Smart roads have become an essential component of intelligent transportation systems (ITS). The roadside perception technology, a critical aspect of smart roads, utilizes various sensors, roadside units (RSUs), and edge computing devices to gather real-time traffic data for vehicle-road cooperation. However, the full potential of smart roads in improving the safety and efficiency of autonomous vehicles only can be realized through the mass deployment of roadside perception and communication devices. On the one hand, roadside devices require significant investment but can only achieve monitoring function currently, resulting in no profitability for investors. On the other hand, drivers lack trust in the safety of autonomous driving technology, making it difficult to promote large-scale commercial applications. To deal with the dilemma of mass deployment, we propose a novel smart-road vehicle-guiding architecture for vehicle-road cooperative autonomous driving, based on which we then propose the corresponding business model and analyze its benefits from both operator and driver perspectives. The numerical simulations validate that our proposed smart road solution can enhance driving safety and traffic efficiency. Moreover, we utilize the cost-benefit analysis (CBA) model to assess the economic advantages of the proposed business model which indicates that the smart highway that can provide vehicle-guided-driving services for autonomous vehicles yields more profit than the regular highway.

Has road technology reached sophistication? We have already seen perfectly smooth and durable asphalt, which is appropriate for any transport type. How else can the road be improved? Vancouver, for example, has proposed adding recycled plastic particles to asphalt, which increases durability, and allows to partially reuse it during resurfacing. But it only improves the existing pavement.

Logistics needs changes, and Artificial Intelligence brings innovations to this field. There are a bunch of cool innovations like smart roads, autonomous vehicles, and so on. In this guide, we'll discuss the five most promising AI use cases in logistics. Moreover, we've listed companies that have already integrated this powerful technology and even got the revenue. Statistics are quite impressive: Artificial Intelligence integration can bring revenue from $1.3 trillion to $2 trillion per year.

The UK is planning to harness AI to help determine the condition of roads and where investment should be prioritised. British drivers are well-accustomed to poor road conditions, especially potholes and the long delays in getting them fixed (one ingenious man has even come up with an innovative way of getting the council to fix them faster...) To be fair to councils, keeping all the roads in top condition is expensive. Factors like minimising disruption along busy routes, and planning diversions, must also be considered. Fortunately, AI is beginning to help automate this automotive dilemma. The Department for Transport (DfT) has awarded £2m in funding to a project using AI to examine the condition of roads, forming part of a wider £350 million funding package.

For our new series Provocation, Co.Design posed that question to some of our favorite design firms. So far, we've heard about flying inflatable drones that act like airbags for pedestrians, a steering wheel that gives passengers control over their car's morality, and an entire connected street grid. The San Francisco-based firm Astro Studios responded to our prompt by creating a smart infrastructure system with warning lights, street illumination, and a fully reactive road that–in the worst-case scenario–will rise up and become a buffer between car and person. The system, created by Astro creative directors Norio Fujikawa and Alejandro Chavetta, is based on the duo's conviction that self-driving cars will be fully dedicated to protecting their passengers. That means it's up to the city's infrastructure to keep pedestrians and cyclists safe.

If you have followed the development of the Internet, starting with the birth of ARPANET (Advanced Research Projects Agency Network) during the Cold War, its evolution might seem interesting but gradual, until it suddenly exploded and changed our lives. After Tim Berners-Lee brought the World Wide Web into existence, the Internet of the early days became practically unrecognizable. This is how technology often develops – very slowly, and then suddenly, very quickly. Self-driving cars also seem to be following this path. In the last few months, we have seen breakthrough after breakthrough that makes autonomous vehicles less "a distant eventuality" and more "a fast-approaching reality."

Artificial intelligence is driving the autonomous car. Coupled with robust computers, automobiles of the future will be more powerful than any other device we own. But they'll only be as powerful as their surrounding allows. If your vehicle doesn't know about a traffic jam along its route, like its human counterparts, it'll get stuck in gridlock. That's where connectivity comes in. When self-driving cars hit the road, they'll not only be computing juggernauts but also sharing data with everything all the time.

One of the UK's most congested highways, connecting the busy container port at Felixstowe to Birmingham, is to become Britain's first internet-connected road in a pilot project that could pave the way for everything from tolls to self-driving cars. A network of sensors will be placed along a 50-mile stretch of the A14 in a collaboration between BT, the Department for Transport and the Cambridge start-up Neul, creating a smart road which can monitor traffic by sending signals to and from mobile phones in moving vehicles. The technology, which sends signals over the white spaces between television channels instead of mobile phone networks, could even pave the way for government systems to automatically control car speeds. The telecoms watchdog Ofcom, which on Wednesday approved the project as part of its new blueprint for how Britain will use spectrum, is already forecasting what high technology traffic systems will look like. "Sensors in cars and on the roads monitor the build-up of congestions and wirelessly send this information to a central traffic control system, which automatically imposes variable speed limits that smooth the flow of traffic," Ofcom said.

As cars become smarter, states believe they need to make their roads just as intelligent. Transit planners say'smart roads' will prevent accidents from happening, cut down on travel time and help drivers save fuel. Although a few miles of highway in the US have new technology, states need to learn how roads can communicate with self-driving cars from different makers, as there is no standard on how cars receive data. Transit planners say'smart roads' are key for drivers to get the most from their self-driving cars, like Google's (pictured), as this technology would prevent accidents from happening, cut down on travel and save fuel Driverless cars have been taught to drive more like human motorists in an attempt to help them recognize and respond to risks on the road. And many car makers say their self-driving cars will be safer than those with people behind the wheel and will reduce the 35,000 lives lost to traffic accidents each year, reports The Wall Street Journal. However, for autonomous vehicle owners to fully experience the capabilities of their machines, the roads have to learn a few tricks themselves.