Using C-ITS to make motorcyclists safer

Motorcycle riders form a disproportionate percentage of fatalities and accidents on Australian roads. Despite major advances in vehicle safety and intelligent transport systems (ITS), motorcycle safety technologies have largely been left behind. The completed project Motorcyclist safety: Connected motorcycle pilot looked to address these three key questions:

1. Are Cooperative Intelligent Transport Systems (C-ITS) for motorcycles technically feasible?
2. Do riders want this technological assistance?
3. Are they effective? Do they help riders react earlier?

Partners on this iMOVE project were Department of Transport and Main Roads (Queensland), Transport Accident Commission, and La Trobe University.

Final reports from the project are available for download below.

Background

Motorcyclists are among the most vulnerable road users, with significantly higher fatality and injury rates per kilometre travelled than car occupants—the highest risk among all motorised vehicle users. They face the highest fatality rate of any motorised road user group in Australia, representing 20% of road deaths despite accounting for just 0.7% of kilometres travelled.

In 2024, 278 riders lost their lives, a 10.3% increase from 252 deaths in 2023, making it the deadliest year since 1989.

The application and use of C-ITS for motorcycles builds on work already conducted for car drivers in the Ipswich Connected Vehicle Pilot. Findings from that earlier work demonstrated that connected vehicle technology could indeed make improvements to road safety in real-world conditions.

C-ITS can increase rider safety in two ways: by alerting riders about road hazards and by making nearby road users aware of the presence of motorcycles.

C-ITS has been trialled for vehicles for almost two decades, but very little of that work has been for the specific use cases of motorcycles.

The work conducted in this trial is the first trial globally to fully test C-ITS for motorcycle-specific safety challenges, using ‘regular’ motorcyclists. Alos on-board for this research were industry partners and regulators.

Project design

The pilot adopted a three-phase approach

1. Market research

• Rider workshops (115 participants)
• Quantitative survey (360 participants)
• Potential HMI provider (20 organisations)
• HMI collaborators (6 organisations)

2. Prototype development

• HMI (30 participants)
• Simulator (30 participants)
• Motorcycles (3 vehicles)
• Use cases (3 participants)

3. Trial

• Test track (94 participants)
• Simulator for behavioural data (65 participants)

From the very beginning, riders were at the core of this project. Riders in Victoria and Queensland were invited to informal gatherings, where they “… gave us a clear picture of how riders think about safety, what makes them feel vulnerable, and how they respond to external alerts.” They were also asked how they though warning should be delivered, and how much information can be safely absorbed while riding in traffic.

These informal— but valuable — beginnings were followed up with a survey, providing answers from 376 riders with varying experience. Most riders were open to the concept of C-ITS, but a quarter of riders were ‘on the fence’ when they were first introduced to it, as shown in the table below.

Riders’ concers

Amongst the concerns expressed by riders were:

• False alarms or missed hazards.
• If the warning would be delivered in time to respond / react.
• Riders were wary of anything that disrupted focus or added unwanted hardware.
• Alerts should blend seamlessly into the riding experience.
• Riders wanted warnings that adapt to their riding style or preferences (e.g. ‘conservative’ vs ‘aggressive’).
• Control over which warnings were active and how they were delivered (e.g. brightness, sound, vibration).
• Some feared over-reliance could reduce situational awareness.
• Cost was a concern, especially for non-premium or older bikes.
• Concerns about how data might be stored or used, particularly when connected to government systems.

Over the course of the project, we maintained focus on these ‘risky’ riders: If we could address the concerns of the most critical riders, we would also meet the needs of the other riders. These insights helped improve the prototypes and understand the potential barriers we could face in our upcoming trials.

Of considerable help to the design of the trials was data from Queensland. In that state the cause of a crash is recorded, allowing researchers to look at 10 years of crash data pertaining to motorcycles. Victorian crash data was also used to support the analysis.

5 use cases

Based on the interviews, surveys, and data, the project focused on five use cases:

1. Forward collision warning;
2. Intersection movement assist;
3. Dangerous curve warning;
4. Change of road surface warning; and
5. Lane change assistance / Blind spot warning

These use cases represented not only high frequency causes of crashes, but also those that would most appeal to riders.

HMI devices

To deliver messages for these use cases, prototype HMI devices were developed, including:

• Smart helmet: LEDs beneath the visor to deliver warnings in the riders’ lower peripheral vision.
• Smartphone apps: Present directional and distance-based warnings.
• LED mirrors: Alert riders of hazards to the rear.
• Audio alerts via earphones: Beep followed by short voice message to capture attention and convey the location and hazard type.
• Dashboard alert: Display of 8 directional cues with urgency indicators.
• Smart glasses: Projects the same 8 directional cues as the dashboard alert..
• Haptic wristband: Mild vibration indicates caution, stronger vibration indicates immediate danger.

Track and simulator trials

Two types of testing took place. First, three test motorcycles with 94 test riders on a track. The motorcycles were connected to track infrastructure, other vehicles, and data collection via V2X hardware.

Secondly, 65 riders  participated in the trial on a custom-built motorcycle simulator, using the same 5 test cases as the track riders, but with increased simulated risk.

For both these trials rider behaviour was recorded in real-time. Subjective feedback from the riders about the testing was gathered from a structured survey, before, during, and after testing.

C-ITS hardware

For the track trial the research team integrated a Cohda MK6 On-Board V2X Unit into each of the three test motorcycles, enabling communication with nearby vehicles and infrastructure. The MK6 was also connected with the motorcycles’ On-Board Diagnostics port, allowing access to the motorcycle’s diagnostic information. This setup provided critical data, such as throttle position, speed, brake light status, and turn indicators, all uploaded 10 times per second.

The data flow begins with the motorcycle, which sends speed, throttle, indicator, and brake signals to the prototype CANbox. The CANbox packages this data into Java Script Object Notation (JSON) and broadcasts it via User Datagram Protocol (UDP).

Both the Cohda MK6 OBU and Android device receive this data. The Cohda unit processes it alongside CAM, DENM, and GPS data to generate hazard warnings, which are then sent to the Android device. The Android device timestamps and forwards all received data, including Cohda warnings, to a MongoDB database service for storage, while also keeping a local backup.

How dd the technology perform?

Findings show strong potential for low-effort, high-impact safety warnings, such as road surface alerts, work zone notifications, and other Infrastructure-to-Vehicle (I2V) messages. Riders started reacting to a dangerous curve 16 meters earlier when warned about it.

Recommendations

Upon the conclusion of the trials come the following recommendations:

1. Given the elevated risk and demonstrated benefits to riders, motorcycles should be considered in all C-ITS ecosystem developments.
2. Governments can accelerate impact by establishing a nationally accessible database of known hazards—such as dangerous curves, roadworks, and black spots—that navigation apps and connected vehicle systems can draw from to deliver consistent warnings to riders.
3. Motorcycle manufacturers can accelerate the integration of collision avoidance technologies and support Bluetooth-based interoperability with third-party wearable Human Machine Interfaces (HMIs). These steps lay a practical foundation for broader C-ITS adoption.
4. Collaboration with the car industry could establish the added value of C-ITS in collision avoidance of motorcycles compared to other technologies (and raise motorcycle awareness among drivers at the same time).
5. Standardised Application Programming Interfaces (APIs) and open communication protocols should be adopted to support compatibility between factory-fitted systems, aftermarket solutions, and rider-preferred devices, enabling a diverse but connected ecosystem.
6. Smart algorithms using AI and edge computing can be co-developed across the industry, in line with the current collaboration on standards. This can ensure a shared understanding of complex traffic scenarios, reduce duplicated effort, and support consistent warning logic across different platforms for the greater good.

What’s next?

Results in this project were obtained using commercially available, off-the-shelf hardware, and simple test algorithms, indicating that the necessary components and basic scenarios are ready for deployment. Still, significant collaboration efforts are required.

From a policy perspective, C-ITS on motorcycles offers a compelling case for public investment: it targets a high-risk user group, shows strong rider acceptance, and has the potential to significantly reduce crash-related injuries and fatalities, a major cost driver in national health and transport budgets.

Governments need not wait for a full-scale rollout. Initial collaboration efforts, such as building the digital infrastructure for hazard warnings, would already yield benefits and catalyse industry collaboration. This incremental approach lowers cost barriers and accelerates the path to connected rider safety.

It should also be said that the rider community is ready, especially when included as partners in development. With collaborative design and smart deployment of existing technologies, the future of motorcycle safety can begin today.

Download the reports

Download your copy of the final report and summary report by clicking the following links:

• Connected Motorcycle Safety: Summary report: Whole of project
• Connected Motorcycle Safety Report + Appendices