The Future of Autonomous Vehicle Infrastructure


The promise of autonomous cars delivering passengers and goods efficiently has ignited consumers’ imaginations, prompting billions in investments. Yet autonomous driving (AD) faces significant hurdles ahead.

Aurora, an AV systems provider, is testing their software with Werner Enterprise tractor-trailers on highway stretches in Texas while FedEx and Uber Freight pilot their own platooning fleets.

Smart Cities

Smart cities are urban development strategies that utilise digital technologies to better deliver government services. A smart city offers its residents, businesses, and visitors numerous advantages from improved safety to lower carbon emissions.

Transportation is one of the main areas where smart city applications can be applied, for instance by using connected vehicles to reduce accidents and congestion by alerting drivers about potentially dangerous situations such as another driver running red lights or someone crossing streets while walking.

Longer term, shared autonomous vehicle (AV) fleets could breathe new life into cities by reducing pollution levels while simultaneously improving traffic flow and public transportation efficiency. If transportation officials start considering SAM issues now, they can prepare for these changes by creating infrastructure enhancements to facilitate shared mobility growth while encouraging it.


Connectivity is of utmost importance in terms of autonomous vehicles. Cities need to equip themselves with fiber and sensor networks, IoT devices, safe public Wi-Fi facilities, and superspeed 5G networks in order to support fleets of AVs that constantly receive and transmit large amounts of data – replacing traditional steering wheels with whatever device the driver wants – placing undue strain on wireless networks.

Autonomous Vehicles (AVs) can harness this wealth of data to make decisions and automate driving, but to take full advantage of this insight they need a fast and secure internet with advanced data analytics for optimal performance.

CAV adoption will likely reduce congestion and air pollution in urban areas by decreasing privately-owned car ownership, thus alleviating congestion. Unfortunately, however, this change could impact job opportunities within transportation – socially disadvantaged groups being particularly susceptible to this impact. To counteract its harmful consequences, governments should institute policies which support CAVs while simultaneously integrating them with current transport infrastructure.

Data Analytics

Autonomous Vehicles must constantly make complex decisions, using sensors and 5G communication modules to do so. As such, they produce large amounts of data which public officials should consider when considering potential infrastructure upgrades.

Street signs and stoplights were designed with human drivers in mind; autonomous vehicles will need to communicate between themselves using protocols that establish traffic priority to function effectively. Such technologies can reduce road accidents, expand highway capacity, and minimize negative environmental impacts in densely populated cities.

Autonomous vehicle fleets will require substantial support facilities to service and charge them, so public officials should keep this in mind when creating infrastructure for these AVs. They should also consider whether private companies operating fleets will shoulder all infrastructure expenses; if this occurs it could speed up adoption; otherwise the public sector should plan ahead for any costs associated with building and maintaining these facilities.

Artificial Intelligence

Autonomous vehicles must process, analyze and transmit massive amounts of data quickly – hence why they require on-board computers with artificial intelligence that make key decisions about when and how to accelerate, brake or turn.

AI systems must also recognize objects and predict their behavior – this cognitive behavior known as “machine learning” forms the cornerstone of autonomous driving technology that is revolutionizing transportation industry.

Even with all of their progress to date, fully autonomous cars remain some time off. There are a variety of factors behind this delay, such as unpredictable urban environments and driving system complexity. Mercedes-Benz recently made headlines when they announced they would assume legal liability for accidents caused by their self-driving cars, taking an important step toward accountability for this technology. Other challenges include cybersecurity risks as well as user acceptance. Once broadly adopted however, autonomous vehicle technology should have profound effects on transportation sector operations.

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