Five Key Trends in Transportation Technology: From Automated Vehicles to AI, Advancements Are Remaking the Way We Move

Five Key Trends in Transportation Technology: From Automated Vehicles to AI, Advancements Are Remaking the Way We Move

The transportation industry finds itself at the forefront of a dynamic era marked by unprecedented technological advancements.

By Ben Pierce, David Ungemah, Mike Lewis, Rob Mowat and Jim Hanson


Automated vehicles are reshaping traditional models of transportation, promising enhanced safety and efficiency. Managed lanes are transforming how we conceptualize and utilize road networks, optimizing traffic flow in urban corridors. Electric vehicles (EVs) are marching inevitably forward, becoming an ever-growing presence on our roads. The implementation of cordon-based congestion pricing heralds a new era in managing urban traffic. Moreover, artificial intelligence (AI) and big data are revolutionizing our understanding of transportation systems, empowering leaders to make better-informed decisions than ever before.

The Quiet Integration of Automated Vehicles

Five years ago, fully automated vehicles were being hyped as imminent. A lot of promises were made, many studies were done, and it was the “next big thing.” Then people realized that full automation is actually quite difficult to achieve. The hype faded. But, in the meantime, automation has continued to advance.

The Society of Automotive Engineers classifies cars from Level 0 (fully manual) to Level 5 (fully automated). Multiple carmakers now offer Level 2 vehicles that provide advanced steering and acceleration support, with lane centering and adaptive cruise control. In 2023, Mercedes-Benz rolled out the first Level 3-certified vehicle in the United States, which takes over all driving tasks in certain conditions. In other words, automated technology is steadily moving forward, though perhaps a little slower than the initial hype suggested.

But even at lower levels of automation, the benefits are becoming clear. States and cities should begin to see long-promised safety and congestion improvements, with a steady decline in crash metrics, for example, on roadways heavily used by automated vehicles. It will depend on the level of adoption as well as the readiness of infrastructure. It’s clear, however, that the automated vehicle era has already begun.

How Should the Industry Respond?

1. Prepare the road network. Transportation officials need to assess their roadway networks and determine which roads are likely to be part of the use cases for Level 2 and Level 3 vehicles. These often are interstates or four-lane divided highways. After the roads are identified, it’s important to ensure they’re in a good state of repair, with lane striping that’s reflective and easy for vehicles to identify.

2. Pay attention to available vehicle features. Fleet owners replacing or adding vehicles should stay informed about the latest technology. It’s unlikely the expense and availability of Level 3 vehicles will make them viable fleet options for the near future. But there are many safety improvements in Level 2 vehicles—adaptive cruise control, collision warnings, blind-spot detection—that hold the potential to improve safety metrics for fleet owners. Whether every fleet needs these features depends on how the vehicles are used, but owners interested in improving their fleets should at least be aware of the options available.

3. Track performance metrics closely and adapt accordingly. As automated vehicles become more common, North America will be able to quantify the actual effects of automated vehicles and compare them to what was predicted. It will be important for departments of transportation and municipalities to pay close attention to changes in crash metrics, congestion levels and more.

The Rise of Cost-Effective Managed Lanes

Managed lanes are not a new concept. The first priced-managed lanes were opened in 1995. In the early days of managed lanes, the technologies and deployments were very similar to those used for tolling. These systems tended to be “infrastructure centric” with costly mechanisms to collect fees. In particular, toll roads frequently rely on overhead gantries equipped with RFID readers and overhead cameras to capture front and rear license plate images. If a toll isn’t collected by transponder, then the license-plate capture provides a mechanism for enforcement (or a “pay-by-plate” alternative). This mechanism not only requires substantial capital equipment for overhead installation, it also entails substantial ongoing operations costs for image review.

In the last few years, however, a necessary and desirable divergence has begun to emerge. New and existing vendors have been refining their technology to appropriately scale toll-collection requirements to managed lanes. In short, “infrastructure-light” applications have been introduced that enable fee collection at a much lower operational cost. Colorado was the first state to introduce pole-mounted, side-fire cameras on managed lanes. This eliminated costly overhead gantries dedicated to camera systems.

Now, new entrants to the market using machine learning have changed what it means to capture a license plate. Instead of hoping for one good, complete image of the plate, new technology uses a series of camera shots, matched with algorithmic fingerprinting of vehicle characteristics, to yield a license plate image that can be assembled in the cloud, reducing operational costs and enhancing enforcement.

The result is a new technological paradigm that promises more-rapid deployment of tolling equipment at a substantially reduced overall capital cost. This could make the difference for marginally viable managed-lanes systems and is particularly helpful for agencies exploring and developing their first toll systems.

How Should the Industry Respond?

1. Conduct a comprehensive managed-lanes system plan.This plan bridges the planning, environmental and systems-engineering processes to guide the agency and industry through upcoming managed-lanes projects, including their goals and objectives, and the parameters by which decisions will be made. Many states, including Colorado, Minnesota and Florida, have developed such plans that can serve as a go-by for other states.

2. Release a Request for Information (RFI) on new practices for toll collection. Vendors are constantly developing new technologies and procedures for collecting toll revenue. An RFI process gives the state agency a formal pathway for vendors to articulate their technologies as well as advise the agency on procurement requirements, specifications and other instructions that may stand in the way of procuring such systems.

3. Eliminate technical specifications and requirements biased toward legacy toll-collection systems. Agencies must avoid getting too detailed on infrastructure requirements, including overhead gantries, median mounts and other details. Instead, offer system integrators a results-oriented approach that allows the agency to consider alternative technologies in a fair and competitive environment.

4. Keep in mind a potential segue to more-expansive use of road pricing and Road Usage Charging. As managed lanes become more common, we may begin to see a movement toward greater acceptance of paying for transportation based on facility type, location and demand coupled with visible improvements in travel times, speeds and mobility. As travelers continue to benefit from priced facilities, they could increasingly support the rationale and benefits of moving away from a revenue model based on the fuel tax to one based on road usage.

Start of Cordon-Based Congestion Pricing

After years of planning and preparation, the MTA Board of Directors voted in November 2023 to advance a tolling structure as recommended by its Traffic Mobility Review Board, beginning the final approval process as required by New York’s State Administrative Procedures Act.

The NYC CBD Tolling Program is unique and will be the first of its kind in many respects. Unlike other tolling programs in North America, the NYC CBD program isn’t tolling a specific roadway but an area of lower Manhattan. Vehicles entering the toll zone from any roadway will be assessed a fee once per day. Fees are being assessed through a combination of technologies that leverage video and image-processing algorithms.

How Should the Industry Respond?

1. Explore the new tool in the toolbox.Most mature major urban centers in North America have lost the ability to expand vehicular capacity through expansion of their highway systems. Some form of demand management will be necessary to maintain or improve mobility and maintain economic vitality. Cities that may be interested in replicating New York’s program should begin planning and discussions now.

2. Plan for equity impacts. Congestion tolling can’t be considered without a careful examination of equity impacts. It’s viable in NYC because of the strength of the city’s mass-transit system, which is used by most commuters to lower Manhattan. But even with this advantage, careful consideration was required to examine and plan for the impacts on disadvantaged communities. The same will be true of other cities, who should proactively engage communities as part of any work toward congestion tolling.

The Inevitability of Electric Vehicles

The EV industry has seen enormous growth in recent years, driven by social action, environmental concerns and government regulation. Now that the industry is past the early adoption stage, consumer demand will likely moderate, though it will still be very strong. EVs also have seen rapid technological change and innovation, with improved range and reliability as well as new capabilities such as vehicle-to-vehicle or vehicle-to-grid power.

With these advancements and government encouragement, many vehicle fleets have been steadily transitioning to EVs in recent years, and that momentum shows no signs of slowing. Transit agencies have been significant early adopters, but there also will be rising adoptions in sectors such as ports, airports, municipalities, waste haulers and others. With costs dropping, and availability and reliability increasing, more fleet managers will see a viable financial case for making the switch.

As more drivers rely on EVs, charging networks will also necessarily expand. Drivers will be looking for easier ways to take their EVs on vacation or trips, requiring chargers at hotels, in tourism locations, at national parks, etc.

How Should the Industry Respond?

1. Start thinking about corridor planning for freight vehicles.Initially, much of the attention has rightfully been on easing the path for passenger vehicles. But EVs are poised to also transform the freight industry. Planning for the needs of these heavy-duty vehicles should be a high priority in the coming years. Much more than just installing chargers at truck stops, this will require complex discussions about energy availability, real estate and capacity. To avoid delaying rollout of these technologies, discussions should be ongoing now.

2. Stay apprised of emerging technologies. Things that weren’t possible a year ago are becoming possible today, and capabilities are changing very rapidly. Barriers to adoption are shrinking as costs fall and range increases. Many fleet operators may find that it now makes sense to consider a transition to EVs.

3. Continue community-readiness planning. Many questions are being asked: How does my city provide community charging to those without access at their home? What’s the role of the private sector? Why does that neighborhood get a charger and this one doesn’t? Proper EV planning at the city or regional level will be key to ensuring the right policies are in place, particularly to access federal funds as the National Electric Vehicle Infrastructure program continues.

4. Update existing transition plans.Agencies with existing transition plans for moving to EVs should invest time in reviewing and updating those plans to determine if new and better options now exist.

Impact of AI, Machine Learning and Big Data

During the last decade, new data sources have dramatically increased available information. Such data have the potential to allow transportation engineers and planners to better plan, design, operate, manage and maintain transportation infrastructure and systems. However, because of the sheer volume of data, transportation professionals have struggled to extract meaningful insights.

Now, the added tool of AI can be used to efficiently process this tremendous amount of information and gain meaningful insights in a timely manner. We’re already seeing examples of how AI and data are leading to more proactive transportation decisions. Google Green Light applies AI and crowd-sourced data from Google Maps to model signal operations and provide recommendations to optimize traffic flow. Similarly, Axilion X Way uses AI to assess traffic data and provide recommendations to optimize signal operations based on user-selected priorities. And Rekor Command assesses multiple real-time data feeds using AI to enhance traffic management and incident response.

How Should the Industry Respond?

1. Keep your eye on the goal. While AI holds tremendous promise, it’s important to identify the outcome you’re hoping to achieve and prioritize that. Will the AI-based solutions proposed or considered make a meaningful contribution to achieving that benefit? There won’t be any shortage of solutions available; it’s critical to ensure the ones chosen are making the most impact.

2. Start with better data. While there are many cloud-based data sources available, they all have limitations. Supplementing this data with traditional sources such as detector-based data can result in better insights. After data are gathered, accurate and meaningful AI-driven analytics also requires standard formatting of data. This formatting, combined with sharing public data through a data exchange, will make it much easier for actionable insights to be generated.

3. Rethink how data are obtained and analyzed. Traditionally, it has been the practice for organizations to collect, own and analyze their own data. New big data sources, easy access to data through the cloud, and various entities developing AI applications to analyze the data are resulting in changes to how data and insights are accessed. Organizations will have to rethink practices for obtaining data to capitalize on opportunities with third parties. At the same time, standards for those aggregating and analyzing data will need to be in place to ensure quality, as their outputs are increasingly relied upon to operate and maintain critical infrastructure.

All authors work for HDR, including Ben Pierce, mobility and operational technology services director; David Ungemah, managed lanes and alternative revenue practice lead; Mike Lewis, principal program manager (in charge of the NYC congestion pricing program for HDR); Rob Mowat, zero emissions mobility practice lead; and Jim Hanson, senior transportation technology lead.

About Ben Pierce

All authors work for HDR, including Ben Pierce, mobility and operational technology services director; David Ungemah, managed lanes and alternative revenue practice lead; Mike Lewis, principal program manager (in charge of the NYC congestion pricing program for HDR); Rob Mowat, zero emissions mobility practice lead; and Jim Hanson, senior transportation technology lead.

The post Five Key Trends in Transportation Technology: From Automated Vehicles to AI, Advancements Are Remaking the Way We Move first appeared on Informed Infrastructure.

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