Technical – Cooperative Intelligent Transport Systems Research within the AIMES Environment APAC-21-126

Ada Lin1,*

1 New Business Solutions, Lexus Australia, 155 Bertie St. Port Melbourne VIC 3127 * Corresponding author: ada.lin@toyota.com.au

Cooperative Intelligent Transport Systems Research within the AIMES

Environment APAC-21-126

1. Introduction

Each year more than 1,100 road users lose their lives across Australia, and around 40,000 are admitted to hospital. Innovative approaches to road rule enforcement, driver behaviour, driver assistance, vehicle design and road design have reduced the harm caused by road crashes, particularly those of high severity. Many countermeasures have addressed the protection of vehicle occupants and, more recently, the avoidance of crashes. The rollout of technologies that sense and ameliorate imminent crash risks is now receiving considerable attention with the advent of advanced sensing, connectivity and automation. Cooperative Intelligent Transport Systems (C-ITS) allow vehicles to communicate with roadside infrastructure through vehicle-to-infrastructure (V2I), with a cloud-based central facility through vehicle-tonetwork (V2N) and with other vehicles through vehicle-to-vehicle (V2V), communications. Based on C-ITS messages exchanged, drivers are presented with safety alerts about immediate and upcoming hazards (Figure 1). C-ITS increase the drivers’ situational awareness to put them in the best position to react to safety risks. Austroads found that if C-ITS technology was deployed in Australia at scale, a reduction in fatalities of up to 23% and injuries of 28% could potentially be achieved [1]. Production vehicles have been equipped with C-ITS in markets such as Japan since October 2015. Toyota/Lexus has sold more than 250,000 vehicles across 19 models (as of September 2021) equipped with C-ITS technology - “ITS Connect”. A 2019 survey of ITS Connect customers indicated that over 70% of them found it helpful, especially where line-of-sight was obscured [2]. Australian Integrated Multimodal EcoSystem (AIMES) is a real-world platform for testing and demonstrating emerging connected transport technologies in complex urban environments in Carlton, Victoria. It incorporates over 100 kilometres of Melbourne road network, where partner organisations have been installing diverse technologies for sensing, connecting, visualising and analysing mobility systems since 2015. In 2021, Lexus Australia developed and evaluated C-ITS safety applications (also called use cases) in the AIMES precinct to study the effectiveness of applying C-ITS in Australia.

2. AIMES Use Cases

For AIMES, the following V2I/V2N use cases were verified: • Advanced Red-Light Warning (ARLW): alerts drivers to a risk of a red-light signal violation unless they apply the brakes • Turn Warning Vulnerable Road User

ABSTRACT

AIMES ecosystem provides a real-world platform for collaborative trials based on the streets of Melbourne to test integrated transport technology to deliver safer, cleaner and more sustainable urban transport outcomes. Lexus Australia conducted Cooperative Intelligent Transport Systems (C-ITS) research within the AIMES ecosystem, including the development and demonstration of vehicle-to-infrastructure (V2I), vehicleto-network (V2N) and vehicle-to-vehicle (V2V) safety applications (also called use cases). V2I safety applications involve direct communication between C-ITS vehicles and roadside units that broadcast live signal status and road geometry information of the intersections to alert drivers to the risk of violating red-light signal and running into pedestrians/cyclists crossing during the permitted phase. V2N safety applications include long-range communications with a cloud-based central facility to alert drivers to road hazards, traffic jams, and roadworks and provide drivers with information about static or variable speed limits. The extension of V2V on communication with emergency service vehicles and public transport vehicles allows sharing of awareness messages between different vehicle types. Notifying drivers of the stationary and approaching emergency service vehicles can assist in avoiding collisions and shorten travel time for ambulances. Tram awareness alerts and tram passenger warnings can potentially mitigate vehicle collisions with trams and passengers, enhancing public transportation’s efficiency and safety. This paper discusses the importance, design and evaluation of C-ITS use cases in AIMES and highlights key findings and next steps for C-ITS deployment in Australia. KEYWORDS: Cooperative Intelligent Transport Systems; Connected Vehicles; C-ITS Safety Applications (Use Cases).

Figure 3. ARLW System Architecture

Figure 4. Live SPaTEM and ALRW (Left) / TWVR (Right) Alerts

(TWVR): alerts drivers to a pedestrian crossing during the permitted phase • Road Hazard Warning (RHW): alerts drivers to hazards, such as debris or water on the road or a crash • Back-of-Queue Warning (BoQ): alerts drivers to a traffic jam • Roadworks Warning (RWW): notifies drivers approaching or driving through roadworks zones, providing speed limit • In-Vehicle Speed (IVS): provides drivers with information about static or variable speed limits. The following V2V use cases, which enabled communication with emergency service vehicles and public transport vehicles, were newly developed and evaluated: • Emergency Service Vehicle Notification (ESVN): notifies on the direction of the approaching emergency vehicle and instructs drivers to comply with regulatory

speed when approaching a stationary emergency vehicle in action • Tram Awareness Alert (TAA) and Tram

Passenger Warning (TPW): alert drivers on approaching trams and passenger disembarkation/embarkation status.

Figure 2. RSU Installation at Gertrude/Nicholson Intersection

3. Live Traffic Signal Status Integration

The Carlton testbed was set up in cooperation with AIMES stakeholders to enable V2I/V2N use cases. A roadside unit (RSU) was installed at the southern end of the intersection (Figure 2) to allow the transmission of intersection geometry information (map) and traffic light signal status via ITS-G5 (Figure 3). For testing, the use case parameters were configured to be very conservative so that alerts could be triggered at greater distances from the intersection at low vehicle speeds. Therefore, how the different factors impact the use case timing and accuracy could be investigated whilst ensuring the safety of testers and other road users. However, this would be changed to avoid triggering warnings unnecessarily in a more realistic driving scenario. ALRW and TWVR alerts were successfully triggered according to the Signal Phase and Timing Extended Message (SPaTEM) broadcasted by RSU. The broadcasted SPaTEMs were in sync with the actual status of the traffic light (Figure 4) that integrated with the Sydney Coordinated Adaptive Traffic System (SCATS) (Figure 5). SCATS adapts traffic signal timing in real-time to match the traffic conditions, installed in over 55,000 intersections across 187 cities and 28 countries worldwide [3]. In Australia, there are 15,169 SCATS intersections (as of May 2022). Whilst more testing and detailed analysis are still underway, the latency for delivering signal status information into the vehicle was obserbed to be negligible. Other factors, such as communicaiton range of the RSU (Appendix A) and vehicle positioning accuracy (Section 6) can also affect the relevece of the driver alerts. Most recently (September 2022), integration and testing of two more SCATS intersections along Victoria Parade for C-ITS applications were commissioned. For widespread deployment of SCATS integration for C-ITS applications in Australia and beyond, system compatibility and rollout plan shall be investigated further.

4. Emergency Service Vehicle

Notification (ESVN)

4.1 Importance of ESVN

Ambulance Victoria (AV) provides emergency medical response for over 5.8 million people across the state. AV has a fleet approaching 1500 vehicles and, in 2021, travelled more than 40 million kilometres responding to over a million cases. In the year 2020-2021, there were 801,984 Triple Zero (000) calls for assistance; more than 80% required emergency response on-road, and others by air [4]. The ambulance response is progressively increasing over the years (Figure 6). Responding to time-critical emergency cases brings a much higher risk of motor vehicle crashes. That risk is elevated in metropolitan areas where it becomes necessary to cross multiple intersections. Reports on incidents have shown that other road users neither hear nor see the approaching ambulance. Improving public awareness of emergency vehicles to shorten emergency response time has become necessary. Providing in-vehicle warning of an emergency vehicle approaching would encourage the drivers to give way. In Victoria, Road Safety Road Rule, Part-7, Division-4, Rule 79A [5] states that vehicles should not exceed 40km/h when passing emergency vehicles that are stationary or moving slowly (less than 10km/h). The road rule aims to ensure the safety of emergency service workers performing work on the

Figure 7. ESVN Use Cases

road or roadside and others at the scene [6]. Providing in-vehicle warning of approaching a slow or stationary emergency service vehicle and instructing speed reduction to regulated speed is intended to encourage the drivers to comply with the road rule.

4.2 ESVN Use Cases

For vehicle communication with emergency service vehicles, two different use cases were implemented and evaluated (Figure 7). Both targeted to improve the efficiency of ambulance service and increase the safety of the personnel and assets of emergency services: • Emergency Service Vehicle Awareness

Alert: the driver is notified about approaching an emergency service vehicle (ESV) with an active lightbar with its distance and direction. • Emergency Service Vehicle Slow-Down

Alert: the driver is instructed to reduce speed to 40km/h when approaching a slow/stationary ESV on active duty (with lightbar ON)

4.3 ESVN System Setup

Enabling ESVN involved mounting the onboard unit (OBU), the device to enable the vehicleto-vehicle communications, on the roof of ambulance and Lexus vehicles (Figure 8).

Direct vehicle-to-vehicle communication relies on Dedicated Short-Range Communication (DSRC) ITS-G5, a standard C-ITS communication protocol defined by the European Telecommunications Standards Institute (ETSI). Vehicles periodically exchange their status using Cooperative Awareness Message (CAM), which includes parameters such as location, speed, direction, heading and role of the vehicle. In the case of special vehicles such as emergency service vehicles, lightbar and siren information is also a part of CAM. The ambulance lightbar 12V-DC signal was converted to a digital signal and fully integrated with the OBU. For Lexus vehicles, the safety alerts are presented to the driver via a Human-Machine Interface (HMI) with visual warnings (display an icon with the distance between the vehicle and ESV) and audio warnings (in human speech, such as “Caution! Approaching emergency service vehicle. Reduce speed to 40km/h”). The warning configuration was appropriate without causing driver distraction (Figure 9). Visual warning with distance information and audio warning with directional information in a human speech made the warning contextual and relevant, keeping the drivers’ focus on the road.

4.4 ESVN System Evaluation

To study the effect of ESVN in the real-world environment, different scenarios, including vehicles approaching each other from different streets and the stationary ambulance scenario, were evaluated. The directional tests (Figure 10) indicated that the directional alerts with human speech ensured that the driver paid attention to the road and promoted direction. With the tuned parameters that consider driver reaction time and vehicle braking capacity, the alerts were timely and precise, with sufficient time for the driver to react. The stationary ESV test (Figure 11) indicated that when the vehicle was travelling at different speeds, the alert was triggered based on the speed and distance to the stationary ambulance (Appendix B). The driver had enough time to safely reduce the speed to the regulatory limit of 40km/h before passing the ESV to ensure the safety of the emergency service personnel working on the road or roadside. ESVN demonstrated a significant increase in situational awareness amongst the vehicle drivers. As a result, this could allow the ESV to provide a quicker emergency response by travelling more smoothly in live traffic and reducing incidents involving them. Therefore, ESVN allows for a safer and more efficient working environment for emergency services.

Figure 8. ESVN System Architecture

Figure 9. Example ESVN driver alerts – ESV on the left Figure 10. ESV Awareness Alert

Figure 11. Approaching a Slow/Stopped ESV

5. Vehicle Communication with Public

Transport

5.1 Importance of Vehicle Communication with

Trams

Melbourne’s tram network is one of the key public transport systems in the city, and it is the largest in the world, with 250km of double track and over 400 trams of various types in service on a typical weekday and annual pre-covid patronage of around 200 million boardings a year. Over 70% of the network is shared with other road users. 80% of injuries on public transport in Victoria in 2018 occurred on the tram network. Yarra Trams reported more than 1,100 vehicle-totram collisions (97% of the collisions were the fault of motorists) in 2018 [7]. Around 70% of vehicle collisions are due to vehicles merging

Figure 13. TAA (top) and TPW (bottom) Use Cases

midblock or U-turning in front of a tram. These collisions can result in severe damage to the vehicles and severe injuries to the road users (Figure 12). In addition, vehicle-to-passenger collisions, in which vehicles pass stationary trams while passengers are boarding or getting off the tram, pose a significant risk. From 1st July 2014 to 30th June 2019, there were 128 passengers knocked down, some resulting in severe injuries that required emergency response [9]. Enabling trams to communicate with surrounding vehicles to alert drivers of approaching trams and passenger disembarkation/ embarkation status can potentially mitigate vehicle collisions with both trams and passengers, hence enhancing the efficiency and safety of public transportation.

5.2 Tram Awareness Alert (TAA) and Tram

Passenger Warning (TPW) Use Cases

TAA alerts the driver when the vehicle is turning across the tram tracks while a tram is approaching from behind (Figure 13) under the following conditions: 1. the turn indicator signal is active, which can be determined by monitoring internal vehicle signals or 2. the vehicle is in a dedicated-turn lane,

which is determined by comparing the vehicle’s location with map content containing road geometry and lane configuration. TPW alerts the driver when the vehicle is approaching a stationary tram at a tram stop, where passengers are disembarking or embarking (Figure 13, bottom). For this trial, whether the tram is currently disembarking or embarking passengers is determined based on the status of tram doors (open or closed).

5.3 TAA and TPW System Setup

The two applications are primarily based on vehicle-to-vehicle communication via ITS-G5. As shown in Figure 14, the tram broadcasts a Cooperative Awareness Message (CAM), including location, heading and speed information, and embarkationStatus field (based on information about the door status). The map containing road geometry and lane configuration information is delivered through Map Data Extended Messages (MAPEM) via ITS-G5 from a roadside station or cellular connection from a cloud-based central facility. This project benefitted from an earlier project funded by the Victorian Government Department of Transport under the Smarter Journeys Program [10] in 2018, where 29 B-class trams were equipped with OBUs. The existing CAM was updated with an additional data field to show the embarkation status in the tram. Lexus vehicles are equipped with OBUs to compute the use case algorithms. The driver awareness alerts were presented via the human-machine interface (HMI) (). For TAA, the visual warning is presented with t audio alert “Tram approaching”. For TPW, the visual alert, including the distance between the tram and the vehicle, is displayed with an audio alert, “Caution, pedestrians”, being played.

5.4 TAA and TPW System Evaluation

The dedicated and structured testing of all applications and scenarios was done during a night testing activity outside of regular tram operating hours, which meant trams could freely move on tracks based

Figure 15. TAA and TPW Driver Alerts

Figure 16. Vehicle/Tram Night-Time Test at Lygon Street

on the test scenarios. In addition, the test area was partially closed off to traffic to enable tram and test vehicle movement in a safe environment and without interference from other traffic participants. The test was conducted from 1 AM to 4 AM on 7th December 2021 on Lygon Street in Melbourne. Figure 16 shows the closed stretch of road shaded in green. The intersection of Lygon St / Princes St was used for some limited testing but not closed to other traffic. Following test scenarios were executed during the TAA evaluation:

Figure 17. Demonstration of Tram Awareness Alerts

Figure 18. Green signal phase for both tram and vehicles

Figure 19. Demonstration of Tram Passenger Warning

1. The vehicle activates the right indicator while a tram is approaching from the rear of the vehicle in a neighbouring lane (Figure 17, left) 2. The vehicle enters a dedicated right-turn lane while a tram is approaching from the rear in a neighbouring lane (Figure 17, right). Both TAA scenarios were successfully triggered (pink paddles). In this particular test of the vehicle travelling in the right-turn lane, the alert was triggered very early (~150m from the intersection stop bar) where the right turn was not yet possible. In the future, improvement in only showing an alert at a certain distance to the stop bar of the lane based on the vehicle speed can be considered to avoid unnecessarily early warnings. This use case can also be particularly useful for the area where both signals for vehicles and trams can be green simultaneously. For example, at the Lygon St / Princes St intersection (Figure 18) used for this testing, a right-turning vehicle still needs to give way to a tram approaching from behind even though it has a green signal. The tram passenger warning was successfully triggered when the vehicle approached a stationary tram with its doors open. Figure 19 shows an example of the alert being triggered (shown with red “P” paddles). This application improves the safety of tram passengers when cars and trams are in shared lanes. However, relying solely on the door status to trigger an alert could be too late for a vehicle to stop behind the tram. For future improvement, some foresight into the intention of the tram and its passengers could be useful. This could be achieved by developing a new signal for a boarding passenger or a passenger stop request to set the embarkationStatus field, which should also be crosschecked in the vehicle to the tram location and nearest tram stop to provide relevant alerts. The successful development and evaluation of TAA and TPW is a big step towards safer roads where public transport and cars are mixed. It not only helps drivers conform to local road rules but can avoid vehicle-to-tram and vehicleto-passenger collisions.

6. Challenge in Vehicle Positioning

Accuracy

C-ITS vehicle uses positioning technology to compute vehicle trajectory (location, speed, and heading), compare it to the location of traffic events and map information, and carry out threat assessment to generate driver safety alerts. Specifically for intersection related use cases, positioning accuracy is critical, as the vehicle needs to determine which lane it is located. Positioning data was acquired using a dedicated positioning system, which utilises satellite navigation data from multiple global navigation satellite systems (GNSS) and further enhanced with corrections from nearby ground reference stations provided through a Real-Time Kinematic (RTK) service (Figure 3). The positioning quality is affected by any obstruction to the vehicles’ view of the sky and connection to satellites. As shown in Figure 20, different positioning accuracy (RTK modes) are represented with coloured dots: Green (with RTK fixed, correction is applied with optimal results and high confidence), Yellow (RTK float, correction is applied, but the confidence of the correction is not as high) and Red (GNSS only). There were differences in the positioning quality at different approaches when driving through the intersection.

Figure 20. Nicholson St Southbound (Top)/ Northbound (Bottom) Positioning Accuracy

For Nicholson St southbound approach, closer to the intersection, the positioning mode is mainly RTK fixed, where the alerts were triggered correctly. However, tree growth on the Carlton Gardens side of the road for the northbound approach obscures a large sky area and prevents satellite signal acquisition. The positioning system repeatedly switches between different modes, decreasing positioning accuracy and preventing relevant and accurate warning triggers (shown with yellow paddles). For all C-ITS use cases, system limitations related to the positioning accuracy (Appendix C) of the vehicles can affect the quality of the driver alerts.

7. Conclusion and Next Steps

AIMES offered exciting opportunities to investigate the requirements for the largescale deployment of C-ITS technologies. The integration of roadside infrastructure with live SPaTEM, V2I/V2N in the AIMES precinct, and reliable V2V communication with emergency service public transport vehicles allowed all C-ITS use cases to be verified successfully. This demonstrated an increase in situational awareness amongst vehicle drivers and strong collaboration between governments, industry stakeholders, public service and academic sectors to form the base for a significant step towards safer roads where multi-modal transport and road users are mixed. Positioning and mapping are essential factors for C-ITS technology, and there should be further studies in these areas. By seeking to integrate real-life traffic events such as live traffic light status and traffic status, all stakeholders have recognised the need for robust, meaningful and current data streams to support use cases. ESVN is one of the most important safetyrelated C-ITS services to be deployed and can also be extended to other emergency services such as police and fire response. Rolling out the vehicle-to-vehicle communication technology to many traffic participants, not only passenger vehicles but also specialised vehicles like ambulances, fire trucks or police cars, trams and buses, would greatly increase the penetration rate of C-ITS to maximise its benefits. This can be supported by evaluating retrofit solutions for existing long/medium-life assets. While specific to Victorian legislation, C-ITS use cases may be extended to other states according to individual states’ requirements; national consistency would facilitate quicker and more standardised adoption. The data exchanged between traffic participants via ITS-G5 must be anonymous and authentic. The ITS standards and well-known harmonising platforms like C-Roads in Europe already define several security requirements and governance specifications. Similarly, these need to be deployed and evaluated in Australia. As C-ITS development and rollout progress, collaborations between government and industry must be continued to define the data requirements and systems to support C-ITS and the broader management and optimisation of transport networks. Representatives should be nominated to lead harmonisation in Australia to ensure smooth deployment and interoperability across the nation. Refer to the public white papers [11] for more comprehensive details.

8. References

[1] David B. Logan, Kristie Young, Trevor Allen and Tim Horberry (2017). Safety Benefits of Cooperative ITS and Automated Driving in Australia and New Zealand, Austroads

Research Report. AP-R551-17. [2] Toyota Motor Corporation (2021).

TOYOTA ITS Web Exhibition 2021 -V2X-. https://www.toyota.co.jp/its/en/2021/ [3] Transport for NSW (2022). SCATS and

Intelligent Transport Systems. https:// www.scats.nsw.gov.au/ [4] Ambulance Victoria (2021). Ambulance

Victoria Annual Report 2020-21. https:// www.ambulance.vic.gov.au/wp-content/ uploads/2021/10/Ambulance-Victoria-

Annual-Report-2020-21.pdf [5] Road Safety Road Rules 2017 S.R. No. 41/2017 Authorised Version incorporating amendments as of 4th November 2020 (Authorised Version No. 009) [6] Victoria State Government (2021). Law enforcement & emergency vehicles. https://www.vicroads.vic.gov.au/ safety-and-road-rules/road-rules/a-toz-of-road-rules/law-enforcement-andemergency-vehicles [7] Victoria State Government (2022). Tram collisions on the rise. https://transport. vic.gov.au/about/transport-news/newsarchive/tram-collisions-on-the-rise [8] Yarra Trams (2019-12). Separation and Tram Safety Report. https://www. parliament.vic.gov.au/images/stories/ committee s/SCEI/Inquiry_into_the_

Increase_in_Victorias_Road_Toll_ /

Submissions/S40_-_Yarra_Trams_

Redacted.pdf [9] Yarra Trams (2020-05). Tram Stop

Road Safety Data Insights Overview. (Unpublished Yarra Trams analysis) [10] Victoria State Government (2017-01).

Grants, Trials and Partnerships. [11] Lexus Australia et al., (2021). Enabling

Infrastructure to Vehicle Communication for Safety Applications of Connected

Vehicles in Carlton, Victoria – Initial Test;

Enabling Emergency Service Vehicle to Vehicle Communication for Safety

Applications in Australia; Enabling Public

Transport to Vehicle Communication for

Safety Applications in Melbourne, Victoria.

The University of Melbourne https://eng. unimelb.edu.au/industry/aimes

Appendix A – ITS-G5 Communication Range

The range of ITS-G5 short-range communication message reception is affected by obstacles that impede line-of-sight communication between the RSU and Lexus vehicles. At Gertrude/Nicholson intersection, the RSU was installed at the Southern end of the intersection (Figure 21). The building at the intersection’s southeast corner limited the communication range on Gertrude St. Compared to both Nicholson St approaches, the range in Gertrude Street was almost halved (150 meters). In this case, the communication range is likely to be sufficient. However, the location of the RSU installation must be carefully selected to optimise communication range in all directions.

Appendix B – ESVN Alert Distance at Different Vehicle Speed

The aambulance was determined to be stationary when its vehicle speed reported in the CAM was less than 3km/h. When the

Figure 22. ESVN alert triggering at different vehicle speeds

Lexus vehicle approached the ambulance at the speed of 60, 80 and 100km/h, the alert was triggered at different distances accordingly (Figure 22).

Appendix C – Positioning Accuracy

The positioning system is paramount to any C-ITS-enabled vehicle to save lives, as positioning accuracy is critical for delivering accurate and contextual safety warnings to the driver. With this study, positioning performance in the local environment, where Lexus Vehicles operate in AIMES, were identified. Figure 23 shows the heat map of the positioning accuracy in the Carlton neighbourhood and Melbourne CBD. The heat map provides a high-level overview of positioning errors (Green: 0-30cm, Amber: 30cm-3m, Red: more than 3m) seen by the vehicles to determine the quality of C-ITS warnings presented to the driver. In other words, this information can be used to determine the reason for particular false positives or missing alerts due to positioning errors. Compared to Carlton, in Central Business District (CBD), where there are tall buildings and tree cover, the positioning accuracy was at its lowest when the antennas were obscured from receiving line-of-sight satellite signals. Conversely, the accuracy was high when there was no obstruction. In addition to the environmental factors, positioning accuracy varies when receivers with different brands and grades are used. While line-of-sight satellite signals were obscured, dead reckoning, a technique to estimate the current position based on a previously determined position, can be applied. An Inertial Navigation System (INS) uses rotation and acceleration information from an Inertial Measurement Unit (IMU) to compute a relative position over time. The following figure shows the positioning result when using a receiver unit with tactical grade IMU (Figure 24); high positioning accuracy was achieved throughout. Using an INS-based GNSS receiver with RTK configuration and connecting to an RTK correction service that can dynamically connect to the nearest reference stations would offer the best positioning capability to deliver appropriate driver alerts. Positioning and other enabling technologies will evolve between now and any prospective implementation in vehicles for Australia. Deeper integration with existing vehicle systems and advanced driver assistance systems will lead to greater accuracy of information presented to the driver and minimise false warnings.

Figure 23. Position Accuracy in Carlton Area and Melbourne CBD