Originally published by Penn State News
By Sara LaJeunesse
Driving services, like Uber and Lyft, are praised by some for their ability to reduce traffic congestion. Still, others argue that driving services increase traffic congestion. A recent study by researchers at Penn State and Boston University analyzed traffic data from across California and found that whether driving services increase or decrease traffic congestion depends on a number of factors, including day of the week, and whether the region previously had high use of public transportation.
“Cities around the world are struggling with traffic congestion issues,” said Suvrat Dhanorkar, associate professor of supply chain management, Smeal College of Business, Penn State. “Sustained traffic jams can have significant impacts on environmental quality, and it can also adversely affect trade and human productivity by increasing fuel and lost time costs.”
Proponents of ride-hailing argue that the services reduce traffic congestion by offering carpooling options and effectively matching patrons with drivers, thereby reducing the overall use of cars. On the other hand, ride-hailing services can increase traffic congestion due to the convenience of travel they offer. This can lead to larger travel volumes and lengths, which can increase overall traffic. In addition, users can turn to ride-hailing services instead of public transportation, such as buses and subways, which can further aggravate traffic jams.
In its study, the team – which also included Gordon Burtch, Kelli Questrom Lecturer in Management, Boston University – aimed to reconcile these opposing perspectives. Taking advantage of Uber’s staggered intakes in various geographic markets in California, the researchers used monthly data from approximately 10,000 vehicle detector station units across California to conduct a statistical analysis to estimate the impact of driving services on traffic volumes. They focused specifically on Uber, as the company is the market leader in terms of market value and penetration. In fact, in 2016, Uber had entered more than 66 countries and 507 cities worldwide.
Overall, the researchers found that Uber’s effect on traffic depends on various contextual factors. For example, the team found some signs of aggregation effects on weekdays, leading to a decrease in traffic load by approximately 0.5%. Over the weekend, Uber was associated with significant congestion effects, which increased the traffic load by up to 8.5%.
However, in regions with high prior public transport, Uber was associated with a greater congestion effect on weekdays of up to 8,451% and on weekends of up to 8,841%.
Previous car-sharing behaviors also significantly affected the way patrons used Uber, with greater congestion effects on weekdays of up to 1.152% and on weekends of up to 3.407% in regions with low prior carpooling.
Finally, the availability of Uber Black, a premium ride-hailing service suitable for exclusivity and lower speeds of use, almost exclusively led to a congestion effect with increases in traffic load of up to 7.144% over the weekend.
“Despite their promise, popularity and rapid growth, the transit implications of riding platforms are not entirely clear,” Dhanorkar said. “On the one hand, ridehail services can provide traffic reductions by effectively matching customer demand with resources or by facilitating car sharing. But on the other hand, riding hail can cause extra travel due to increased convenience and substitution of travel mode, which can create congestion. Our study, which we know is the most comprehensive analysis of Uber’s traffic effects, suggests a possible explanation for the conflicting evidence in previous work that can be addressed by taking heterogeneity into account. ”
The results appeared in a recent issue of the journal Transport science.
Featured photo of Alvaro Reyes on Unsplash
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