What Is Smart Road Technology?
With new pressures for cities to develop more-effective roadways and highways, smart infrastructure is essential for modernization. Smart city roads built on IoT technologies make it possible for cities to collect and analyze data to improve day-to-day traffic management and adapt for long-term transportation needs. With IoT sensors, cameras, and radar, 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 or improving road conditions.
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 can automatically adjust their timing based on sensor data, enhancing 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/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.2 Smart road technology can track vehicles and adjust traffic lights when there are fewer or no cars approaching, helping prevent bumper-to-bumper traffic. This could help drivers and passengers save 9.4 hours each year.1
- Improved traffic and pedestrian safety. Traffic-monitoring solutions powered by computer vision can detect vehicles, pedestrians, and bicyclists to help enable safety practices. In the event of a crash or crime on the street, smart devices can immediately alert first responders.
- Enhanced parking and e-tolling. E-tolling reduces 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 environmental quality, for example:
- Identifying problem areas. Analytics can help detect intersections or other sites that have a high rate of collisions or near misses between vehicles or pedestrians. This helps cities determine if the site would benefit from a yield or stop sign, crosswalk, or traffic light.
- Improving pavement conditions. Over time, streets erode or weather away. With road condition monitoring, cities can assess pavement conditions and act accordingly. According to the Minnesota Department of Transportation, if cracks in pavement are addressed early enough, cities can pay roughly USD 62.50/lane/km/year, compared to USD 1,000/lane/km/year if not addressed properly.3
- Reducing pollution. Smart infrastructure can help reduce carbon emissions from daily transportation by optimizing traffic flow to avoid idling engines. Cities can also help reduce pollution by understanding where to best place electric vehicle charging stations.
For an average United States citizen, congestion costs 99 hours of their time and USD 1,377 each year.2
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 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 and can 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.
Global Use Cases and Case Studies
Smart road technology is not a futuristic concept. It’s already being implemented all over the world, and some cities and countries are seeing its benefits today.
Learn more about the road use cases enabling the cities of the future in the video below:
Discover how real cities and governments are using smart road infrastructure solutions to help improve the lives of their citizens. We explore some of these case studies below, but we encourage you to check out our e-book to view more.
Edge Services for Roadside
German industrial manufacturers collaborated with Intel on a research project with the goal of improving the agility of automated vehicles, vehicle safety, and the overall flow of traffic on highways. With Intel® Xeon® processors inside edge nodes, the project covered a two-kilometer section of a highway between Munich and Nuremberg, transmitting traffic information to oncoming vehicles and identifying potential risks ahead.
Electronic Toll Collection (ETC)
Shenzhen JHC Technology Development Co. (JHCTECH) teamed up with Intel to improve China’s existing transportation infrastructure and ETC systems. The JHCTECH ETC IPC series can detect and identify vehicles automatically, allowing toll fees to be paid without stopping. This helps break up bottlenecks and keep traffic moving. Edge solutions are powered by Intel® Core™ vPro® processors, which deliver high performance and remote management capabilities.
Intelligent Traffic Management
Powered by Intel® Core™ processors, the GRIDSMART System uses computer vision to monitor intersections and collect traffic data in near real-time. On Arizona’s Bell Road Highway, GRIDSMART’s camera system reduced delays by 20 percent on weekdays and 43 percent on weekends.4
Smart Sensors for Road Infrastructure
As a member of the Intel® IoT Solutions Alliance, Hitachi Vantara designs solutions that improve traffic management with smart cameras and other edge technologies. Hitachi developed a camera system powered by Intel® technologies that provides real-time data, analytics, and storage at the edge. The cameras are suitable for indoor or outdoor environments, are easily deployable, and function in extreme weather conditions.
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
Our 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 street lights, 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. These edge nodes can even provide public Wi-Fi coverage. Supported by Intel® Vision Products with integrated security features, the AAEON Atlas edge computing node is a ready-to-deploy solution based on this reference design.
Converged Edge Reference Architecture (CERA)
CERA is a platform approach for IoT and networking workload convergence. With this architecture, our 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 OpenNESS. 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.
Intel’s 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 in an OpenNESS edge node, which contains all the necessary software stacks to host a 5G RAN.
|Intel® Technologies for Smart Roads and Smart Infrastructure|
|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.|
|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.|
|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™ toolkit4||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 a lot of 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, 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.