The discussion started with the recent V2I demonstration in Frisco. The time to green feature was demonstrated where a driver at a red light receives a countdown timer to the green light. Future features will be the reduced speed recommendation, where signals are sent to the vehicle for optimum speed between traffic signals without the need for stopping. Currently, the applications are certain only for late 2016 and 2017 Audis with the traffic light information service. However, from the diagram in the linked article, it appears that there aren’t technical limitations on other models eventually using the system. Frisco expects the system to go live in early 2017

John Lindsay discussed the beta of his Smooth Driver Monitoring app, which monitors driver behavior for sudden stops using the accelerometer and GPS data. The location of the sudden stop are logged and displayed to the user as they drive. Over time, clusters of sudden stops may be formed. This display encourages drivers to change their driving behavior in those locations and average their speed through the location. The app is native Android. See the prior Accessing Sensors in Android Development slides (PDF).

Shayne O’Sullivan discussed the Vinli hardware and software. The hardware aspect of Vinli is a dongle that plugs in the OBD port of the vehicle. The dongle adds 4G LTE connectivity to the vehicle for passengers as as outbound transport of OBD data. The dongle also includes an accelerometer and GPS. The data provides the basis for the Vinli app development environment, which is the largest app ecosystem for cars. The raw OBD, accelerometer, and GPS data are uploaded for controlled access by apps. The Vinli platform provides categorized access to the raw data and provides access to some basic analytics on the raw data. The access is generally RESTful and has wrappers for web socket, Android, and iOS access. See the Vinli developer portal or the developer docs.

Brandon Swink discussed using the IBM Bluemix for a smarter city’s use of aggregate driver data in order to aid increased proactive traffic management/communications. He discussed processing individual vehicle data such as that output by the Smooth Driver App and other individual vehicle data using tools such as IBM Streaming Analytics Services (PDF slides), individually or in aggregate. IBM Streaming Analytics enables a developer to receive and process large volumes of data with low latency. The demo include receiving data that was processed to detect an accident condition for a vehicle. A geofence was created around the accident vehicle for signaling for use by city staff such as traffic or EMS. See the Connected Car Bluemix demo environment.

Jimmy Smerud from Forgerock discussed security issues in a vehicle and connected vehicle setting. He started with the different roles in vehicle access and use such as adult drivers, teen drivers, mechanics, and valets . Following that was discussion of a reference connected device architecture where security can be applied. See the presentation slides (PDF) or the  video of Forgerock Authenticator integration.