Multi-Path Progression Optimization at an Urban Interchange: A Case Study

Abstract

Progression optimization is a common approach for coordinating traffic signals along arterial streets as well as arterial networks. A number of techniques with varying degrees of refinement have been developed for this purpose (1-2). In recent years another layer of sophistication has been added by providing separate bands of progression for major origin-destination path flows crossing in-and-out of the arterial. A typical example where traffic turning in at intersection A and turning out at intersection C is allocated a separate band that enables it uninterrupted progression. This occurs in parallel with the two mainstream bands. The program that designs such bands utilizing vehicular traffic origin-destination information is called OD-BAND (3).

This approach has been extended to provide progression opportunities for major O-D path flows in both arterials and in networks . The program uses a mixed-integer linear programming formulation to optimize all relevant signal parameters, including: green times, cycle time, phase sequences and offsets.

A special case with added complexity concerns interchanges where multiple origin-destination path flows converge into a limited space, especially when traffic volumes are at or near capacity. In this paper we consider as a case study the Hashalom Interchange in Tel Aviv. This interchange consists of four closely-spaced intersections with multiple O-D flows. The different demand volumes create severe congestion in the middle-link which crosses over the Ayalon freeway. The objective is to determine optimal progressions that minimize travel time through the interchange and average vehicular delay.

Two cases were analyzed: (a.) the existing pattern of flows; (b.) an optimized pattern using the OD-BAND model. This mixed-integer linear programming problem is solved by the CPLEX software . The results are then compared by microscopic simulation using the AIMSUN software.

The results indicate that by careful selection of the major O-D path flows and using the MILP algorithm one can obtain substantial improvements in network performance.

References

1. GARTNER, Nathan H., et al. MULTIBAND--a variable-bandwidth arterial progression scheme. Transportation Research Record, 1990, 1287.? .

2. ZHANG, Chao, et al. AM-band: an asymmetrical multi-band model for arterial traffic signal coordination. Transportation Research Part C: Emerging Technologies, 2015, 58: 515-531.?

3.ARSAVA, Tugba, et al. Arterial traffic signal coordination utilizing vehicular traffic origin-destination information. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC). IEEE, 2014. p. 2132-2137.?