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IET visit the Intelligent Transport Systems (ITS) World Congress

The annual Intelligent Transport Systems (ITS) World Congress was held in Singapore from the 21 -25 October. This event brings together the roads technology industry from across the globe for a huge programme of technical and special interest sessions (including a Joint IET/Department for Transport panel discussion on Learning Lessons From C-ITS Early Adaptors) that discuss everything from national strategy and policy to detailed technology implementation. It also features high level ministerial and city-leader debates that explore the wider issues around ITS.

The ITS World Congress is enormously useful as a means of gauging where technology is going and what challenges are ahead. As the ITS sectors from every corner of the world are represented, it provides a great opportunity to get a wide perspective on what is being worked, what is likely to come to market and what challenges the industry is reacting to.

For the IET, a presence at the World Congress is extremely useful both in terms of allowing the Transport Sector to better understand worldwide developments and to promote the work we are doing in the Transport Sector Committee, the Transport Policy Panel and the TPNs internationally. For the past three Congresses in Montreal, Copenhagen and Singapore, the IET has been represented as part of the UK delegation as has had the opportunity to show it’s thought leadership in this area.

So, what did we learn at the Singapore event? The coming of 5G communications is likely to have a huge impact on the scope and diversity of transport data service in the future;

Finland has built an ecosystem of 5G in different domains, and for transport, this is primarily seen as useful for remotely controlling autonomous small delivery vehicles working in an urban environment and driverless trucks, possibly for slow speed use in terminal areas, etc.

There is a clear role for the engineering community and public authorities in setting the rules, defining the societal goals and working out what is needed to ensure goals are realistic and deliverable. It is the market’s job to determine the best technology solution.

In the USA the opportunity and benefits of 5G is seen as low latency and there is work to develop iterations of Vehicle to Infrastructure (V2I) functionality that specifically utilise this benefit.

A unified connectivity fabric developed by the private and public sectors is needed to ensure the delivery of new services such as enhanced mobile broadband; massive IoT. Ford see connectivity as fundamental to achieving 100% connectivity in the USA, with 100% of vehicle models capable of participating in connected services by 2020 and 100% new models in US equipped with V2I technology starting 2022.

They see cars using 5G as a basis of car to car negotiation, with cars negotiating with each other and forming agreements using blockchain to form ‘contract’ regarding interaction and ‘who goes first’ at intersections and conflict points.

The TM2.0 standard being developed in the EU promises a ‘win-win-win’ for transport users, public authorities and vehicle manufacturers. It focuses on vehicle centred data and how the automated vehicle operates on the road.

TM2.0 aims to use this and be the platform for the optimisation of the transport system using newly available data opportunities. It provides an informed view of the road network that leads to optimisation of traffic management.

In the future, it is envisaged that informal Public-Private Partnerships will be essential for the win-win-win described above to be realised; “Unless there is data quality there is no security and safety”, and open but not necessarily free and accessible data is needed from all sources.

Artificial intelligence is seen as crucial in some areas for ensuring new technologies deliver promised health and safety benefits. In Thailand, traffic deaths are is 5 times more common than fatalities from AIDS and on a par with heart disease. They see traffic accident-related deaths as a major public health crisis.

Using AI to deal with data and treat accident location prediction as a data science problem is helping to meet the political imperative in this area. An approach using AI to make Thai roads safer has been adopted; Accident prediction is based on real-world data including traffic volume and weather, policy evaluation and causal reference.

90% accidents in Bangkok happen in 5% of the road area but the problems are too complex for humans to understand, so it is simplified using AI – this can help reduce field officers’ resources by up to 90%. For every accident, AI needs only 3% of resources to identify its place and time, compared to manual means.

In Nevada in the USA, the ‘Waycare’ initiative is able to reduce crashes and reduce response time through a cloud architecture that allows multiple agencies working in the roads sector to connect.

It gives advanced warning when the system thinks an incident is going to happen, based on real-time data input and it is believed this could lead to a 17% reduction in crashes and a 12-minute reduction in response time, by identifying crashes before they are called in through conventional means and warning other road users more quickly of their presence.

It is also believed that this analysis and prediction tool could result in Highway Patrol Officers being positioned where they are needed more readily and will reduce the amount of CAD (Computer Aided Dispatch) chatter by clarifying what responders should be concentrating on.

Today, we have no shortage of data; the problem lies in ensuring quality is maintained in even larger and more complex data sets. Traffic information for human-controlled vehicles allows for ‘human common-sense check’ before data is acted on but for automated vehicles, the automated algorithms they rely on cannot perform this sense check.

AD (Automated Driving) vehicles have good sensing but cannot see around corners or anticipated in the way humans can and so data provided over infrastructure-to-vehicle services must assist AD vehicles to have this ability to ‘see’ further and discriminate data quality. This can assist ADs to react earlier and also allow occupants of ADs to understand why the vehicle is doing what it is doing, which increases user confidence in ADs.

Los Angeles has identified that on average it is possible for residents to reach 12 times as many jobs by car as public transport. The City sees opening data and the development of a standard platform, known as MDS (the Mobility Data Service) as crucial to re-balancing transport opportunities, dealing with health and inclusion issues and ensuring affordable mobility is available to all. E-Scooters and micro-mobility solutions have appeared, and this gave LADOT the opportunity to test their approach in responding to new disruptive technology.

Now around 80 cities around the work have used MDS and this has led to the formation of the Open Data Forum, linking cities and the private sector together to deliver mobility solutions as a way of solving the problem of public sector working with the private sector fleets operating on our roads. LADOT’s view is that “When the private sector makes private wealth from the public infrastructure, then the public should own the data”.

To build public trust the public sector should never look to monetise the data they own but should be using data and MDS (for example) to develop new business models.