Understanding Tech Trends for the Future of Transportation
Pooya Najaf, PhD, PTP, a key team member of SEPI’s Traffic Engineering group, attended the Transportation Research Board (TRB) 98th Annual Meeting in Washington, DC. TRB is an annual conference that attracts more than 14,000 transportation practitioners and researchers from all around the world.
Pooya is currently serving as a committee member of Transit Capacity and Quality of Service that aims to update TCQSM. He is also involved in many other research activities, such as Travel Forecasting committee and NCHRP projects that aim to update Highway Safety Manual (HSM).
Here Pooya shares some of the most interesting topics discussed in the TRB that will change our future:
Connected & Automated Vehicles (CAVs)
CAVs are one of the most interesting emerging technologies that are broadly discussed among researchers, professors, tech firms, and the automation industry. CAVs are predicted to change the future of the transportation in many different ways:
Traffic Engineering: traffic flow theory, that is the basis of our traffic engineering knowledge, will be impacted by the CAV market expansion. V2V (vehicle-to-vehicle) and V2I (vehicle-to-infrastructure) communications will help drivers or driverless vehicles to make faster, safer, and more reliable decisions. For instance, the headway between two vehicles in a platoon will be significantly reduced by these technologies. The lower the headway, the higher the capacity of the road. Therefore, our understanding about LOS (level of service) and highway capacity will change significantly. The Highway Capacity Manual and Highway Safety Manual will need to adjust for these technologies.
Roadway Design: CAVs will help to make faster decisions. The faster the decision, the lower the reaction time. Lower reaction times will then change our standards to design vertical and horizontal curves in our roadway system. CAVs can help roadway engineers to design more efficient roads. On the other hand, the V2I communication requires us to follow a same set of standards in roadway design manuals. For instance, the curbs, pavement markings or even traffic signs will be detected by CAVs in their HD map technology. This requires us to have a set of standards, approved by FHWA or USDOT, that can serve as a common language between roadway engineers and the CAV developers.
Transportation Planning: CAVs consume less energy, produce less GHGs (greenhouse gasses), and increase safety. They can even change their path intelligently to take a shorter distance. Our transportation planning criteria in terms of air quality, environmental impacts, efficiency, accessibility, equity, and safety will be significantly impacted by these technologies.
Gold or oil might have been the most valuable commodities traditionally. But we are living in a world that data has already become the most valuable product. Big data is the hottest topic between transportation researchers. Big data is not only used when we need to look up some information in Google, but also when we want to find the hot-spots or congested roads in different TODs (time of the days).
Many data initiative firms have started to develop useful transportation data for agencies and consultants. Location information data, extracted from cell phones, is being used to estimate the travel time, traffic volume, reliability, transit share, ODs (origin destination data), and speed data.
Artificial Intelligence (AI)
AI is another hot topic in transportation engineering. AI helps practitioners to solve problems and equations faster than ever. AI helps engineers to model the most complicated engineering scenarios.
AI is actually a broad keyword to describe a knowledge that combines computer science, mathematics, and statistics. AI makes it possible to send a robot to a field study and ask it to perform a complete bridge inspection, using image processing techniques. AI makes it possible to avoid crashes at the very last moment in the new generation cars. AI allows us to communicate with cell phones and ask Siri to process our voice through text mining and for navigation purposes.
CAVs, AI, and Big Data can all be combined to form a very smart city. Vehicles can move more efficiently in a smart city. For instance, imagine your smart car arrives an intersection where the signals and detectors can predict your arrival time, speed, acceleration, and path. Smart city technologies would make it possible to drive through the intersection smoothly, without stopping, since the detectors have already coordinated your arrival time with other competing vehicles to make sure there is no conflict between your paths. Driving behind a slow driver while they are occupying the high-speed lane will not happen in a connected world, where traffic control devices can send orders to the connected vehicles.
Shared mobility covers a very broad concept, from a simple bus or a public scooter in downtown area to a high-speed flying car that can serve as an emergency ambulance. The whole concept behind the shared mobility is that users can still make efficient, reliable and convenient trips without owning a private vehicle.
Carpooling is a very basic example of shared mobility. The future smart cities will be designed in a way that communities (or public government) will own reliable smart and connected vehicles that will serve based on an on-demand (demand responsive) service. Users may take a shared vehicle to get to gym and use another shared vehicle to get back home without any delay in their travel time estimation. Planners expect a higher rate of shared mobility in metropolitan areas.
Many other emerging technologies have been introduced by researchers, engineers, and practitioners. 3-D visualization techniques can significantly change our standards and perceptions in the near future. Flying drones and their capabilities in terms of transportation and data collection are another emerging technology. Managed lanes, reversible lanes, tolling, pricing policies, and telecommunication are some other interesting topics in transportation.