Smart Roads Start with Smart Infrastructure

Smart road technology enables better access to citizen resources, an improved quality of life, and more safe and sustainable transportation for all.

Benefits of Smart City Roads

  • Multimodal sensors and edge computing help speed up the flow of traffic with real-time processing, reducing congestion and emissions.

  • Smart road technology can assist in optimizing traffic flow and managing road conditions, creating a more sustainable environment within cities.

  • Smart road technology using multi-access edge computing (MEC) edge servers leverages 4G/5G cellular networks to improve real-time safety and traffic data.

author-image

โดย

What Is Smart Road Technology?

With new pressures for cities to develop more effective roadways and highways, smart infrastructure is essential for modernization. Smart roads built on IoT and information and communications technology (ICT) can make it possible for cities and transportation authorities to collect and analyze data to improve day-to-day traffic management. Smart road infrastructure can also help cities adapt for long-term sustainable transportation needs. With IoT sensors, cameras, radar, and 5G-equipped technologies, data can be analyzed in near-real time and used to improve congested roadways, streamlining traffic flow. Data can also be sent to the cloud for long-term analysis, providing critical insight for efforts such as reducing CO2 emissions.

Edge computing opens myriad possibilities for smart and connected roads. It enables low latency for the analytics and artificial intelligence (AI) that power smart road infrastructure, like adaptive traffic lights and integrated roadways. For example, traffic lights that automatically adjust their timing based on sensor data can enhance the flow of traffic or change signals to help protect others on the road from dangerous drivers.

Benefits of Smart Roads and Smart Infrastructure

There are many types of devices that enable smart road technology: speed sensors, acoustic sensors, IP CCTV cameras, smart traffic lights, condition and weather monitoring systems, and digital signage. When these devices collect and analyze data in near-real time, cities can realize several benefits:

  • Less congested streets. For an average US citizen, congestion costs 99 hours of their time and USD 1,377 each year.1 Smart road technology can track vehicles and adjust traffic lights based on traffic conditions, helping prevent bumper-to-bumper traffic.
  • Improved traffic and pedestrian safety. Pedestrian deaths have risen by a staggering 46 percent over the past decade compared to a 5 percent increase in all other traffic-related fatalities.2 Smart roadside equipment deployed in intersections can provide alerts that enhance safety for vulnerable road users, including pedestrians, bicyclists, and motorcyclists.
  • Extended connectivity alongside transportation infrastructure. Roadside network deployments can extend and improve wireless public/private connectivity and the use of intelligent transportation system (ITS) applications on roadways and transportation corridors, including those that were previously unconnected. This results in improved coverage and access to near-real-time insight into activities and events happening on roadways that can be used to proactively address problem areas, reduce response times, and improve overall road safety.
  • Enhanced parking and e-tolling. E-tolling can reduce congestion by using license plate recognition and vehicle tracking to automatically charge highway and bridge tolling fees—all without making vehicles stop or slow down.

By sending select data to the cloud to be analyzed over time, cities can make continual improvements in traffic management, road maintenance, and sustainability. Cities can also use digital twin technology to create virtual city models using real data to continuously evaluate and improve current infrastructure as well as test new technologies prior to full investment. Smart road technology can enable cities to assist in the following ways:

  • Improved services and emergency response. Creating a digital twin environment powered by Intel® technologies can enable roadside infrastructure to provide on-demand commercial services to vehicles or other road users and can help alert first responders to accidents.
  • Improved road layout and pavement conditions. Road condition monitoring solutions can help city planners analyze the rate of collisions and near misses as well as assess road and pavement conditions. This aids in proactively identifying needed road layout changes and pavement improvements. Delayed improvements can result in increased costs for cities, up to 150 percent per lane/km/year.3
  • Sustainable transportation. Smart infrastructure enables optimization of traffic flow and standardization of EV charging networks, helping to promote the use of lower emission vehicles and reduce carbon emissions from daily transportation.

Large cities consume more than two-thirds of the world’s energy and account for more than 70 percent of global greenhouse gas emissions.4

Global Use Cases and Case Studies

Smart road technology is not a futuristic concept. It’s already being implemented worldwide, with many cities and countries experiencing the benefits today.

Read on to discover smart road technology innovations Intel customers and partners have developed to help address transportation challenges and improve the lives of citizens.

  • Intelligent traffic management. Mayflower has partnered with AAEON Technology to help local governments and traffic management groups make road infrastructure improvement decisions. With its lightweight, easy-to-adopt optical sensor, the Mayflower Smart Control Insite Sentinel sensor can be mounted anywhere and moved as needed.
  • E-tolling and smart parking. ST Engineering Electronics’ Smart Car Park Platform is a cloud-based car park management solution that centralizes all car park operations and maintenance. The solution leverages ANPR and mobile payment apps to provide efficient and nonintrusive, seamless parking services to motorists while offering operating efficiency and cost savings to car park operators and building owners.
  • Digital twin and sensor fusion. German industrial manufacturers collaborated with Intel Labs on the Providentia ++ (P++) project to improve automated driving by using infrastructure-based sensor fusion. To achieve project goals, the team leveraged self-organizing orchestration of compute loads between infrastructure and automated vehicles at the hardware and OS level.
  • Smart connected roads. To help city authorities and transportation solution providers implement smart city applications that leverage 5G networking and edge services, Capgemini Engineering and Intel collaborated to create the Capgemini Engineering Smart 5G RSU solution which simplifies smart city and transportation technology obstacles through Capgemini Engineering’s ENSCONCE MEC platform.
  • Smart connected roads. The city of Turin, Italy, hosted a live international trial of new driver and pedestrian safety technology that could allow near-real-time notification of roadway hazards through a 5G-edge network. This public-private collaboration, organized by the 5G Automotive Association (5GAA), exhibited how the connected car concept could use high-speed and edge computing technology, along with IoT, to communicate with car sensors and pedestrian smartphones.
  • Smart connected roads. The Cellnex Mobility Lab in Castelloli, Spain, is dedicated to developing 5G-based, sustainable, connected, and autonomous mobility solutions for vehicles, traffic management, and road infrastructure. To conduct its research, it digitally transformed the Circuit Parcmotor Castelloli racing complex into a living lab for smart mobility and connected/autonomous vehicles using high-definition cameras, a cellular Vehicle-to-Everything (C-V2X) wireless network, and converged edge architecture.
  • EV charging. Imagen Energy and a leading EV charging OEM leveraged Intel® technologies to create a next-generation EV DC-fast charging solution that is more efficient, compact, configurable, and cost-effective. This next-generation charger combines Intel® CPUs with Intel® FPGAs for the ability to use advanced capabilities at the edge, such as remote management, digital advertising, and edge networking, while also providing industry-leading power efficiency.

Read our Intel® eBook on intelligent road infrastructure to learn more about the positive outcomes cities and transportation leaders are achieving with smart road technology.

The Future of Smart Roads

Urban population, forecasted to exceed the world’s rural population by 2050,1 will have a profound impact on transportation infrastructure and the environment. Learn more about the road use cases that will enable the cities of the future in this video:

Striving for Intelligent Transportation Policies

Policies and standards are critical for deploying IoT technologies in transportation. As a member of 5GAA, Intel is working with policy makers, automakers, manufacturers, and infrastructure owner-operators to deploy digital infrastructure such as cellular vehicle-to-everything (C-V2X) around the world. This 5G standards–based technology helps ensure that vehicles, infrastructure, and other road users are connected to mobilize safely. Intel has also been an active member of technical bodies and contributes to standards development for collaborative perception, maneuver coordination, and misbehavior detection.

Intel® Technologies for Smart Roads

Sensors, AI, and intelligent cameras are some of the driving IoT technologies that make smart infrastructure possible. Intel and our partners have developed technologies and hardware to assist in edge and cloud computing for smart road technology. We provide prevalidated reference designs and reference implementations to enable solutions that modernize road infrastructure.

Roadside Unit Reference Design

The Intel® reference design for roadside edge computing powers a unit that can be attached to streetlights and other fixtures. This roadside unit is ideal for real-time video analytics and other performance-hungry tasks. Cities can deploy these units as part of a solution for smart streetlights, smart traffic lights, smart parking, or e-tolling stations. They deliver the processing capabilities needed to detect license plates, spot pedestrians, and monitor traffic congestion.

Converged Edge Reference Architecture (CERA)

CERA is a reference architecture for IoT and networking workload convergence. With this architecture, Intel partners can design solutions for roadside equipment to process sensor modalities and perform sensor fusion. This brings intelligence to the edge while hosting 5G network capabilities and microservices.

Solutions built on this platform can be set up at intersections or on-premises for near-edge computing and data processing for multiple IoT devices. Solutions can be optimized using the Intel® Distribution of OpenVINO™ toolkit and Intel® Smart Edge Open Toolkit. With 5G connectivity, CERA provides networking capabilities that allow IoT devices to communicate with each other at the edge or send data to the cloud. It processes the information from cameras, radar, and a wide range of other sensors.

Reference Implementations

Intel® reference implementations offer preconfigured software for a complete sample application. Our intelligent traffic management reference implementation is designed to monitor intersections via IP cameras to optimize the flow of traffic. Our wireless network-ready intelligent traffic management reference implementation is hosted with Smart Edge Open, which contains all the necessary software stacks to host a 5G RAN.

In addition, Intel provides a portfolio of other technologies that enable low latency and efficient connectivity.

Intel® Technologies for Smart Roads and Smart Infrastructure
Edge Compute
IoT and embedded Intel® processors Enhanced for IoT and embedded use cases, Intel® processors come in a range of options for compute performance and power consumption, enabling the latest audio and visual quality for intelligent cameras and sensors attached at roadside.
Intel® Xeon® Scalable processors Intel® Xeon® Scalable processors deliver high performance for edge servers, ideal for performing real-time analytics and AI on smart road sensor data.
AI and Computer Vision
Intel® Movidius™ VPUs Intel® Movidius™ VPUs enable computer vision for specific use cases, such as finding or “seeing” license plates and vehicles at smart intersections.
Networking
Intel-supported 5G networks Intel-supported 5G networks will improve real-time traffic data at the edge while also advancing connectivity and transmission to and from wireless networks.
Developer Resources
Intel® Edge Software Hub Find software to accelerate the development of smart road infrastructure solutions, including referenced implementations for intelligent traffic management.
Intel® Distribution of OpenVINO™ toolkit5 The Intel® Distribution of OpenVINO™ toolkit streamlines the development of vision applications on Intel® platforms, including VPUs and CPUs. This portfolio enables computer vision to locate pedestrians, cars, and street signs.
OpenNESS OpenNESS open source software simplifies the complex orchestration and management of edge services across diverse network platforms and access technologies.
Intel® DevCloud for the Edge Reduce time and cost in determining the right hardware for optimal AI application performance. Intel® DevCloud for the Edge provides instant performance feedback via a virtual AI prototyping tool.
Open Visual Cloud This collection of open source stacks and pipelines is built with optimized ingredients for encode, decode, inference, and render. This creates a reusable developer environment that eases testing, evaluation, and deployment of services, including video on demand (VOD) and live streaming with SVT-AV1.

Expanding on Smart Road Technology

While smart road technology has already been implemented across the world, the future of smart infrastructure is only getting started. Cities today are seeing the benefits—reduced traffic congestion, increased public safety, and lowered CO2 emissions. With the latest generation of IoT technologies, city planners can confidently invest in smart road technology that makes an impact.

Frequently Asked Questions

Smart roads make use of smart road technology, smart road infrastructure, and other computing solutions, including IoT and ICT-enabled devices, edge and cloud computing, and AI, to collect and analyze data across cities and roadways. Cities and transportation authorities can use this data to improve day-to-day traffic management, assess and plan for long-term sustainable transportation needs, decrease environmental impact, and improve the lives of citizens.

With access to smart road devices that collect and analyze data in near-real time, cities can reduce roadway congestion, manage traffic flow, and improve pedestrian safety. Smart road infrastructure helps cities identify problem areas, improve pavement conditions, better enable emergency services, help reduce carbon emissions, and inform sustainable transportation efforts.

ข้อมูลผลิตภัณฑ์และประสิทธิภาพ

1

“Congestion Costs Each American Nearly 100 Hours and $1,400 per Year,” itsdigest.com, เข้าใช้เมื่อเดือนพฤษภาคม 2022, itsdigest.com/congestion-costs-each-american-nearly-100-hours-and-1400-year

2

“Pedestrian Traffic Fatalities by State: 2020 Preliminary Data,” GHSA, มีนาคม 2021, ghsa.org/sites/default/files/2021-03/Ped%20Spotlight%202021%20FINAL%203.23.21.pdf

3

“Pothole Prevention and Innovative Repair,” Minnesota Department of Transportation, มีนาคม 2018, dot.state.mn.us/research/reports/2018/201814.pdf

4

“100 วันนับตั้งแต่ข้อตกลงด้านสภาพอากาศในปารีส: 5 เหตุผลที่เมืองต่างๆ มีบทบาทสำคัญในการส่งมอบความสำเร็จ”C40 Cities, เข้าถึงเมื่อ พฤษภาคม 2022 c40.org/news/100-days-since-the-paris-climate-agreement-5-reasons-why-cities-hold-the-key-to-delivering-success/

5

“5G and Distributed Computing Tackle Critical Challenges for Cities,” Intel, กันยายน 2020, blogs.intel.com/technology/2020/09/5g-distributed-computing-tackle-critical-challenges-for-cities/#gs.gspvml