Reducing Traffic Congestion with IndiGO Lidar Sensors
Reducing Traffic Congestion with IndiGO
Longer commute times, logn lines of cars waiting at intersections, and slower speeds
Longer commute times, long lines of cars waiting at intersections, and slower speeds: all are symptoms of the traffic congestion problem. In some busy urban areas, drivers can spend up to 119 hours a year stuck in traffic. With over 80% of commuters choosing private vehicles to get to work at the same time, many road systems struggle to handle peak-hour loads. All those idling cars also lead to increased carbon emissions. Solutions include improving traffic flow with better timing of traffic lights, improving infrastructure planning by considering pedestrians and cyclists, and reducing car crashes that block arteries. Transport planners have their hands full trying to find methods to address the traffic congestion problem.
Improving traffic flow
with a new technology
Traffic flow at intersections can be dramatically improved with detailed data that provide information on all road users, including pedestrians and cyclists. Real-time multimodal data can help adjust the timing of traffic lights and extend the amount of time allotted to pedestrians to cross the street. If no pedestrians are present, cars can be given the right to proceed. Unfortunately, up until recently, existing methods were not able to supply the type of information to do this.
Current methods are unable to provide multimodal data on vulnerable road users or data in real-time. Safety analytics and information about vehicle speed, crashes, trajectories, or turning directions are difficult or impossible to obtain. Even when the available information is used, once adjustments are made to intersections, new studies must be implemented to measure the results of the changes to see if they are successful.
Inductive loops, radar and video cameras have been used to obtain the data cities use to make policy changes regarding intersections, but each comes with its own set of drawbacks, including high cost or, data limitations. In the case of video cameras, privacy has become an issue for citizens’ rights groups.
Lidar and AI for Enhanced Traffic Analytics
This is why Bluecity combines lidar sensors and artificial intelligence to provide real-time multimodal data for city engineers, transport planners and consulting firms involved in improving traffic flow. Bluecity’s IndiGO solution provides many benefits over existing systems.
- Waterproof casing for reliable 24/7 data collection in any weather or lighting conditions.
- 360-degree coverage so one sensor per intersection is usually enough
- 60-meter radius coverage for vehicles and 40-meter radius for pedestrians
- No collection of private citizen data
- One single wire for power and data
- Easy and inexpensive installation and maintenance
- Embedded NVIDIA GPU and LTE/5G IoT connectivity
- Multimodal – easily distinguishes between vehicles, cyclists and pedestrians.
- Real-time tracking
- Counts of data in aggregate or disaggregate formats
- AI for better visualization and analytics
- Integration into traffic controllers
IndiGO iQ platform
- Multimodal count data that includes volume and direction
- Occupancy ratio
- Streaming of critical conflicts
- Advanced safety analytics help identify dangerous intersections before accidents occur
- Dashboards allow selections, filters and download data for improved traffic planning
With IndiGO, you get the best transport planning results by capturing multimodal, real-time traffic data. Our solution is easy to install and maintain and most intersections require only one sensor. This powerful and cost-effective solution allows you to better understand and adjust smart city mobility.