Air : Traffic Control ! The Triple Trigger Approach

Air : Traffic Control ! The Triple Trigger Approach


Colin D Reekie, IBI Group


Triple Trigger Approach extracts air quality and noise data from various sources, such as innovative sensors and microsimulation tools. Output is fed into traffic management algorithms to influence driver behaviour with the aim of managing pollution.


Poor air quality is estimated to reduce the life expectancy of the average UK citizen by 7-8 months, and is responsible for 24,000 to 35,000 premature deaths in the UK. Road traffic is the main cause of exceedence of air quality standards in urban areas and alongside busy roads, and the second fastest growing source of greenhouse gas emissions. Poor air quality is also frequently linked to exceedence of noise limits.

National and international governments have acted. The Scottish Government’s target is to reduce carbon emissions by 80% by 2050. Despite this, the levels of pollution in some urban areas are now exceeding European limits, risking heavy fines for the UK and Scottish Governments.

Improving poor air quality and reducing the noise caused by road traffic requires inventive solutions, such as active traffic management (ATM), which could be used to encourage drivers to use an alternative route or mode (e.g. Park & Ride). However, for ATM to be effective, it requires as inputs accurate and reliable air quality and noise level data.

This paper will provide an overview of an innovative approach – Triple Trigger Point – currently under development by Transport Scotland and IBI Group in partnership with Local Authorities, Strathclyde University and other academic institutions. Triple Trigger Point is intended to produce a holistic system where the air quality data from multiple sources, or “triggers”, can be integrated into ATM.

The triggers intended for use are as follows:
• Measurement of air quality and noise level data using sensors developed, tested and validated at Transport Scotland’s established ITS Test Bed for the purposes of trialling new and innovative technologies. The sensors must be reliable, affordable and maintainable and importantly the information must be defensible.
• Measured flows and analysis of real time emissions using post processing tools AIRE and TANoise. These programs, given the outputs from a microsimulation model, produce the estimated instantaneous levels of air and noise pollution respectively. They differ from more conventional predictions of air and noise quality by accounting for the pollution produced by individual vehicles (especially when accelerating and braking), rather than approximating an average.
• Records of local pollution levels from existing Local Air Quality Monitoring base stations operated by the Local Authorities.

The project will comprise 3 phases:
1. Sensors – We will utilise the ITS test bed to determine the most effective air quality and noise assessment sensors for trunk roads (Trigger 1). This may include transverse distribution assessment. Once tested and costed, we intend to deploy these at appropriate rural and urban locations.
2. Modelled emissions – We will investigate microsimulation post processing tools (AIRE and TANoise) to evaluate instantaneous emissions from real-time traffic data (Trigger 2), liaising with the developers of these tools in onsite validation and calibration against the sensors developed.
3. Trigger assessment and messages – We will develop an algorithm that takes the outputs from previous phases, collates them with real time data from any Local Authority air quality monitoring (Trigger 3), and evaluates appropriate trigger points, related messages, and data to be provided to the public. We will investigate the effectiveness of such messages in stimulating behavioural change, and consider using a test vehicle to simulate real time messages within the vehicle.

It is anticipated the project will take place beginning April 2013. It is expected that the Triple Trigger Point approach can provide a positive impact on behavioural change in order that high emission levels can be controlled effectively.


Association for European Transport