Increased highway congestion is leading to alternative methods of transportation, such as mobility as a service (MaaS), as a means of traffic management.
When it comes to highway traffic management, transportation agencies must consider a number of things before deploying a solution. They must focus both on meeting short-term challenges, while also keeping in mind future changes and longevity.
Traditional traffic management systems
are based on both hardware and on intelligent video analysis software. These systems generally consist of information collection modules (e.g., sensors, cameras, weather stations, license plate readers
, etc.), information to users (e.g, information panels, call centers), information processing (e.g., travel times, service levels, etc.) and management centers that collect, process and distribute useful information for road users.
Traffic management has become increasingly complex, though, as rapid urbanization results in increased road congestion. It has caused a “change in behavior on how people commute and move,” according to Jose Carlos Riveira, Strategy and Portfolio Management at Kapsch TrafficCom
“This increasing complexity is moving agencies into the need of better understanding the new patterns and challenges of how people are moving and how to manage demand,” Riveira said.
This is forcing agencies to address the demands for which access control, air quality control, vehicle miles travel, incentives or collaborative routing have become new aspects and techniques that will soon be incorporated into traffic management.
“For that the transportation agencies need higher automatization of tasks that can leverage available technologies to facilitate operator’s work; this is related with improvements in decision-support, forecasting and real-time dashboards to drive awareness and decision making,” Riveira said.
Public space assignment, such as parking spaces
and streets and roads, and resource availability are also becoming more critical in highways and city accesses, Riveira added.
To address some of these challenges
, transportation agencies need to increase the digitization of their services so that information is constantly being gathered and can be directly accessed by users. Agencies must also be able to analyze this large amount of collected data in real time in order to create actionable intelligence that can improve traffic situations.
Some of the most important transformations nowadays, however, deal with emerging alternative transportation media, micro mobility (e.g., bike sharing, e-scooters, etc.) and mobility as a service (MaaS)
— eventually also with connected cars and autonomous vehicles.
Regarding traffic managers and motorway concessionaires, José Luis Añonuevo, GM of Traffic Management Systems Operations at Indra
believes that they will evolve toward a MaaS model for car users. This will include smart tolling solutions on highways for access to certain routes or modular pricing and real-time payment based on road conditions, the day or time, vehicle occupancy, etc.
Furthermore, as mobile communications become more secure and the Internet of Things (IoT) drives advancements in connected and autonomous cars, these things will radically change the highway travel experience. It will also give users access to more traffic information and provide more assistance for safer driving.
These transformations are being driven, in part, by the users’ desire for more convenient and easier to manage and control modes of transportation. Continued technological developments will allow people “to enjoy transport without technological barriers, assisted with information in real time, adapted to their preferences and needs at every moment, optimized and with a lower cost,” Añonuevo added.
“This new reality will lead transport operators to carry out a more intelligent, intermodal and optimized management of their services,” Añonuevo said. “Bus, subway or train operators will shortly have an integrated route management system, centralized and connected with information from travelers and traffic, in which machine learning and big data will facilitate the redefinition routes in real time or generate customized routes for users of other means of transport.”