A heuristic methodology to tackle the Braess Paradox detecting problem tailored for real road networks

Adding a new road to help traffic flow in a congested urban network may at first appear to be a good idea. The Braess Paradox (BP) says, adding new capacity may actually worsen traffic flow. BP does not only call for extra vigilance in expanding a network, it also highlights a question: Does BP exist in existing networks? Literature reveals that BP is rife in real world. This study proposes a methodology to find a set of roads in a real network, whose closure improve traffic flow. It is called the Braess Paradox Detection (BPD) problem. Literature proves that the BPD problem is highly intractable especially in real networks and no efficient method has been introduced. We developed a heuristic methodology based on a Genetic Algorithm to tackle BPD problem. First, a set of likely Braess-tainted roads is identified by simply testing their closure (one-by-one). Secondly, a seraph algorithm is devised to run over the Braess-tainted roads to find a combination whose closure improves traffic flow. In our methodology, the extent of road closure is limited to some certain level to preserve connectivity of the network. The efficiency and applicability of the methodology are demonstrated using the benchmark Hagstrom-Abrams network, and on a network of city of Winnipeg in Canada.