Intelligent traffic light project

/ DENSE URBAN / INTELLIGENT TRANSPORT SYSTEMS /

Maximize the smooth flow of heavy vehicles approaching traffic lights on a 6 km stretch of road in a critical area.

A PROJECT BY

Up to 3 liters of fuel are needed to accelerate a heavy vehicle after a stop. So, how can traffic flow be improved and the number of unnecessary truck stops at traffic lights be reduced? The answer is both simple and complex: by enabling heavy trucks to communicate with traffic lights in order to adjust green light sequences and timings when necessary.

In 2021, the City of Trois-Rivières decided to take on the challenge by implementing a pilot project that ultimately allowed it to optimize energy efficiency and reduce greenhouse gas (GHG) emissions from urban freight transport on its territory thanks to Internet of Things technologies.

In collaboration with its partners, the City developed and implemented an intelligent transport solution that, while remaining safe, maximizes the smooth flow of heavy vehicles approaching traffic lights on a 6 km road section — heavily used by this type of vehicle and impossible to divert — in a critical area.

In addition to reducing GHG emissions from urban freight transport, the prioritization system helped improve traffic flow in some situations for all users, reduce urban noise levels and contribute to the performance of local businesses.

This project led to the modernization of the control systems of 14 traffic lights, centralized tracking of heavy trucks and the development of the algorithms and communication protocol allowing stop-avoidance service requests to be sent to the traffic lights.

Project objectives

• Demonstrate the feasibility of contributing to the achievement of a common goal, namely the reduction of GHGs, by carrying out a "Smart City" type project in collaboration with community partners (private, institutional, etc.).
• Demonstrate the potential of using new technologies to reduce GHG emissions generated by urban freight and passenger transport.
• Develop expertise to facilitate the future implementation of sustainable mobility projects, in a collaborative mode.

Together, let’s support and accelerate innovation by sharing knowledge and best practices!

Pre-project methodology

The implementation and preliminary testing phase was carried out from March 2021 to June 2022. First, the City modernized intersections and telecommunications to document counting measurements before installing sensors to measure impacts, anonymously observe user behaviors and calibrate simulations. The project team worked to optimize the operational parameters of the traffic lights and the vehicle detection algorithms in order to maximize the reduction of GHG emissions.

For its part, Laval University focused on modeling the road network to ensure a clear view of the reality on the ground.

In collaboration with Transport Somavrac, niosense built a centralized platform to capture the data. Functional tests, carried out with the City's equipment, made it possible to collect the carrier's telematics data in March 2022.

A few months later, in September 2022, the stop-avoidance equipment was installed. The connected fleet expanded, enabling the geolocation of more vehicles and optimal coordination with the traffic lights.

Performance measurements and optimizations took place continuously until June 2023.

Funding

The budget is $978,000, including $400,000 for infrastructure, $500,000 for software and $78,000 for modeling and research. This amount includes infrastructures (telecommunications, additional sensors, etc.), software and research and development (identification of the system's optimal parameters, for example).

This investment will benefit other cities interested in implementing this solution. They will be able to rely on the methodology, data and best practices of the City of Trois-Rivières to reduce their development and testing costs.

Results achieved

Sustainable mobility

According to statistics and projected simulations with university partners, the anticipated impacts of the implemented solution are on the order of one avoided stop for each passage of a heavy truck on the targeted road segment. For this corridor and the project's fleets, this represents 16 avoided stops per day (since these vehicles use it frequently) and an estimated reduction of one liter of diesel for each stop, or about 2.7 kg of CO2. This represents 43.2 kg per day and 11.2 tonnes per vehicle per year (based on 5 days/week).

It is expected that several hundred vehicles will be able to use the offered functionality. With an estimate of 200 vehicles each making two round trips per day, the project's impact on GHG emissions will be 561 tonnes of GHG per year for the single segment of 14 deployed intersections, representing savings of 10% to 20% in stops, 10% in time and 1.5% to 5% in fuel consumption.

In addition to the positive impacts of GHG reduction, this innovative solution reduces the use of engine braking, braking and acceleration noise and also helps avoid some of the fine particle emissions related to braking systems. It also reduces mechanical maintenance and fuel costs while improving traffic flow.

Optimization and validation of technologies

From a technological standpoint, the project is built around an innovative, open, data-centered architecture with at its core a state-of-the-art real-time data distribution system. The project benefits from technological advances in Lidar sensor detection, the Internet of Things (IoT), cellular connectivity, urban mobility simulation and modeling tools, cloud computing and artificial intelligence.

Exportability and sustainability of the project

The project can easily be exported to any municipality that manages traffic lights. A methodology has been developed to facilitate the knowledge transfer process.

For example, in the case of a typical municipality, the adaptation costs (for the City) to be able to use this solution range between $1,000 and $10,000 per intersection (depending on the current state of the traffic lights), not including maintenance fees, cellular communication to the intersections and mobile data.

The business model, developed within the project, allows the city to benefit from connected infrastructures economically by involving users in their maintenance, to the benefit of all citizens.

Lessons learned

Success factors

• Conducting a structured feasibility study during the preparatory phase;
• Integrating the project into a Smart City, Sustainable Mobility and Innovation vision;
• Collaboration or networking between the City and stakeholders in the road freight transport sector;
• Open-mindedness, a taste for innovation, the vision and boldness of elected officials and City management;
• Involvement of the City's internal contributors (Public Works, Information Technology, Engineering, Clerk's Office, Finance and Procurement);
• Financial support from partners to accelerate project implementation;
• The collaboration of Innovation and Economic Development Trois-Rivières helped facilitate relationships with partners in the local industrial and commercial community;
• Involvement of road freight companies willing to equip their fleets with vehicle tracking beacons and be the first users to test the prioritization system;
• Conducting tests to validate technologies upfront;
• Involvement of innovative start-ups in the project;
• Assessment of all costs;
• Project sustainability;
• Sharing best practices and data with other cities interested in adopting Smart City practices;
• Team consistency and stability;
• Transparency and information sharing from all project team members;
• Speed and responsiveness of stakeholders.

Practical advice for carrying out such a project

• Ensure financing is well planned in advance;
• Rely on political will and a vision for Sustainable Development;
• Validate technological choices and opt for proven, open solutions;
• Ensure the modeling presents a traffic simulation for different times of the day;
• Equip yourself with reliable modems to avoid communication failures;
• Plan equipment procurement to avoid delivery delays;
• Define in advance the method for calculating energy savings gains. It is complex to establish the savings realized on mechanical maintenance, for example.

Next steps

This initiative made it possible to demonstrate and test this new technology successfully. The project will run until June 2023 to collect further data.

TheLaval University will oversee the development of a simulation report to present the anticipated gains.

The sustainability of this stretch will ensure better transport fluidity at the heart of the City. The project could then be opened to agencies representing one or different types of carriers, such as snow removal companies, ambulance services, etc., according to a priority order to be defined.

A vision with potential impact across Quebec and Canada.

According to Statistics Canada, 270,150 heavy trucks were on the road across the country in 2020. If the project's approach were extended nationwide, this could represent annual reductions of 3,025,680 tonnes of GHG (assuming a speed of 50 km/h at all stops).

Project partners

• City of Trois-Rivières – project proponent
• Ministry of the Environment and the Fight Against Climate Change : financial support for project implementation
• Niosense : technological partner responsible for implementing the software interface required to easily interconnect system users with the City's traffic lights
• Laval University (via its "center for innovation in sustainable logistics and supply chain" (CILCAD)) : research partner responsible for modeling the Trois-Rivières road network, determining and measuring the system's potential impacts and identifying opportunities for improvement
• Transport Somavrac and the Trois-Rivières Transit Authority : companies transporting goods and people that agreed to equip their vehicle fleets with vehicle tracking beacons and to be the first users to test the prioritization system
• IVEO : support for municipal innovation

Articles published about the project :

• A pilot project launched in Trois-Rivières to reduce GHGs
• Connected traffic lights to reduce GHG emissions
• Intelligent traffic lights: sustainable mobility according to Niosense

Project contact person

Niosense
Patrick Lauzière, CEO
info@niosense.com

City of Trois-Rivières
1240 Royale Street
P.O. Box 368, Trois-Rivières (Quebec) G9A 5H3
v3r.net

Vincent Turgeon
Coordinator – Operational Technology Systems
Information Technology Department
Tel. 819 374-2002

Somavrac Group
3450 Gene-H.-Kruger Boulevard
Trois-Rivières (Quebec)
G9A 4M3
Phone: 819 379-3311
Email: info@groupesomavrac.com
Martin Deschamps – Director General, Transport Operations