WHITE PAPER

CONVERGING PARALLELS:HOW AUTOMATED VEHICLES AND

DRIVERLESS TRAINS INFLUENCE EACH OTHER

Prepared by:

Rodrigo Álvarez Practice Director, Telecommunications

Rail Systems Australia

Michael Crocker Transit Systems Engineer

Public Transport Authority Western Australia

April 2018

www.railsystemsaustralia.com.au

1. IntroductionRoad vehicles, like most artefacts in today’s world, are becoming increasingly automated. From lane departure warnings to parking assist, driving is slowly being removed from human hands. Vehicles with higher levels of automation are becoming more frequent, and recent advances in technology have seen the arrival of the Automated Vehicle (AV): a vehicle that does not rely on a human driver.

2. Automated VehiclesAccording to the Society of Automotive Engineers [2], the task of driving can be broken into 6 different sub tasks:

1. Lateral vehicle motion control via steering;2. Longitudinal vehicle motion control via

acceleration and deceleration;3. Monitoring the driving environment via

object and event detection, recognition, classification, and response preparation

4. Object and event response execution;5. Manoeuvre planning; and6. Enhancing conspicuity via lighting,

signalling and gesturing, etc.

More broadly, these sub tasks can be thought of as belonging to three different aspects: controlling the vehicle’s motion (sub tasks 1, 2 & 4), situational awareness (3, 4 & 5) and external communication (5 & 6).

Automating the first of these aspects (controlling the vehicle’s motion) is a relatively simple task, and is already present in most modern automobiles, largely in the form of adaptive cruise control or parking assist.

The second is arguably the current focus of the AV industry: from Light Detection and Ranging (LIDAR) systems to visual processing, AVs are making rapid advances in sensing the world around them. High resolution roadmaps are also under development to allow reliable navigation without driver assistance [3]. The third aspect, however, is of a higher order of complexity. As the Chief Technology Officer of Mobileye (Amnon Shashua) states, communication is “the reason we take driving lessons” [3]. Prompts such as brake lights, indicators, hand gestures and horns help drivers send and receive messages to each other, often at speed. Interpreted in the context of the local road rules and customs, drivers can safely and efficiently negotiate the road network.The extent to which an AV system completes the sub tasks mentioned above is described in the SAE J3016 automation levels proposed by the International Transport Forum, as described in Table 1.

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SummaryAutonomous Vehicles (AVs) have gained significant media attention and investment in recent years, with an estimated industry value of $US 77 billion by 2035 [1].

However, many of the future challenges facing the AV industry have largely been experienced by the railway industry, in the form of Automatic Train Control (ATC), Automatic Train Operation (ATO), and related sub systems. Can existing railway systems provide solutions to these problems, and if so, how can railway engineers and organisations tap into this growing market?

This paper highlights the technological similarities between railway networks and the future AV market, focusing on the need for an omnipresent and reliable communications network and protocols to carry safety critical information. Opportunities for shared learnings are identified, and a likely roadmap to the meeting point between the two industries is discussed.

Table 1 - Levels of Automated Driving [2]

How will AVs interpret the signals from others, and how will they signal their own intentions? While AVs will in the short term tend to mimic human drivers (ie interpreting visual clues from traffic lights, and using conventional indicators), the need for such systems should decrease as the penetration rates of AVs increase, since AVs will not need to rely on the same visual clues used by human drivers.

What is more certain is that the AV industry will require a low latency and highly reliable communications network to handle critical information between moving vehicles [4].

3. AV Communication NetworkThe development of communications networks that support AVs sharing information with each other and with their environment are a key element in the path towards fully Automated Vehicles. One of the key actors in that development is the 3rd Generation Partnership Project (3GPP), which is the international standards body responsible for Long Term Evolution (LTE), the mobile communications technology commonly referred to as 4G.

Recently, 3GPP expanded its offering to mission or safety critical users, such as railways, emergency services, and road network operators. This includes a focus on speed and network availability over simple data throughput [5].

The most recent set of standards and technical documents issued by 3GPP (Release 14) includes several Vehicle to Everything (V2X) aspects, including 3GPP Technical Specification (3GPP TS) 22.185. This specification highlights the requirements for the different communication pairs that are required for an AV to function effectively and safely. These are listed in Table 2.

Communication Pair Exmple Message

Vehicle To Vehicle (V2V) “Vehicle A will slow in x metres/seconds”

Vehicle To Infrastructure (V2I)

“Upcoming traffic light at stop”

Vehicle To Network (V2N)

“Crash on upcoming section of road”

Vehicle To Pedestrian (V2P)

“Pedestrian using crosswalk”

These pairs are often generalised to the term V2X. The interactions between the different pairs are highlighted in Figure 1.

Device to Device (D2D) communications, or Vehicular Ad-hoc Networks (VANETs), are spectrally efficient methods to allow intelligent devices to communicating locally over short distances, without requiring resources from the wider network [6,7]. Many V2V, V2I and V2P applications fall into the D2D category, allowing communications to be carried ‘offline’.

3GPP use the term Proximity Services (ProSe) to encapsulate the method for delivering peer D2D messages, without requiring a fixed radio network. Although available since Release 12, ProSe received significant attention in Release 14, and upgrades for the safety critical user could bear fruit for the AV market [8].

However, frequent connections/disconnections and the possibility of broadcast storms may limit the effectiveness of such networks [7]. An omnipresent and stable communications network is likely to continue to be required in high traffic (both vehicular and communications) areas, for efficient message coordination.

V2N communications allow for coordination between many vehicles over longer distances, and without line of sight. Broadcast messages could reduce transmission delays for safety critical messages applicable to multiple users, eg “upcoming crash”. Likewise, general traffic conditions (ie those that can only be sensed in the aggregate) could be broadcast in real-time, improving the overall efficiency of the network [6].

4. Automated… Trains?After discussing AV functions and the mobile communications networks that support them, it is time to turn our attention towards a special subgroup of vehicles that travel over fixed steel tracks rather than asphalt roads.

Surprising as it may be to people outside the rail industry, trains have been travelling the road where AVs are heading for decades. Trains were once driven like cars are driven now, relying on a driver to see the vehicle ahead and to brake before a rear-end collision took place, while visual signals were the basis for traffic flow control. For passenger services in busy lines, that era was over by the 1890s.

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Table 2 - AV Communication Pairs

Figure 1 - Communication Pairs in an AV Network

There were good reasons for that. A braking train, with hundreds – or even thousands, in the case of heavy haul – of tons of inertia behind it, rolling over a nearly frictionless steel wheel over steel rail surface, takes a much longer distance and much more time to come to a complete stop than a rubber wheeled, five-door sedan. Trains also carry more passengers than cars, so the consequences of an individual train-on-train collision were much more dramatic than a single road vehicle accident.

In addition, train ownership was vested in companies and corporations, rather than physical persons. It was therefore politically and economically easier to legally force those railway companies to implement improved safety systems than it is today to force the general car-owning public to make an equivalent investment.

The engineering problems of controlling the movement of a vehicle running on rails were also simpler to solve, due to the limited degree of freedom in the movement of the vehicle itself and to the interfaces between trains and other rail track users. Although it is possible for third parties – pedestrians and road vehicles – outside of a segregated railway to go onto the tracks, it is a relatively rare occurrence, normally limited to level crossing and pedestrian crossing areas.

A less cluttered environment, concentrated vehicle ownership, simpler motion control … all these factors led to a development of train control technologies, starting in the late 19th century with mechanical interlockings, followed by track occupancy detection mechanisms and coloured light lineside signals.

Advances in electronics and computer design gave birth in the late 20th century to new Mass

Transit train control systems. The first of these new systems may have been the Automatic Train Operation (ATO) system deployed on Barcelona Metro Line 2 and on London Underground Victoria Line in the early 1960s, but they were soon followed by more sophisticated systems.

5. Driverless Train PrinciplesSeveral of those ‘sophisticated’ driverless train systems exist in the current market. Most of them fall under the umbrella of the IEEE 1474 standard [9] and can therefore be labelled Communications-Based Train Control (CBTC) systems.

As shown by Figure 2 below, CBTC works through the continuous exchange of information between on board equipment and wayside equipment. The On-Board Controller (OBC), composed of (A) an on-board Automatic Train Operation (ATO) function and (B) an on board Automatic Train Protection (ATP) function uses the location information provided by wayside beacons (C) to transmit position and status update messages to the wayside. Those messages are sent via the On-Board Data Radio (D), which connects to the wayside Data Communications Network (E) and reach the wayside Zone Controller (F). Train location will then be reported to the Automatic Train Supervision (ATS) system and to the human Train Controllers located in the Operations Centre (G).

The wayside system also sends messages back to the train, following the same route from (G) and (F) back to (A) and (B). These messages provide a movement authority, telling the on-board system how far and how fast it can safely continue before needing to stop.

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Figure 2 - CBTC Working Principle - On Board to Wayside

Through the exchange of messages with wayside subsystems described above, the OBC fulfils the following functions to safely control the speed of the train:

• Enforce speed limitations• Identify position via beacons• Accelerate to optimal speed• Know track gradients and curves• Accurately calculate travelled distance

These train operation functions are similar to the AV sub tasks described in Section 2.

The degree of automation in executing these functions can be categorised into types of train operation that are similar to the SAE Levels of Automated Driving described in Section 2. Table 3 summarises the description of the types of train operation and links them to defined Grades of Automation according to the International Association of Public Transport (UITP), which defines train operation types as on-sight, manual operation, Semi-automatic Train Operation (STO), Driverless Train Operation (DTO) and Unattended Train Operation (UTO).

6. Train-Centric CBTC SystemsWhile conventional CBTC systems still rely heavily upon wayside infrastructure and central control to coordinate rail traffic and ensure safe separation of vehicles, newer Train-Centric CBTC systems transfer these tasks to the trains themselves[10]. These systems place high importance on V2V communications, and less on a fixed network.

Traditional CBTC suppliers are developing or already offer these kinds of systems, such as Astom’s Urbalis Fluence, which is a driverless UTO (GoA 4) system currently being deployed in the Lille (France) Metropole Light Rail network, or other train-centric CBTC systems being proposed by Hitachi and Thales.

The concept behind Train-Centric CBTC systems is moving several of the ATO functions from the wayside to the on-board system, as shown in Figure 3

In a Train-Centric CBTC system, each train independently negotiates access to track infrastructure such as switches, crossings, road level crossings and road traffic signals by sending direct requests to Object Controllers, without using the ATS and Interlocking functions. This is equivalent to the AV V2I functionality.

Also, train protection is achieved by train-to-train communications, where each train issues location reports to all nearby trains, which then use this information to independently calculate their Limit of Authority. This is equivalent to V2V communication in AV operation.

It would therefore seem that Train-Centric CBTC is virtually equivalent to an Automated Vehicle. There is still one fundamental difference, however, with regards to the interface with other road traffic – the Lille system will still be a highly segregated system, without the real need to consider extraneous vehicles.

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Grade of Automation

Type of Train

Operation

Setting Train in Motion

Stopping Train

Door Closure

Operation during

Disruption

GoA 0

GoA 1

GoA 2

GoA 3

GoA 4

On Sight

No ATO

STO

DTO

UTO

Driver

Driver

Automatic

Automatic

Automatic

Driver

Driver

Automatic

Automatic

Automatic

Attendant

Automatic

Driver/Attendant

Driver/Attendant

Driver/Attendant

Attendant

Automatic

Driver/Attendant

Driver/Attendant

Driver/Attendant

Table 3 - CBTC Grades of Automation

Figure 3 - Wayside-Cenrtric vs Train-Centric CBTC

It is also interesting to see the advantages identified the proponents of Train-Centric CBTC systems themselves. According to Alstom, Urbalis Fluence will be cheaper, simpler to install and with reduced headways when compared to traditional CBTC systems. The industry uptake of these systems, however, is still very limited, given that Train-Centric CBTC systems are relatively new.

7. CBTC Radio Bearer EvolutionThe previous sections make it evident that the radio system that supports train to wayside communications is critical for an adequate driver-less train operation.

To provide train to wayside communications, the earliest ATO systems used either near-field induction loops in the four-foot transmitting information to antennas mounted under the train, or a leaky waveguide mounted on the track side transmitting to antennas on the side of the train.Induction loops and waveguides, however, presented important drawbacks, with its most pressing problem being capacity. High capacity ATO systems require continuous train-to-wayside communications not linked to limitations in physical infrastructure.

In the early 1990s, the industry started to use radio to support train to wayside communications. Initially, each proprietary CBTC system was designed to use a bespoke radio system to conduct train to wayside communication. These proprietary radios proved very expensive to install, operate and maintain.

In 2004, Alcatel (now Thales) decided to use a standard IEEE 802.11 Wi-Fi data radio to support its SelTrac CBTC system. This choice brought many advantages: cheap, Commercially Off-The-Shelf (COTS) radio units, interoperability amongst different Wi-Fi suppliers, and open standard Layer 2 and 3 communications protocols (TCP, UDP and IP), with a very large pool of available expertise.By 2010, all CBTC suppliers had produced Wi-Fi versions of their CBTC products, and these constitute the standard offering in current CBTC deployments.

8. AV Radio Bearer EvolutionIn parallel with CBTC systems, the Automated Vehicles community is concentrating its efforts on two radio systems to support V2X communications.

The first system, called Dedicated Short-Range Communication (DSRC), is based on the Orthogonal Frequency Division Multiple Access (OFDMA)

physical layer described by standard IEEE 802.1a, while using a IEEE 802.11e Enhanced Distributed Channel Access (EDCA) MAC sublayer [11].

As a Wi-Fi based radio bearer, however, DSRC has proved to present some problems. The IEEE 802.11 protocols present important inherent limitations with regards to range, mobility, radio resource access, quality of service and interference management that pose significant issues to mobile mission critical applications [12].

To address those issues, the industry has developed a newer system for V2V/V2I data transmission that constitutes the next generation after DSRC. This system is known as Wireless Access to Vehicular Environment (WAVE). WAVE is based on the IEEE 802.11p and IEEE 1609.x standards, to avoid the interference problems associated with the unlicensed spectrum bands used by conventional Wi-Fi, WAVE operates on the 5.850 - 5.9250 GHz band, delivering between 3 and 27 Mb/s (with a bandwidth of 10 MHz), and between 6 and 54 Mb/s (with a bandwidth of 20 MHz).

To cope with Wi-Fi’s mobility problems, WAVE’s omnidirectional range is around 1,000 m, well in excess of typical 802.11 ranges of 100s of meters range, and useful data throughput values can be obtained at speeds up to 110 km/h [11].

WAVE, as a bespoke 802.11 application, is better suited to support AV communication requirements than DSRC was. However, this solution presents an interesting parallelism with the radio systems that support driverless train applications.

9. Radio Bearer ComparisonJust like DSRC and WAVE, CBTC started using conventional IEEE 802.11 standards. The first CBTC applications to make use of a Wi-Fi radio bearer network were in fact based on the 802.11b protocol, moving later to 802.11g and its OFDMA encoding.

At that point in time, however, CBTC suppliers tried to solve some of the mobility and resource allocation problems inherent to 802.11 networks by adding to each proprietary CBTC application a transmission management layer that could handle the limitations of Wi-Fi.

Some of these techniques included the use of up to four simultaneous on-board data radio units to handle the handover between wayside Wi-Fi access points.

Effectively, trains are long enough to have the data radios in the front cab connected to one access point while the data radios in the rear cab are

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connected to the previous access point. The CBTC application then transmits through whichever radios are connected at any given time, while the other radios complete their roaming process to a new access point. The AV case will present some limitations to this technique since road vehicles are shorter and the distances between roadside access points will be longer.

Another technique introduced by the CBTC radio management layer is the allocation of radio resources by negotiating transmission times between CBTC fitted trains in an area, to avoid Wi-Fi packet collision detection and avoidance. This feature could also be delivered in V2V/V2I networks, to improve Quality of Service.

Unfortunately, all these additional mechanisms mean that CBTC applications and the Wi-Fi radio that support them have now become bespoke systems like the ones that predated Wi-Fi and suffer from the same operational and maintenance problems. Replacing Wi-Fi radios is no longer a COTS like-for-like exercise if it involves modifying the CBTC application. The same limitation has occurred in AV systems with the change from DSRC to WAVE, mitigated by the economies of scale introduced by the potential sheer number of AV radio devices.

The limitations inherent to IEEE 802.11 protocols have been pushing the CBTC industry to search for alternatives. The industry is now transitioning to 3GPP LTE mobile technology, with at least four independent trials between different CBTC and LTE products having taken place since 2014, and with the first operational implementations of CBTC over LTE systems already being installed at the time of issue of this paper. Interestingly, LTE is also evolving to capture the one area where 802.11p could arguably be superior: short range ad-hoc networks. As discussed in section 3 above, Proximity Services (ProSe) features have been built into the latest LTE releases and it is expected that, in the next few years, LTE networks will support direct D2D communications.

Will WAVE and 802.11p follow the same path CBTC Wi-Fi systems are following? Or will the significant commercial differences between the AV and the CBTC markets play a role in casting a different fate for WAVE?

10. Meeting in the Middle: AutomatedBuses and Light Rail

10.1 Automated BusesLike railways, high volume bus routes often utilise exclusive infrastructure such as busways or lanes. Segregated from the general traffic and travelling along a fixed route, the number of potential obstacles (and hence the required complexity of automation solutions) is greatly reduced.

At the time of writing, bus operators and manufacturers had shown little interest in the prospect of automated buses, particularly when compared to private automated vehicles [13]. This is reflected in the relative efforts and expenditure of the market.

However, as both the capital and ongoing costs of bus operations are significantly higher than for a private passenger vehicle, bus operators are more likely to be willing to absorb the cost for higher levels of automation. Many public transport operators maintain both rail and bus networks, so inhouse signalling and control systems expertise is generally available.

Automated buses have already been trialled in Australia. The RACWA in conjunction with the Western Australian State Government have conducted on road trials with a Navya bus in South Perth since September 2016. Curtin University has likewise begun trialling a driverless bus, carrying out a campus shuttle role.Similar trials have been launched in other countries, including Greece, Spain, Switzerland, USA & UK [13].

10.2 Automated Light RailDriverless light rail systems already exist, most notably the Docklands Light Railway (DLR) in London, where staffing levels are lower than in comparable railway systems. DLR operates in a largely segregated right of way, which reduces the complexity of the system.

Automating light rail systems operating in mixed traffic[14] (ie on surface streets, interacting with cars and pedestrians) pose a greater challenge, although steps are being taken to accomplish this. Bombardier has developed a driver assistance system that scans the vehicle’s upcoming swept path for obstacles and warns the driver of a potential collision. The next logical step is to use this technology for an ATP type application, which is under development [15].

Considering the investments being made by the AV industry in obstacle detection, leveraging these technologies for the railway industry could prove to be a cost-efficient mechanism for ATC in light rail vehicles in mixed traffic.

As the wheels-on-rails system reduces the complexity of the possible network, it could represent a useful proof of concept for AV network systems.

Combined with a train-centric CBTC solution, there is potential for a GoA 4 or higher solution operating in a mixed environment, and which requires little interaction with wayside infrastructure.

This solution would be largely applicable to both rail and road networks and could represent a launch pad for rail-based signalling and communications organisations to enter the automated vehicle market.

11. ConclusionDespite the hype of novelty surrounding Automated Vehicles, the railway industry has been quietly solving the issues of automatic control for decades. CBTC (particularly train-centric systems) already undertake many of the responsibilities that supposedly pose challenges for the AV industry.

Thus, the railway system engineer is in the position of being able to bring some relevant experience to an industry where most are novices. At a predicted market value of $US77 billion in 2035[1], the opportunities for railway system engineers look bright.

As the AV industry matures, the similarities to the railway industry will strengthen, and many systems and applications will likely become transferrable. A reliable mechanism for safe separation of vehicles, and the omnipresent communications network to support this are two such examples of this. A variety of communications protocols are being developed to support this need, and development will likely follow the path of CBTC Communications from 802.11 to LTE.

The confluence of the two industries is most likely to occur at the development of the automated bus or light rail vehicle, both of which are making progress towards full automation.

12. Referees1. Autonomous Vehicle Adoption Study [Internet]. https://

www.bcg.com. 2017 [cited 25 September 2017]. Available from: https://www.bcg.com/industries/automotive/autonomous-vehicle-adoption-study.aspx

2. Society of Automotive Engineers. Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles [Internet]. SAE International; 2016. Available from: http://standards.sae.org/j3016_201609/

3. Gurdus, E., The 3 basic elements to building self-driving cars [Internet]. CNBC. 2017 [cited 30 September 2017]. Available from: https://www.cnbc.com/2017/01/05/the-3-basic-elements-to-building-self-driving-cars.html

4. Hameed Mir, Z., Filali, F., LTE and IEEE 802.11p for vehicular networking: a performance evaluation. EURASIP Journal on Wireless Communications and Networking. 2014;2014(1).

5. Alvarez, R., Crocker, M., The VoLTE edge: mission-critical voice over LTE. CORE 2016, Maintaining the Momentum, Conference on Railway Excellence. Melbourne: Railway Technical Society of Australasia; 2016.

6. The Case for Cellular V2X for Safety and Cooperative Driving [Internet]. 5GAA; 2016 [cited 25 September 2017]. Available from: http://www.5gaa.org/pdfs /5GAA-whi tepaper-23-Nov-2016 .pdf

7. Ucar, S., Ergen, SC., Ozkasap, O., 2016. Multihop-Cluster-Based IEEE 802.11p and LTE Hybrid Architecture for VANET Safety Message Dissemination. IEEE Transactions on Vehicular Technology. 65(4), 2621-2636.

8. Gallo, L., Haerri, J., Unsupervised Long- Term Evolution Device-to-Device: A Case Study for Safety-Critical V2X Communications. IEEE Vehicular Technology Magazine. 2017;12(2):69-77.

9. The Institute of Electrical and Electronics Engineers, Inc. IEEE Standard for Communications-Based Train Control (CBTC) Performance and Functional Requirements [Internet]. New York: IEEE; 2004. Available from: https://standards.ieee.org/f indstds/standard/1474.1-2004.html

10. Ali, N., CBTC 2.0: Vehicle Centric Architecture & Train to Train Communication. CBTC Seminar [Internet]. Toronto: Institution of Railway Signal Engineers; 2016 [cited 21 October 2017]. Available from: http://www.irse.org/knowledge/publicdocuments/IRSE%20C B TC % 2 0 C o n f e re n ce % 2 0 % 2 0 - % 2 0 2 0 1 6 % 2 0Toronto%20%20Naeem_Al i_CBTC2_Rev05.pdf

11. Perallos, A., Hernandez-Jayo, U., Onieva, E., Garcia Zuazola, I., Aguiriano, N., Intelligent Transport Systems: Technologies and Applications. John Wiley & Sons, Inc. 2016.

12. Alvarez, R., CBTC over WI-FI: gathering clouds. AusRAIL PLUS 2014, Making Innovation Work [Internet]. Perth: Australasian Railway Association; 2014 [cited 16 October 2017].

13. Pressaro, B., Evaluation of Automated Vehicle Technology for Transit - 2016 Update [Internet]. Tampa: National Center for Transit Research; 2017. Available from: https://www.nctr.usf.edu/2016/04/evaluation-of-automated-vehic le-technology-for-transi t-2016-update/

14. Vuchic, V., Urban transit systems and technology. Hoboken, N.J.: John Wiley & Sons; 2007.

15. Robinson, A., Driver Assistance System for Avoidance of Collision on Light Rail Vehicles. CORE 2016: Maintaining the Momentum. Melbourne:

Railway Technical Society of Australasia; 2016.

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7. About the AuthorsMr Rodrigo ÁlvarezRail Systems AustraliaRodrigo has been involved in railway communications in Australia, the UK and Europe with a career spanning over 12 years. His comprehensive experience extends to railway radio communications deployment projects, the integration of advanced railway signalling systems and communications technologies and the design and implementation of railway fixed communications networks. He is one of a small number of Engineers in Australia with experience in the design of GSM-R and ERTMS systems, as well as LTE, SDH and Carrier Ethernet networks.

Mr Michael CrockerPublic Transport AuthorityPrior to joining the PTA’s Radio System Replacement (RSR) project team in 2015, Michael was involved in strategic planning for the future railway and bus networks in Perth, including the Forrestfield-Airport Link, East Wanneroo Rail Link and Level Crossing Removal projects.

Subsequently, Michael joined the core team delivering the Perth and Peel Transport Plan for 3.5 million people and beyond. The resulting suite of strategic documents laid out Perth’s transport needs and integrated passenger heavy and light rail, bus, automobile freight and active transport networks. A key aspect of this was the consideration of AVs and ATC on the overall transport network.

After an intermediate period in SCADA and control systems, Michael re-joined the RSR project in 2017 where he is part of a team working to deliver a leading-edge 4G network with MCPTT and MCData capabilities.

About Rail Systems Australia

Rail Systems Australia is an independent Australian rail engineering practice providing rail operators and their partners with trusted advice. We deliver innovative, safe and reliable solutions through the integration of communications, signalling, automatic train control and asset management.

Backed by a proud record of delivery, we are committed to lead the Australian rail industry in the adoption of technology and innovation to steer through complexity.

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Disclaimer The author only represents himself as competent professional in the planning, design and implementation of Telecommunications and Information Technology systems, networks and practice. Any statement provided which may be of a legal nature is only offered as an opinion based on the author’s understanding of the law and how it may apply. The author has made every effort to identify all relevant and available source data in the preparation of this document. All surveys, forecasts, projections and recommendations are made in good faith on the basis of information available at the time. The author, its agents, licensee and/or other representatives disclaims any liability for loss of damage caused by errors or omissions, whether such errors or omissions resulted from negligence, accident or other causes. Neither the author, its agents, licensee nor representatives wil be liable for any loss or other consequences (whether or not due to the negligence of the author or their agents) arising out of the use of information in this report. No responsibility is taken for the accuracy of this information in relation to pricing or functionality of products and services described in this report. Readers should confirm with the appropriate service provider as to the validity of the information and any variations which may have taken place since publishing.

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