Connected cars and data sharing to improve road safety?

Wide scale advancements in technology and data sharing has brought about a change in the decision-making process of many sectors, but this has until now mostly missed the auto industry. However, connected and autonomous vehicles are ready to break this wall and the “wave of attribution” is finally coming to driving behavior. A collaboration between Ford, Uber, and Lyft will share data over a common platform called SharedStreets and aims to improve roadway safety and curbside management.

New multimodal trip data on the horizon

StreetLight Data, which provides trip-making data compiled from cellphones and mobile devices, recently announced a new multimodal data initiative called “M2.” The company has offered data from personal and commercial vehicles for several years. SSTI used these data for a study of travel demand management opportunities in Northern Virginia. By incorporating additional data from location-based services, the company can now identify trips made by walking, biking, transit, and potentially other modes.

Curbs: A new data frontier

State and local transportation agencies have long focused on what’s happening between the curbs—collecting data about the speed, volume, and types of vehicles moving along each road—but growing competition for curb space from parked cars, bikes, taxis, TNCs, and deliveries presents new challenges both in terms of data and policy. Fortunately, data experts are stepping up to the task.

Opportunities and potential bias in new transportation data

A new issue brief from the Center for American Progress examines congestion on roadways in the United States and considers the potential and pitfalls of new data sources, such as those provided by private ride hailing companies including Uber and others. Although cities are eager to access these private sources of data, the report warns that planners should be careful of relying too heavily on these sources.

Opportunities and potential bias in new transportation data

A new issue brief from the Center for American Progress examines congestion on roadways in the United States and considers the potential and pitfalls of new data sources, such as those provided by private ride hailing companies including Uber and others. Although cities are eager to access these private sources of data, the report warns that planners should be careful of relying too heavily on these sources.

Big data enables new tool for analyzing and diagnosing traffic congestion

StreetLight Data, which provides trip-making data from mobile devices and smartphone apps, has just launched a new interactive Congestion Analysis tool. The tool lets subscribers identify congested roads by time of day, break down the traffic in terms of trip length, trip purpose, and other characteristics, and then focus on specific strategies to relieve demand.

Tapping into TNC data

With the rise of transportation network companies like Uber and Lyft, and growing concerns about their effects on traffic and curb usage, transportation agencies and local governments are eager for data. Data from TNCs, however, are heavily guarded. Many governments are trying to negotiate agreements with these companies and working on laws that require data sharing. Others, however, are getting more creative.

SmarterRoads: Virginia’s public-private transportation data sharing strategy

The Virginia Department of Transportation has launched a public cloud-based data portal that contains a vast array of state transportation data. The portal is named “SmarterRoads” and will be available to anyone who creates a free account. Information contained in the portal includes average daily traffic, crashes, signal data, vehicle miles traveled, and speed limits. 

New SSTI Resource: Understanding Trip-Making with Big Data

SSTI has released a new resource for decision-makers interested in using big data to understand travel patterns, but who are not sure how to get started. This new brief provides an overview of trip-making data from cellphones, mobile apps, and in-vehicle GPS devices. It shows example applications and offers lessons learned from our recent Connecting Sacramento study and from past studies in Colorado and Virginia.

Connecting Sacramento

Connecting Sacramento is the first study to incorporate both accessibility analysis and tripmaking data, including data from multiple sources, and assess how they can be used together to guide transportation- and land use-related decisions. This study focused specifically on opportunities to improve first- and last-mile connections to light rail transit in Sacramento, but its findings are widely applicable.