Showcase Tag: Traffic Flow

Timing Travel with Precision

Davod Hosseini is a good guy to know if you’re a commuter. That’s because his “operations research” or OR, tries to solve complex problems in transportation planning and logistical management.

“The core process of OR involves identifying an issue, formulating a mathematical model to represent it, gathering and analyzing relevant data to understand its behaviour, and, finally, providing actionable recommendations by finding optimal or near-optimal solutions,” explains Hosseini, assistant professor of management science at Saint Mary’s University’s Sobey School of Business.

Specifically, Hosseini leverages OR to optimize routing, scheduling and vehicle assignment in two types of transportation systems — regular systems, in which he looks at transportation costs and customer satisfaction, and in riskier transportation systems involving transportation of hazardous materials (hazmat) via railroads, in which he aims to minimize risk.

“The optimization process in both cases is performed by considering factors such as traffic patterns, distance, service and delivery times, demand forecast and vehicle capacity, while ensuring all operational constraints, government regulations and customer requests are fulfilled,” Hosseini says. “However, the inherent variability in these factors adds a layer of complexity to the model, making it more challenging to achieve an optimal solution.”

“Companies such as Amazon or FedEx leverage advanced route optimization to plan daily deliveries for thousands of packages,” Hosseini explains. “The system considers factors such as delivery windows, traffic conditions, package size and driver location to create efficient routes and meet tight delivery deadlines.”

Another application is home health-care, where providers visit multiple patients daily. The system can account for patient location, appointment times, last-minute appointment cancellations, new patient requests, care urgency and unexpected traffic delays, to name a few, and then generate route planning that minimizes travel time, ensures on-time visits and maximizes patient experience.

On the hazmat side, one could imagine a use for chemical manufacturers who want to transport their products by rail. The software considers such factors as population density along the route and prioritizes less populated routes in case of an accident, weather conditions and track maintenance.

Hosseini says he uses ACENET services because he usually has large datasets, numerous constraints and variables in the mathematical model, and complex optimization algorithms.

“Traditional computing can become slow and impractical when dealing with vast amounts of data, such as railroad networks with thousands of tracks and intersections or logistics scenarios involving millions of delivery points. HPC provides the processing power to handle these large datasets efficiently.”

He says he has benefited from ACENET staff’s expertise in supercomputing to migrate his workflows from his university desktop to an HPC cluster.

Without ACENET’s tools, Hosseini says his work would take weeks or months to complete.

Redesigning Halifax with Data Cave Technology

It’s an opportunity that most cities don’t get very often – the chance to develop 16 acres of prime real estate in the heart of Halifax’s downtown, just steps away from the waterfront. The development land comes courtesy of a new initiative that will remove a 40-year-old downtown white elephant called the Cogswell Interchange, a leftover vestige of a highway project that was scrapped in 1971. HRM city planners have created an arresting vision for the property once the Interchange is hauled away over the next few years – a plan that includes multi-residential, office and retail complexes, an inter-model transit terminal, major downtown green space, multi-use trails stretching north along Barrington Street and a large open plaza at the end of the Granville Mall. Designing new traffic flow patterns through the city to compensate for the loss of the interchange is a major priority for the city – one that’s being helped by the ACENET Data Cave located at Saint Mary’s University in Halifax. In 2013, HRM municipal planning staff took part in an experiment at SMU that used the Data Cave technology to help design one of the roundabouts that will be created to help ease traffic flow once the Cogswell Interchange is gone. ACENET provides universities and other groups with access to one of the most powerful computer networks in Canada and the experts who run it – an accessible tool that is facilitating research and innovation across the region. The Data Cave is part of ACENET’s suite of services – a computer laboratory that allows users to create complex 3-D images of anything from molecules and machine parts to downtown city blocks. John Charles is the city planner behind the North Park Street Roundabout design. He says the Data Cave sessions were an experiment in city planning. “We attended an open house at the Data Cave about two years ago, and we were struck by the possibilities it offered for municipal design,” he says. “We decided to see if we could use our AutoCad files to create a 3-D model that we could use for the design.” Once in the Data Cave, ACENET staff converted the files into a high speed program capable of projecting a 3-D image of what the intersection will look like when the new roundabout is in place. Charles says the virtual projection allowed his team to visualize the myriad of considerations that must be taken into account during the design. “We have to consider things like pedestrian flow, active transportation flow, landscaping, historic building streetscapes, tree removal. It’s quite a complex process.” Charles outlined his initial experiences with the ACENET Data Cave at the High Performance Computing Symposium 2014, Compute Canada’s national conference for advanced research computing, in June. He told the audience at the Halifax conference that overall the experiment was positive. “There were a few problems with the quality of the projection but that was mostly to do with the quality of our own files,” he says. “We’ve been working on improving the quality of our files since then and I can see the Data Cave as becoming a very useful planning tool for us in the future.”