After many years of delays, self-driving cars, trucks, and buses are appearing on the roads of major American cities. There are currently autonomous taxis in Phoenix, San Francisco, and Austin, and self-driving trucks in Texas. Washington, D.C. is also testing the vehicles, and it will be interesting to see how they navigate the city’s complicated traffic circles.
As these vehicles become more ubiquitous, though, questions are emerging about how they will reshape urban design and operations —and what cities should do to fully leverage the technology. These new forms of transportation are poised to transform city life and require changes to city streets and traffic infrastructure, but with the right adjustments, autonomous driving could make urban travel safer, faster, and cleaner.
Around 40,000 people die in traffic accidents each year in America, and roughly 90% of the fatalities are due to human error. People make mistakes because of drunk driving, tiredness, usage, or other factors that take their eyes off the road.
Autonomous vehicles have caused accidents, including fatal ones, due to issues like solar glare, camera malfunctions, software errors, and hardware failures. However, these risks are expected to cause far fewer deaths than those tied to human intoxication, exhaustion, or distraction. For all their possible flaws, computer-driven vehicles don’t get drunk, tired, or distracted, and as they become more common, the overall human toll on the roads is likely to drop significantly.
We already are seeing significant drops in vehicle ownership in urban areas, especially among young people. Many people living in central cities are unlikely to own vehicles, relying instead on ride-sharing services or taxis to meet their transportation needs. Autonomous vehicles are expected to accelerate this shift away from car ownership, helping to reduce traffic congestion and lessen the environmental impact of cars and trucks in major metropolitan areas.
As car ownership declines, cities will need fewer parking lots, gas stations, and even streets. In turn, urban planners will be able to shift their focus away from car-centric design and toward human-centered spaces like parks, pedestrian walkways, bike lanes, and entertainment zones.
With an increase in the number of autonomous cars, trucks, and buses, urban leaders can redesign streets for bikes, autonomous delivery, and commuting. There may be less need for streets in their traditional sense, allowing cities to think about urban designs featuring dedicated areas for autonomous vehicles and automated delivery systems or amenities such as bike lanes.
Streets could include designated cutouts for delivery vehicles, preventing vans and trucks from blocking traffic as they often do today. Without proper parking, deliveries frequently disrupt traffic flow, frustrating drivers and slowing commutes. By giving delivery vehicles a place to pull aside, cities could reduce congestion and make driving more efficient and pleasant.
Most cities today use static traffic lights that change on fixed timers, regardless of actual traffic conditions. As a result, drivers often sit at red lights even when no cross traffic is present. By integrating road sensors or using data from navigational systems that already track vehicle locations, cities could adopt dynamic traffic lights that adjust in real time. These smart signals would improve traffic flow and offer a more efficient, convenient alternative to current static models.
Autonomous vehicles will create opportunities to redesign cities with pedestrians—not cars—as the central focus. Contemporary cities devote vast amounts of space to streets, parking, gas stations and auto repair businesses. But with fewer personally owned vehicles and increased reliance on autonomous vehicles, city planners can explore more creative layouts that prioritize walkways, malls, and entertainment zones. These redesigned spaces could feature designated pickup and drop-off points for autonomous vehicles and ride-sharing services, reducing the need for expansive roadways and parking lots.
In cities with widespread autonomous vehicle use, distance may become less of a barrier than it is today. Much like the expansion of railroads and subways once allowed people to move farther from city centers, autonomous vehicles could make long commutes more tolerable by transforming driving into a passive experience. Instead of battling traffic, passengers could work, relax with a movie, or connect with loved ones on the —arriving home refreshed as opposed to angry and exhausted. This shift could expand commuting zones and reduce the necessity of living in central urban areas.
As autonomous technology gains steam, the demand for human drivers of trucks, taxis and ride-sharing services will decline. Cities will need to figure out how to retrain these workers for new jobs. Entry-level positions in taxi driving and ride-sharing will likely disappear, and urban leaders must ensure that transportation-sector workers aren’t left behind as this aspect of the digital revolution unfolds.
Autonomy is advancing rapidly, and city planners must consider how the rise of self-driving cars and trucks will impact city operations, urban planning, and metropolitan design. They should recognize that past approaches will likely require significant revisions and develop new planning models that reflect these emerging transportation changes.
At the same time, leaders should work to increase public confidence in autonomous systems. Even though research demonstrates that autonomous vehicles are safer and cleaner than human-operated ones, many people remain wary and are reluctant to ride in them. A Brookings survey found that only 21% of Americans were willing to ride in autonomous vehicles, with many opposed citing safety and security concerns. As cities adopt these technologies, public education campaigns will be essential to address skepticism and reassure people about the safety and reliability of autonomous transportation.
CESVIMAP communication manager and business development coordinator
Last-mile delivery is the Achilles heel of logistics companies. These kinds of deliveries require a lot of time and labor, and account for up to 28% of the total cost of shipments, according to the research group Euromonitor International. For years now, research has been being conducted into autonomous delivery robots that can navigate 99% of the time without human intervention, aided by an algorithm that locates the most efficient distribution routes. The cost advantage of these robots will come into full play when they reach the economy of scale. According to the consulting firm Atos, more than 60% of buyers would change e-commerce platforms to avoid additional shipping costs.
Delivery robots are designed in an energy efficient way. This means that they optimize routes and minimize energy consumption. Their ability to deliver accurately and quickly contributes to reducing the carbon footprint of conventional delivery methods like delivery trucks.
Compared to traditional vehicles, autonomous delivery robots are inherently smaller and lighter, and they usually drive on the sidewalks instead of on the road. By consuming fewer resources, these robots reduce traffic congestion or the need for parking. They also minimize road wear and tear, contributing to the sustainability of urban infrastructure.
Although large distribution centers provide volume and scale, sending orders to clients “on demand” and in a profitable way is increasingly difficult. The aim of these robots is to boost local trade, offering fast and affordable deliveries for small businesses. By facilitating last-mile logistics, they promote a preference for local purchases. This reduces delivery distances and the environmental impacts associated with long-distance deliveries.
Sustainable mobility seeks to reduce dependence on fossil fuels and to evolve the delivery industry toward more sustainable practices. Many of these robots are designed to be powered by renewable energy, such as solar or electrical. Similarly, as these delivery systems are more efficient, they decrease the required packaging (in plastic, cardboard, etc.).
The cutting-edge technology of these robots includes GPS, as well as advanced sensors and cameras—up to 12—that allow them to see where they are going. They travel at about 4 mi/h (similar to a pedestrian’s speed). This determines the type of products delivered (this must be taken into account when delivering hot food, for example, so that it doesn’t get cold). The robots use artificial intelligence (AI) to generate optimal routes, avoid obstacles, and offer a profitable service with distribution costs that are up to 65% lower than traditional ones. The onboard technology allows them to get around objects and people they may cross paths with and gather information about the distribution process. Users can track the order in real time, as they can see all the robot’s movements until the delivery takes place. The objective? The objective is to use this data to optimize operations and improve client efficiency and experience.
Link to rino.ai
CESVIMAP, Mapfre’s mobility laboratory, is experimenting with this technology, as well as with other autonomous vehicles that are already on the streets of Spain. CESVIMAP has analyzed the Goggo distribution robots, identifying risks and opportunities in their current performance, as well as their road navigation. The company is also behind other projects being researched at Mapfre, such as autonomous shuttles to transport people, developed by the Centro tecnológico de Automoción de Galicia [Galicia Automotive Technology Center] (CTAG).
Starship Technologies: This company is characterized by six-wheel autonomous delivery robots to deliver food and products over short distances. They operate electrically and optimize delivery routes in urban areas.
Nuro: For more than 7 years, Nuro has tried multiple vehicle platforms to understand the autonomy of its robots in the Bay Area of San Francisco, Los Angeles (California), and Houston (Texas). Its fleet consists of several vehicles, each with a characteristic function, developed in a Machine Learning framework to improve their perception and behavior systems.
Kiwibot: This company specializes in four-wheeled autonomous delivery robots, particularly used in food delivery. Its thousands of robots operate in 35 locations and at universities around the world. Kiwibot’s service is available on applications such as Grubhub and Everyday by Sodexo.
Amazon Scout: Amazon’s small six-wheel autonomous delivery robot began operating in in Seattle, with the idea of expanding to southern California, Georgia, and Tennessee. In , the major tech company canceled home delivery tests and relocated the technical team that was running it—more than 400 people.
Amazon Prime Air: Amazon also has a package delivery service using drones. According to the company, drones deliver orders in less than 30 minutes and can avoid obstacles in the environment (trees, bushes, electrical wiring, buildings, statues, etc.) thanks to their sensor and camera technology. Drones currently operate in Lockeford (California) and College Station (Texas), but Amazon has already announced that a third U.S. city will be added in . The service will also make the leap into Europe, specifically Italy and the United Kingdom.
Alibaba: Since , more than 500 driverless electric robots, nicknamed Xiaomanlv or “burritos” in Mandarin, have delivered on university campuses throughout China. To achieve economies of scale, the company has tested these robots on university campuses with busy stations, which receive more than 4,000 packages a day.
Goggo Network: Founded in , the company’s objective was to operate autonomous vehicle fleets in Europe and to contribute to developing the licensing system for their circulation. In , Goggo Network tested the first autonomous food truck driving on the streets of Spain. It collected food from restaurants to then be sold on public roads. That same year, together with Glovo, the company presented its delivery robot in Madrid. In the company canceled all its projects.
These examples represent only a fraction of the technological race to establish delivery robots as the new future of distribution.
However, the deployment of these autonomous robots requires an initial investment, with high testing and manufacturing costs. A new area must be mapped before starting to provide services there to ensure that the robot can travel the route.
When we talk about risks, we are referring to:
Vandalism: Given their autonomous nature, robots may be susceptible to theft or vandalism. To deal with this, they are relatively heavy to collect or move. If someone tries to lift, tip over, or manipulate them, an alarm sounds as a deterrent. Each robot is tracked by GPS with an accuracy of centimeters, and the lid is locked throughout the delivery journey to protect the items it contains. The robots can only be unlocked by the client at the delivery destination using a code.
Obstacles in the environment:: Delivery robots can overcome difficulties navigating through complex urban environments with unforeseen obstacles such as pedestrians, bicycles, or elements on the road.
Regulations: Local regulations aren’t yet adapted to the presence of these level 4 robots in public spaces, which limits their deployment.
Interactions with pedestrians: Some people may feel uncomfortable or unsafe when sharing a space with robots, especially in crowded environments.
Weather conditions: Climate factors such as heavy rain, snow, or strong winds affect the mobility and effectiveness of delivery robots, limiting their operational capacity.
Maintenance and technical failures: Autonomous robots are subject to wear and tear and possible technical failures, which interrupt their delivery operations.
Road safety: Although robots are programmed to comply with safety standards, their low volume doesn't allow us to know how they will interact with vehicular traffic and whether other road users will respect their presence.
Delivery integrity: Guaranteeing safe delivery is essential. What happens if the recipients can't interact properly with the robot or if human intervention is required to complete the delivery?
Will delivery robots revolutionize logistics efficiency? Various companies and research centers, such as CESVIMAP, are currently studying their role in building a more sustainable future, as well as the matter of insuring them.
From energy efficiency to waste reduction, these autonomous robots represent the cutting edge in the convergence of technology and environmental responsibility. They are paving the way to greener and more efficient delivery.
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