Developing a Smart Transportation System Goes Beyond Intelligent Vehicles
Date: 11/03/2024
While the key to solve today's congestion problem is autonomous cars and EVs, there are additional critical issues that need to be addressed for the success of smart transport systems.
By Carrie Gan
Figure 1 - Is this how the road of the future might operate (Source: Choi_Nikolai adobe stock 556078681)
When discussing the future of smart transportation systems, what exactly are we envisioning? Is it the highly intelligent self-driving electric cars, or just a significant component of a much larger puzzle? To provide a comprehensive answer to this question, it is important to explain the initial intention that drove the development of smart transportation systems.
The process of urabanization is advancing at a rapid pace globally, resulting in densely populated cities and expanding populations. Consequently, the traffic congestion and the challenges of daily commuting, burden countless people around the world. The 2022 Inrix Global traffic survey revealed findings demonstrating that drivers in London experienced an estimated 156 hours of traffic congestion annually, while their counterparts in Bogota wasted 122 hours, highlighting the global impact of this issue1 .
The relentless march of technological development can be attributed to humanity’s continuous search for a more convenient and improved way of living. This persistent search, leads to the development of smart transportation solutions in response to the urgent need to tackle the increasingly complex problem of urban traffic. The pressing need also forced major corporations to invest in autonomous driving technologies a decade ago.
Over the years, it has become apparent that the challenges of attaining autonomous driving are greater than initially foreseen, and it is also clear that solving congestion problems extends far beyond the implementation of intelligence to individual vehicles. In fact, it is essential to adopt a comprehensive approach that encompasses the entire transportation ecosystem, which creates the need for groundbreaking innovations to overcome existing obstacles.
The Challenge of True Vehicle Intelligence
While significant advancements have been made in vehicle intelligence, the dream of achieving widespread autonomous driving remains elusive. The concept of autonomous driving involves various levels, with Level 3 autonomy as a pivotal milestone denoted as ‘conditional autonomous driving’ within the industry
Level 3 autonomous driving signifies an advanced system that can carry out all dynamic driving tasks within predefined operational boundaries. This system can take full command of the vehicle’s lateral and longitudinal movements under specific conditions and eliminates the need for the driver’s continuous engagement in the driving process. At present, the 2024 Mercedes-Benz S-Class is only the car model that has certified level 3 automated driving systems and is currently only approved for use in California and Nevada2 .
The timeline for achieving widespread adoption of advanced autonomous driving remains speculative. In an IEEE survey, nearly half of the respondents anticipated that a majority vehicles sold worldwide would feature autonomous capabilities within three to five years, with 22% expecting to achieve this milestone sooner3 . Over half of the respondents expressed their likelihood of driving a self-driving vehicle within the next five years.
According to Auto2x, a consultancy specializing in automotive technology, it is anticipated the ADAS companies are expected to launch 71 vehicles equipped with Level 3 technology in Europe by 2025. Additionally, it is projected that Level 3 penetration will account for 21.2% of European new car sales during that same year4.
Enhancing Infrastructure Intelligence
Two main technological development paths have emerged in the filed of autonomous driving.: The vehicle intelligence, which focuses on enhancing the capabilities of individual vehicles, and Vehicle to Infrastructure (V2I) plus Vehicle to Everything collaboration (V2X), which emphasize the interaction between vehicles and surrounding infrastructure.
Though there has been significant progress in vehicle intelligence, it is becoming increasingly evident that just depending on this approach has its limitations. Some of the major challenges emphasized by experts include, safety concerns, limitations in the Operational Design Domain (ODD), and increasing economic costs. .
Safety concerns encompass a range of issues, including software and hardware vulnerabilities and the effectiveness of intelligent autonomous driving systems in handling challenging situations like blind spots, adverse weather conditions, and traffic accidents.
The limitations of ODD arise from the limitations associated with the installation of sensors on the vehicle, the detection range,, and the need for synchronization. These factors hinder the accurate perception and positioning in complex environments.
From an economic perspective, ensuring the safety of autonomous driving requires a significant expansion of sensor deployment and redundancy, as well as the incorporation of high-precision maps and similar software and hardware elements. This, in turn, leads to an increase in manufacturing costs.
Due to the challenges encountered, it is impractical to deploy advanced autonomous driving that relies solely on vehicle intelligence for large-scale commercial use. However, autonomous driving based on collaboration between vehicles and the road is a promising alternative.
The Relationship Between Vehicle and Road
Numerous governments and automotive authorities have emphasized the importance of accelerating the development of intelligent networked vehicle-road infrastructure and 5G-V2X Internet of Vehicles (IoV) demonstration networks. The ultimate objective is to enable advanced autonomous driving applications beyond Level 3 by enhancing the integration between onboard intelligent equipment, road infrastructure, and intelligent control facilities.
The concept of autonomous driving, which is based on the collaboration between intelligent vehicles and smart infrastructure, offers a solution to overcome the limitations of individual vehicle intelligence by facilitating the exchange of information, enabling collaborative sensing, and fostering joint decision-making. By addressing technical bottlenecks and cost constraints, this collaborative framework plays a crucial role in contributing to the advancement and widespread commercialization of autonomous driving technologies.
At present, a smart cars can only detect objects in its immediate surroundings and receive traffic updates as external input. However, if intelligent cars and infrastructure systems were combined, it could function like a hive, allowing vehicles to be intelligently distributed in the event of a road closure, preventing any disruptions.
The emergence of high-level smart roads is considered indispensable for developing vehicle-road collaborative autonomous driving and the alleviation of congestion problems. With the increasing prevalence of intelligent vehicles, it is imperative to establish a corresponding level of road support to facilitate the widespread commercialization of collaborative autonomous driving.
Since the early 2000s, there has been a noticeable surge in global interest and investment in smart road infrastructure, highlighting the increasing importance of digitization and intelligence in transportation systems. This trend is expected to continue as smarter cameras and signage are added to highways, along with new technologies such as wireless communications that transmit data to vehicles.
Transportation Diversification
It is important to go beyond conventional concepts of road travel when envisioning the future of intelligent transportation. Advanced modes of transportation, such as flying cars and robot taxis (Figure 2), are gradually becoming more feasible, although they may not be widely available by 2024. However, the continuous advancements in these technologies highlight their imminent arrival.
Figure 2 - Self-driving taxis like this might become a staple of urban transportation (Source:Jason Adobe:71227107)
Imagine the ability to effortlessly summon an electric vertical take-off and landing aircraft, commanding a self-driving robot taxi through a smartphone application, or traveling at supersonic velocities within vacuum tube-based vehicles underground. The domain of futuristic transportation holds the potential for a transformative shift in the way how we move.
The entrepreneurs and government initiatives are driving the development of air taxis, all operating within the framework of “Advanced Air Mobility (AAM).” The Federal Aviation Administration has set a goal of facilitating the implementation of air taxis by 2028, with researchers in Texas leading the development of air traffic control frameworks.
Conclusion
The advent of novel transportation technologies, such as autonomous vehicles, hyper-loop systems, and electric aircraft, promises to revolutionize the way we travel. These advancements will not only enhance the efficiency and safety of transportation but also have far-reaching implications for society. For instance, integrating smart transportation systems require advancements in communication technology to enable seamless connectivity between vehicles, infrastructure, and passengers. Additionally, the vast amount of data these systems generate will necessitate advanced analytics capabilities to derive meaningful insights and optimize transportation networks.
Furthermore, the IoT and IoV will play a crucial role in enabling real-time monitoring and control of transportation infrastructure, ensuring smooth operations and minimizing disruptions. However, to bring this futuristic transportation concept to life, the manufacturing industry must adjust its practices to produce these innovative technologies. This will necessitate the use of advanced manufacturing techniques and a skilled workforce. In general, the impacts of smart transportation technologies will reach far beyond just the transportation sector, revolutionizing various aspects of human society.
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References:
1 https://inrix.com/press-releases/2022-global-traffic-scorecard-uk/
2 https://group.mercedes-benz.com/innovation/product-innovation/autonomous-driving/drive-pilot-nevada.html
3 https://transmitter.ieee.org/pilots-and-drivers-not-included-autonomous-travel-advances/
4 https://auto2xtech.com/level-3-automation-in-1-in-5-cars-in-europe-by-2025/
