empirical basis for evidence-based policy making for improving urban sustainability. This data collection has also been one of the most expensive and time-consuming tasks, which restricts how well and how often the models can be built and validated, often to the extent that urban transport models have to rely on severely outdated data with sparse coverage. New smart data such as GPS vehicle traces has raised the prospect of remedying the data shortage, but for operational and data protection reasons often only low-sampling frequency traces are available. This paper proposes a novel method for estimating actual, congested link-speeds from lowsampling frequency taxi GPS traces that are publicly available. The method is based on a path inference process and is applied over a detailed road network in a large city region. It shows that low frequency GPS trajectories can significantly improve the spatial and temporal resolutions of traffic speed data for transport modelling and policy analysis. This opens up the prospect of improving road operation performance, managing travel demand and optimizing urban circulation.

Measuring Accessibility to Healthcare Using Taxi Trajectories Data: A Case Study of Acute Myocardial Infarction Cases in Beijing

“…Therefore, network representation is also a challenge. See Deng et al 20 for more details of how to address the two key challenges.…”

“…The road network data of Beijing in 2008 were provided by Deng et al 20 The GPS trajectory dataset employed in this study includes 1 500 000 observations from 10 357 taxis within the Fifth Ring Road of Beijing covering the 5:00-11:00 am period from Monday the 4th to Wednesday the 6th of February 2008. The data were derived from Microsoft Research Asia.…”

“…Each observation contains details of the taxi identifiers, locations, and timestamps. We did not calculate the congested link speeds from the taxi GPS traces; instead, we directly obtained the link speed data within Beijing’s Fifth Ring Road from Deng et al 20 who proposed the method employed in this study for calculating congested link speeds from taxi GPS traces. The area within the Fifth Ring Road of Beijing is the area from the centre of Beijing to the Fifth Ring Road in Beijing, which is the main area of traffic congestion.…”

TomTom Data Applications for the Assessment of Tactical Urbanism Interventions: The Case of Bologna

“…Lately, Floating Car Data has been used as ground data for research studies addressing mobility tasks and issues, such as detecting and analysing urban patterns from GPS traces [12], estimating traffic delays and network speeds from low-frequency GPS taxi trajectories [13], detecting traffic congestion and incidents [14] or estimating or updating OD matrices.…”