Piecewise linear regression: a statistical method for the analysis of the relationship between traffic signal parameters and air pollutant emissions

Christina Ng, Susilawati Susilawati, Irene Chew Mei Leng

    Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

    1 Citation (Scopus)

    Abstract

    On-road emissions from urban traffic during interrupted and congested flow conditions are often higher compared to free-flow traffic condition and are often influenced by changes in accelerating and decelerating speed due to frequent stop-and-go. In this study, we present linear regression models to investigate effects of congestion on traffic emissions along an arterial road and used regression models to derive analytical expressions separating free-flow traffic conditions with congested conditions. The regression models use traffic demands and degree of saturation as explanatory variables. Correlation of emission rates with traffic parameters (cycle length, the degree of saturation, and flows) was investigated at a range of conditions extending from under-saturated to oversaturated traffic flows. Data for calibrating these models are obtained from the application of Sidra Intersection, a micro-analytical software. A comparison of the proposed models to similar information contained in the Highway Capacity Manual marked similarity to the point of saturation and suggested an additional relationship with emission rates. Results confirmed that the relationship between the amount of air pollutant emission and traffic flow as well as the degree of saturation shown a piecewise linear relationship with significant differences in slopes separated by breakpoints. Moreover, regression results suggested that degree of saturation for the point of saturation is proposed for volume-to-capacity (v/c) ratio values at 0.99, indicating that for all volumes, the change in emission of CO2 occurs around this value. As the efforts at integrating traffic simulation models and emission models have become a fast-evolving research area, the findings of this study will set up a solid and extensive application of simulation optimisation in sustainable traffic planning, operations, and management as well as reducing emissions at urban areas.

    Original languageEnglish
    Title of host publication38th Australasian Transport Research Forum, ATRF 2016, Melbourne, 16 November 2016 - 18 November 2016,
    PublisherAustralasian Transport Research Forum
    Publication statusPublished - 2016
    EventAustralasian Transport Research Forum 2016 - Melbourne, Australia
    Duration: 16 Nov 201618 Nov 2016
    Conference number: 38th
    https://www.australasiantransportresearchforum.org.au/papers/2016 (Proceedings)

    Conference

    ConferenceAustralasian Transport Research Forum 2016
    Abbreviated titleATRF 2016
    Country/TerritoryAustralia
    CityMelbourne
    Period16/11/1618/11/16
    Internet address

    Keywords

    • Air pollution
    • Carbon dioxide
    • Traffic signal
    • Urban traffic

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