Traditionally, offset optimization for coordinated traffic signals is based on average travel times between intersections and average traffic volumes at each intersection, without consideration of the stochastic nature of field traffic. Using the archived high-resolution traffic signal data, in this project, we developed a data-driven arterial offset optimization model that will address two well-known problems with vehicle-actuated signal coordination: the early return to green problem and the uncertain intersection queue length problem. To account for the early return to green problem, we introduce the concept of conditional distribution of the green start times for the coordinated phase. To handle the uncertainty of intersection queue length, we adopt a scenario-based approach that generates optimization results using a series of traffic-demand scenarios as the input to the offset optimization model. Both the conditional distributions of the green start times and traffic demand scenarios can be obtained from the archived high-resolution traffic signal data. Under different traffic conditions, queues formed by side-street and main-street traffic are explicitly considered in the derivation of intersection delay. The objective of this model is to minimize total delay for the main coordinated direction and at the same time it considers the performance of the opposite direction. Due to model complexity, a genetic algorithm is adopted to obtain the optimal solution. We test the performance of the optimized offsets not only in a simulated environment but also in the field. Results from both experiments show that the proposed model can reduce travel delay of coordinated direction significantly without compromising the performance of the opposite approach.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen


    Exportieren, teilen und zitieren



    Titel :

    SMART-Signal Phase II: Arterial Offset Optimization using Achieved High-Resolution Traffic Signal Data


    Beteiligte:
    H. X. Liu (Autor:in) / H. Hu (Autor:in)

    Erscheinungsdatum :

    2013


    Format / Umfang :

    37 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch





    Arterial Signal Offset Optimization Using Crowdsourced Speed Data

    Xia, Liang / Li, Xiaofeng / Shaon, Mohammad Razaur Rahman et al. | Transportation Research Record | 2022



    Traffic signal offset prediction

    AKSENY CHRISTIAN / PORTOLI STEFANO / FORRONI DANIEL et al. | Europäisches Patentamt | 2023

    Freier Zugriff

    TRAFFIC SIGNAL OFFSET PREDICTION

    AXENIE CRISTIAN / BORTOLI STEFANO / FORONI DANIELE et al. | Europäisches Patentamt | 2022

    Freier Zugriff