Big data and the commuter experience

Big data and the commuter experience

Digitalisation has demonstrated rich value in industries such as finance and real estate, but it has yet to make a significant impact in the ground transportation industry

Big data analytics is the future of operational efficiency targeting improved passenger experience.

Exponential growth and availability of data along with the latest digital technologies – big data and big analytics, machine learning, etc – open new ways towards more efficient operations, structured interactions between the various services, and addresses passenger expectations for more personalised services.

Public transport’s challenges

With the growth in urban population, there is an exponentially increasing demand for public transportation.

Trains, buses, and other forms of transport are now experiencing bigger crowds of people and forcing mass transit system operators to deal with the consequences of it. A bigger mass of people often means altered efficiency. Large floods of people accompanied with rush hour overcrowding, delays, human error, and malfunctioning machines creates a plethora of unhappy customers having to choose between waiting in long lines and finding an alternate mode of transportation.

Along with ridership growth, passenger expectations are increasing. Passengers now expect a more personalized experience with maximum comfort and ease. While operators are faced with all of these issues, they are also bounded by the constraints of existing aging assets and increasing operating costs.

Operators’ current efforts in understanding their passengers involve manually counting passengers at a few particular stations only a fraction of the time on particular days. This method is costly, inaccurate and only provides a very limited understanding of the passenger journey patterns.

It misses the variability between days or stations and the different perturbations that can occur in the network.

Big data analytics

Transit operators are generating huge amounts of data and the latest digital solutions can make the data talk and create value for them. For instance, big data analytics allow them to learn about passengers and their everyday patterns.

By creating algorithms that analyse multiple data points like ticketing data, GSM, Wi-Fi, Bluetooth, and social media posts, they can better understand the everyday flow. More importantly, they can study the data to be more efficient and provide a better service. Unlike traditional surveys, with big data analytics, all real trips made by commuters are taken into account to ensure completeness and fact-based outputs.

Armed with its digital services, Thales is shaping up to become a pioneer in the new digital era of the transport industry. As an example, Thales delivers the most up-to-date and accurate digital solution to one of the busiest urban rail networks in the world. Thales’ product Naia is delivered as a service for the Train Occupancy and Platform Analytics for MTR Network project in Hong Kong.

With eleven railway lines and 93 stations, Hong Kong’s Mass Transit Railway (MTR) accommodates over five million passengers resulting in more than nine million data inputs each day.

Simplifying the complex

The big data analytics platform Naia assesses the performance of the urban rail network by processing the data from the network delivering on a fifteen-minute interval the number of passengers per train, per platform and per station.

It provides key performance indicators such as train occupancy, platform crowding, and waiting time or missed trains, enabling operators to study, plan and adapt the capacity of the lines and train services, ultimately giving riders a better commuting experience.

The data is securely gathered and collected in what is called a data lake before being processed. With an accuracy level of 95 per cent, the journey of each single passenger is reconstructed anonymously to enable the computation of the key performance indicators. Not only can the transit operators use the data to better plan and operate its services, the data can also be used as a policy tool to create win-win situations for both themselves and the commuters, as well as a tool for marketing campaigns.

Stephen Lau, manager for market analysis and planning at MTR, said. ‘Train occupancy and platform crowding analytics for MTR brings us many useful train service information, which supports us in performance monitoring and service planning for our expanding network.’

Also, moving towards near real-time data analytics for prediction and passenger sentiments analytics, rail operators and passengers are ensured of a consistent, safe, and efficient experience every day. This advanced technology enables rail operators to maximize efficiency and safety by anticipating what the crowd would be and, hence, mitigating risk and inefficiency of human error, delays, and rush hour over-capacity.

Direct benefits

Better understanding the journey patterns allow any public transport agency to adapt its time table, fare table, discount policy and transport resources. For instance, it can be materialized through a marketing campaign along the most crowded routes.

Operators can also decide to better dispatch their staff where the crowd is and may need assistance. Routes and connection can be redefined.

Passengers can also benefit from real time accurate information on waiting times at the platform, or through their personal connected devices. Thanks to the direct communication channel between the operation and passenger information systems, any delay or change is communicated immediately, without any operator intervention.

In a nutshell, serving the passengers better is a direct causation of an increase in ridership and, therefore, the generation of additional revenue by capturing more customers.

Digital services

Technical solutions are not sufficient. Data science as well as new development techniques – design thinking, lean usability, fast prototyping through the concept of minimal viable product – demonstrate the importance of joint efforts between an industrial player such as Thales and the public transport operators.

Iterative processes are what make big data analytics really meaningful to the users. Not only does Thales provide a solution at the beginning of a customer’s journey – it aims to be dedicated by being with the customer every step of the way. The flow of passengers, the way the passengers travel may be different, because there will be an event, there will be an opening of a new line, unforeseen circumstances.

The solution has to be adaptive and customized through time. Instead of delivering the full functionality at the beginning, the minimal scope covering user appeal, usability, reliability and functionalities is designed and developed in a short time, the prototype is presented to the users, their feedback is collected, fine-tuning applies to the prototype before expanding the scope of each component to deliver the desired solution.

About Thales

Thales is a global technology leader for the aerospace, transport, defence and security markets. With 64,000 employees in 56 countries, Thales reported sales of $17.6 billion in 2016. With over 25,000 engineers and researchers, Thales has a unique capability to design and deploy equipment, systems and services to meet the most complex security requirements.

Its exceptional international footprint allows it to work closely with its customers all over the world. Technology driven by nature, Thales is inspired to meet its goals in four core digital technologies: connectivity, data analytics (including real time), artificial intelligence, and cyber security.

Over the past two to three years, Thales has invested $1.2 billion to reinforce the group in these four core technologies. Recently, Thales launched a fully-fledged digital platform for industry-focused services called Digital Factory to cater to customers’ digital transformation in key markets.

To further enhance its capabilities and establish its position in the world of big data, Thales also made a strategic move in the acquisition of the Silicon Valley big data analytics giant Guavus, with extensive experience in the telecommunications industry in the US.

With a proven track record spanning more than 40 years in the rail industry, a detailed understanding of its customers’ activities and a broad portfolio of solutions and credentials, Thales has the expertise to meet the concerns of city authorities, with a particular focus on mobility.


Tel: +852 39 16 87 87

Email: [email protected]


2017-12-11T15:54:26+00:00 November 28th, 2017|December 2017|