01660447

Component

Network Fundamental Diagram (NFD) or Macroscopic Fundamental Diagram (MFD) represents dynamics of traffic flow at the network level. It is used to design various network-wide traffic control and pricing strategies to improve mobility and mitigate congestion. NFD is well defined when congestion distribution in the network is homogenous. However, in real world networks, traffic is often heterogeneously distributed and initiated from an asymmetric and time-varying origin-destination (OD) demand. In this paper, the authors formulate a resource allocation problem to find the optimal location of fixed measurement points and sampling of probe trajectories to estimate the NFD, accounting for network traffic heterogeneity and limited resources for data collection. Data from probe trajectories are used to estimate space-mean speed while data from fixed detectors are used to estimate traffic flow. Thus, the proposed model does not require an aggregate penetration rate of probe vehicles as a priori to be known, which is one of the main contributions of this study. The proposed model is a mixed integer problem with non-linear constraints known to be NP-hard. A heuristic solution algorithm (Simulated Annealing) is implemented to solve the problem. Using a calibrated simulation-based network model of downtown Chicago, the authors present a successful application of the proposed model and solution algorithm to estimate NFD. The results demonstrate the sensitivity of the NFD estimation accuracy to the available budget (number of fixed measurement points and probe trajectories). The authors show that for a fixed proportion of OD trajectories, the increase in the proportion of fixed detection points increases the accuracy of NFD estimation as expected. However, when the proportion of fixed detection points is set to be constant, the increase in the proportion of OD trajectories does not necessarily improve the estimated NFD. Results also hold true when varying demand is used to emulate variation in day-to-day traffic patterns.

This paper was sponsored by TRB committee AHB45 Standing Committee on Traffic Flow Theory and Characteristics.

18-06612

English

11p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; References; Tables

Algorithms; Heuristic methods; Probe vehicles; Traffic flow rate; Traffic measurement; Trajectory

Chicago (Illinois)

Highways; Operations and Traffic Management; Planning and Forecasting

Transportation Research Board Annual Meeting 2018 Paper #18-06612

TRIS, TRB, ATRI

Jan 8 2018 11:42AM