Didi: Public Transit Data For Urban Planning

22/10/2019

 

 

The move will win the goodwill of the company by city officials

 

 

The Chinese giant Didi Chuxing is opening its important transit data repositories with the release of two important data sets, in order to improve the understanding of transport models and optimize infrastructure investments.

The move will probably conquer the goodwill of the company by city officials after attracting greater control by the authorities, especially in the last year. Machine learning applications, largely driven by data sharing, play a fundamental role in the use of resources and in planning safer and smarter transport networks.

 

Didi will make two of its TTI historical data sets available

 

At the end of 2017, Didi launched for the first time its GAIA Initiative, a global research platform on which scientists can request access to anonymous data to explore traffic solutions.

Didi, thus, will make available two of its anonymized TTI (Travel Time Index) historical data sets that index urban congestion, collected by vehicles on its platform. To announce it was the CTO of Didi, Zhang Bo.

The release contains traffic congestion indices, calculated using passenger travel information, as well as the average speed of motor vehicles on Didi’s platform in the last year in six major Chinese cities: Shenzhen, Chengdu, Xi’an, Jinan, Suzhou and Haikou.

 

The data have been calculated, in the last period, in as many as six Chinese cities

 

The other set of data includes detailed historical data at the travel level, namely anonymised start and end points and route information from Didi’s Express and Premier service levels for a two-month period in Chengdu and Xi’an at the end of 2018. The company said that the timing of more than 2,000 traffic lights across the country has reduced congestion from 10% to 20%

The racing giant said it had worked with governments in more than 20 Chinese cities to provide innovative solutions for transport and traffic management, such as intelligent traffic signalling technologies. The company said that the timing of more than 2,000 traffic lights across the country has reduced congestion from 10% to 20% on average.

Didi, however, is not the only company that seeks to play an important role in an intelligent transport system built around connected autonomous vehicles. At the beginning of 2017, in fact, Uber launched an online website called Movement, which used data and tools that allowed users to measure travel times between points in cities such as Washington DC, Sydney and Manila.

 

 

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