Hyperloop Route Planner

Helping the adoption of Hyperloop by explaining the environmental advantages

Client Hardt
UN SDGs 09 Industry, Innovation And Infrastructure 13 Climate Action 17 Partnership For The Goals

01 Introduction

Hardt is a European hyperloop technology company that develops the hyperloop. With its test facilities in the Netherlands, Hardt has demonstrated and proven core hyperloop technologies. The company initiated the European Hyperloop Center, received an investment from the European Commission, and is working with European regulators to provide a pathway for the commercialisation of hyperloop technology in Europe and beyond.

AndAnotherDay partnered with Hardt to build a new route planner to allow users to compare travel via a Hyperloop network compared to current methods of transport (road, air etc.). The aim of the tool was to show customers that hyperloop is an efficient, affordable method of transport, when taking into consideration the time saved, but to also bring to the front the benefits to the environment and significant safety benefits for passengers.

As well as the need to demonstrate to stakeholders of the benefits of the innovative transport solution, Hardt needed to access anonymous user data to help drive further organisation-wide business decisions and insights.

02 The Project

Along with 3rd-party sources, the tool needed to incorporate data supplied by Hardt detailing the hyper loop routes, different speeds and stations. We investigated data from other sources including Google Openroute, Traveltime, Skyscanner, and Travelport. We worked with Hardt to find the most suitable available and advised on the costs before making a final decision. The APIs selected helped to inform the development stack we for the final tool.

Data supplied by Hardt included approximate geo locations for all hyperloop stations, energy use per mile/km for hyperloop, time taken mile/km for hyperloop, cost mile/km for hyperloop or the proposed cost taken between stations, and the global CO2 impact if the route was implemented.

Initially, we had hoped that most of the data could be taken from Google’s APIs but this was missing the detail of airport location, the available flights between each one, and the duration. Because we needed to calculate journey from the user’s departure location to the nearest suitable airport station and the same at the destination end we needed to combine Google’s APIs with Amadeus and our own locally sourced data. For accuracy, we then had to take the curvature of the Earth into account to get as accurate as we could.

$sql = "SELECT * , (3956 * 2 * ASIN(SQRT( POWER(SIN(( $lat - latitude) *  pi()/180 / 2), 2) +COS( $lat * pi()/180) * COS(latitude * pi()/180) * POWER(SIN(( $long - longitude) * pi()/180 / 2), 2) ))) AS distance FROM airports WHERE airport_type = 'large_airport' ORDER BY distance LIMIT 1";

    if ($result = $mysqli->query($sql)) {
        while ($obj = $result->fetch_object()) {
            $airport = array(
                'name' => trim($obj->name),
                'distance' => ($obj->distance * 1.609),
                'latitude' => trim($obj->latitude),
                'longitude' => trim($obj->longitude)

            // {"type":"location","subType":"AIRPORT","name":"HEATHROW","detailedName":"LONDON\/GB:HEATHROW","timeZoneOffset":"+01:00","iataCode":"LHR","geoCode":{"latitude":51.47294,"longitude":-0.45061},"address":{"cityName":"LONDON","cityCode":"LON","countryName":"UNITED KINGDOM","countryCode":"GB","regionCode":"EUROP"},"distance":{"value":57,"unit":"KM"},"analytics":{"flights":{"score":39},"travelers":{"score":45}},"relevance":67.63792}

        return json_encode($airport);

When working on the project we have to overcome two main challenges:

Firstly, the accuracy of data when combining different data sources and the fact that some requests had to be sequential. This potentially could have given poor user experience, reduced usage and the primary objective would have failed.

Secondly, we had to think about limiting the curse of knowledge (a cognitive bias that assumes everyone shares the same background and understanding). Not everyone understands data and even fewer understand CO2 equivalents. To combat this, we allowed users of the tool to compare the data with everyday items that consume energy, such as cooking burgers, bananas, and LED light bulbs.

03 Conclusion

The collaboration between Hardt and AndAnotherDay resulted in the successful development of an application that effectively compared the energy efficiency and speed of hyperloop transportation with conventional transport options. The application provided users with a user-friendly interface and interactive tools to explore and understand the advantages of hyperloop technology. The animated charts, tables, and tooltips enhanced data visualisation, making complex information easily digestible.

Throughout the project, several valuable lessons were learned. Effective collaboration between the development and design teams ensured the seamless integration of functionality and aesthetics. The utilisation of APIs proved instrumental in accessing accurate and up-to-date data for meaningful comparisons. Additionally, incorporating interactive elements, such as animated charts and tooltips, significantly enhanced the user experience and facilitated better data comprehension.

The project’s success demonstrated the effectiveness of collaboration, innovative design, and meticulous development in delivering a valuable tool for promoting sustainable and efficient transportation options.


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