Skip to main content

Sharing the knowledge on car sharing

Researchers help develop strategy for smart growth of popular service
September 11, 2012
By Laurence Miall

Car-sharing services such as Quebec’s Communauto have seen a large increase in members in the past decade. | Photo courtesy of Communauto
Car-sharing services such as Quebec’s Communauto have seen a large increase in members in the past decade. | Photo courtesy of Communauto

Share and share alike is a concept we all learn as youngsters. Of course, when it comes to something as personal – and expensive – as a car, sharing’s not so easy. Due to rising fuel costs, increased concerns about the environment and overcrowded cities, car sharing is becoming a popular way to get around. Can it be more popular still?

Researchers from the Concordia Institute of Information Systems Engineering can answer this question with a resounding “yes.” They have piloted a computer model that can help determine how a car-sharing service can grow, maximize customer satisfaction and be profitable.

“Given car sharing’s goal of reducing congestion and carbon emissions, our work represents a potential boost to environmental sustainability,” explains Anjali Awasthi. The assistant professor in the Faculty of Enginering and Computer Science came to Concordia in 2008 after spending many years researching car-sharing services in Europe.

“I wanted to apply the lessons I’d learned overseas to the Montreal region,” recalls Awasthi, who was quick to enlist the help of her master’s student Ahmed Al Fassi. They turned to local car-sharing company, Communauto. Founded in 1994, the Montreal-based organization is the oldest of its kind in North America.

Awasthi and Al Fassi assessed which areas had the greatest growth potential in Montreal, based on factors like population density and customers’ proximity to existing stations. They focused on data from Communauto for one particular area – the borough of Verdun. They then simulated the response to various growth scenarios to measure the potential impact on the level of activity at each station, the level of activity among the service’s members, and the availability of cars to meet customer demand.

The researchers’ model can test hundreds of different scenarios and evaluate their respective performances. It can help predict the best strategy for car-sharing growth in any given location, be it increasing the number of vehicles at one station, merging stations, or opening a new station entirely.

For Communauto, the scholarly research was a great boost. “The expertise and input of professor Awasthi and Ahmed Al Fassi allowed us to improve the analysis necessary to determine our growth strategy,” says Communauto’s Director of Development and Public Relations Marco Viviani. “This was the first step that we hope will lead to a long-term collaboration.”

Awasthi is now collaborating on another study with Communauto, funded by the Natural Sciences and Engineering Research Council of Canada. This time her focus has switched from the stations to the car fleet itself, and she’ll be identifying possible ways to deploy vehicles more efficiently.

Rewarding research: The paper authored by Awasthi and Al Fassi was one of three selected as finalists in a competition run by the Canadian Operational Research Society. It was also published this year in the international journal Expert Systems with Applications.

Related links:
•    Concordia Institute of Information Systems Engineering
•    Concordia's Department of Computer Science and Software Engineering
•    Communauto
•    Natural Sciences and Engineering Research Council


Back to top Back to top

© Concordia University