The best view of the future trip, in real-time and in an open data format
“We provide information to our passengers from our vehicle location data, but how do we know it’s accurate? We need to give times that are true to life – the here and now!”
When we ask transport authorities and operators what their biggest objectives are right now, this is one of the things they say to us. In this blog we reveal how we help with our cutting-edge ETA prediction engine that’s generations ahead of the market.
Real-time passenger information that’s accurate and true to life
If you have vehicle location and monitoring systems, you’re in a great starting position. Given that Computer Aided Dispatch and Automatic Vehicle Location (CAD/AVL) systems are now considered standard for fixed-route transit networks, we imagine you do?
In theory, you have data to support your operations and provide real-time estimates to transit users on bus arrival and journey times. But how accurate is this information?
In our experience, real-time data originates from multiple dispersed data sources and is processed by various systems – often ‘bolted on’ over time with varying degrees of integration. Consideration is rarely given to the quality of the data being processed.
Our analysis tells us that arrival predictions in most cities can be as low as 35% accurate. Is that acceptable? We don’t think so! Here are three reasons why you need to ensure your AVL data is both accurate and compliant.
1. Why passengers care about accurate service predictions?
It’s generally accepted that providing real-time arrival and journey time predictions to passengers brings wide-reaching benefits. We also know that the window of tolerance for a bus turning up late is up to five minutes.
We need to reduce the anxiety about how late a bus might be and give passengers an increased sense of security and control over their journey. How?
By making the timetable obsolete for the immediate journey and replacing it with predictions at the point of travel that are more accurate. Like, completely accurate. So, if the passenger information display or mobile app states that the bus will arrive in 7 minutes, it arrives in 7 minutes.
We believe that providing better quality information enhances the passenger experience by removing uncertainty when waiting at stops. It will ultimately attract more people to use bus services and grow the overall bus market.
2. How does accurate passenger information support operations?
Business intelligence is the foundation of public transit operations, and data is the foundation of business intelligence.
It’s used for operational planning and decision making, to help address the problem of bus bunching or gapping, facilitate smooth and timely connections at transfer points, improve resilience and responsiveness to disruptions, and so much more.
It’s the basis for strategic decision making, detailed and accurate audit data offers insight into future transport trends and challenges, helping operators to proactively implement service changes to meet customer needs as they evolve.
You don’t need us to say this, but we will anyway: Making the best decisions is entirely dependent on good quality, accurate data.
3. How will good quality data in an open standard format impact me?
The current approach to open data is out of step with other sectors. There is a lack of accessible, accurate and timely data, which includes information on bus routes and service arrivals.
This is the case around the world, and every nation is in at a different stage when it comes to tackling the issue by enforcing a consistent set of global standards. Legislation is now emerging with the aim of making it easier for passengers to make informed travel decisions based on complete, accurate and timely data.
The industry will be required to comply with legislation that sets out clear ownership and responsibilities, a consistent set of data standards, complete digitization of processes and open innovation for creating digital applications. It will also require operators to illustrate the performance of local bus services, including historic punctuality data.
AVL open data standards are very much on everyone’s agenda right now. If it’s not on yours, watch out, it’s coming!
Introducing LIT Predict: Real-Time Predictions
LIT Predict is a cutting-edge ETA prediction engine that’s generations ahead of the market. It’s for public transport operators that need to go beyond real-time passenger information.
By aggregating all available data into a single source and applying advanced machine learning based statistical models, LIT Predict gives the best view of the future trip, in real-time and in an open data format.
It improves the information quality at all stages of the journey and generates arrival, departure and journey times that are reflective of the actual service.
- Existing CAD/AVL data feeds are consolidated and analyzed for accuracy so you can understand existing ETA data quality.
- The prediction engine replaces every arrival, departure and journey time made by your existing system with a more accurate ‘real-world’ calculation.
- The comprehensive, visual dashboard shows detailed analytics for every element of your transit network.
- Data is compliant with global open data standards for easy integration, providing a consistent, accurate data layer for every system.
- It can underpin your operational control system for a more accurate reflection of ETA, so support more robust service planning and operational control.
- It can also feed your passenger information system and other passenger touchpoints with more accurate data, such as web and mobile.
- Gather detailed insights on service performance and benchmark against historical data and other cities, for informed decision making.
- Monitor all aspects of your service, in-depth and in real-time, as well as historical data recording for compliance and audit reporting.
In a nutshell, LIT Predict offers a cutting-edge ETA prediction engine that will enable you to reap the rewards of real-time arrival, departure and journey times that are true to life.
If you want to go beyond real-time passenger information to real-life passenger information, contact us for a demo of LIT Predict.
This is blog four in a series on a deep dive into our main solution areas, read the previous on LIT Operate and the next on LIT Inform.