Intelligent Traffic Management Systems
Over the recent years which have seen the spread of technological developments to most parts of the world, there is a steady rise in the number of people who conduct their daily movements with vehicles. Vehicles powered by gasoline, diesel and fossil fuels are gradually being replaced by futuristic vehicles powered by solar energy, electricity and even water, in a bid to forestall the effects of greenhouse emissions by the older vehicle models on the ozone layer. Once upon a time, the swing of a police baton, an upraised hand belonging to a traffic beat cop or the upward, aloft position of a red, hexagonal traffic sign with the word “STOP” in bold print was enough to control traffic flow at a busy intersection. Unfortunately, the regular updates in road construction have not translated into more modern and equally nuanced systems to man the complex vehicles plying the roads. Without an efficient, greener traffic management system to keep up with increasingly congested roads, operations utilizing vehicular movements would become laborious and result in a net negative for the environment.
The solution? Enter Intelligent Traffic Management Systems (ITMS, as referred to in some circles). In simple terms, Intelligent Traffic Management Systems refer to any kind of contemporary smart solution or technological adaptation that provides innovative, technology-driven services related to the organizing, arranging and controlling of vehicular, cyclists and pedestrian traffic in a bid to enable safer, more orderly and more effective use of road transport networks.
Components of an ITMS
An Intelligent Traffic Management System requires an ecosystem of connectivity, hardware and software technologies involved in data collection, data transmission, data analysis and processing, data conversion and information transmission to road users.
a. Data Collection:
The collection of data is an important function in the management of traffic, as the retrieval of data obtained through hardware located in and connected to road network forms the basis for prediction and analysis of traffic conditions. Hardware components collecting data for analysis do so via surveillance, traffic count, speed tracking, pinpointing areas recording traffic lags, delays and congestion, evaluating vehicle parameters and recording road conditions, amongst other methodologies.
b. Data Transmission:
Data obtained through the above listed mediums is transmitted securely via specified, highly-protected wireless pipeline to public and private traffic management system centers for storage and analysis.
c. Data Analysis and Processing:
Using complex optimization algorithms, machine learning, deep learning technologies, cloud computing and edge computing, massive proportions of retrieved data are processed, structured and checked for errors before being converted.
d. Data Conversion:
After being analyzed and thoroughly checked, processed data is converted to relevant, intelligible information in the form of statistics, graphs, gradient and predictions which when interpreted provide real-time traffic information for end road users.
e. Information Transmission to End Users:
At this point, interpreted data which is essentially real time traffic information is disseminated to everyday road users via different modes of mass communication including mobile apps, traffic advisory radio, cellular-phone broadcast messages, variable direction signs and text panels, news broadcast, pre-trip information carriers such as bulletins and newsletters and individual driver information systems amongst other media platforms. After all, transportation systems are essentially networks that thrive on information. The knowledge obtained through disseminated information can help road users identify critical traffic situations and decide on the most appropriate control actions to be taken.
Intelligent Traffic Management Systems adapt information and communication systems through the principal elements of technology; hardware and software, to create innovative solutions for traffic flow and management.
Hardware components that facilitate ITMS include:
Sensors (air quality sensors, temperature sensors, IoT sensors)
Inductive loops
Microphones
Automatic Identification Data Collection tags
Edge devices
Anchor sensing nodes
Ramp meters
Connected video cameras
Connected traffic light systems etc.
Software mechanisms involve in ITMS include:
Big data and predictive analysis tools to plan and optimize traffic flow
Artificial Intelligence
Machine and Deep Learning Technologies
Cloud computing technologies
Algorithms
Wireless Networks
Edge computation
Geographic Information Systems
Location-based services
Global Positioning System (GPS)
Bluetooth systems
Traffic data platform/data lakes
RFID (Radio Frequency Identification and Data collection) etc.
A combination of the above systems, along with connectivity, allows the road to:
Detect incidents (such as car crashes, road blockages, illegal parking and so on) when they happen.
Transmit alerts to the main Intelligent Traffic Management System.
Automatically execute a sequence of already programmed follow up actions such as providing public transportation apparatus with alternative routes, dispatching emergency traffic services, updating nearby drivers amongst other control actions.
Advantages of an ITMS
The benefits of introducing smart technology to prevailing traffic management systems can only be described as enormous.
The use of predictive planning techniques and proliferation of real time dissemination of traffic information greatly reduces laborious movement and logistics. The restoration of orderliness and free flowing vehicular movement to highway networks enhances day to day mobility and becomes a source of convenience for road users. For instance, the accurate prediction of future traffic flow helps synchronize traffic signals to ensure the smooth flow of the overall traffic of the city. An update on travel time can help people select the mode of transportation that can help them reach their destinations as quickly as they can. This is especially important for public transportation and regional emergency response systems.
Traffic congestion often occurs when road usage increases. However, the quick detection of accidents, delays and other road incidents; creation of priority for emergency vans and reduction of vehicular waiting time at traffic signals enabled via smart traffic management mechanisms help to decrease and to a large extent, avoid traffic congestion.
Intelligent Traffic Management Systems, when deployed, have a domino effect on every sphere of the society and economy. A reduction of traffic congestion, for instances, translates to a reduction of queues, increased transportation speed, reduced travel durations; which in turn leads to a reduction in commuter fatigue; directly resulting in reduced stress levels causing greater productivity and operational performance for citizens and increased tourism by transients. In essence, wise allocation of state resources to smart traffic management influences economic development.
Intelligent Traffic Management Systems are a notable component of safer and greener urban environments. All of the features of a smart traffic management system are designed as traffic congestion control mechanisms. Sustainable transportation have a lower incidence of CO2 emissions per journey and greenhouse gas proliferation. As a result of lesser time wasted in traffic congestion, air quality is safer; pollution is reduced; carbon footprints are reduced; billions of gallons of fuel are saved; road infrastructure is less prone to damage due to fewer occurrences of natural disasters; climate neutrality is achieved and the world is a better place.
Challenges of Intelligent Traffic Management Systems
Several concerns have been raised about the use of smart traffic management systems and the resultant impact on urban transportation systems.
Existing traffic management and control systems in many localities show higher rates of error when handling copious, critical amounts of traffic and traffic conditions. Due to the constant movement of vehicles in large-sized urban areas; accuracy, reliability and adequacy of data collected by the limited-capacity current traffic control systems can be in question. Without accurate data collection, real-time traffic advisory is unreliable and can end up being ignored by road users.
Flowing from the advent of rapidly evolving and heterogeneous traffic management architecture (e.g. new route guidance systems), there is a need for increased support tools to help cope with the information extracted from these facilities and resulting traffic management plans. Furthermore, due to the unequal rate of standard developments for different components of the transportation system, more collaborative research needs to be done for ITMS mechanisms to work with all devices.
Privacy issues are also a growing concern. With the advent of vehicle to vehicle communication, vehicle to infrastructure communication and the use of Bluetooth, cellular networks and GPS tracking to transmit traffic information to traffic management centers, all data collected from vehicles must be passed on via highly secure routes. If not done securely enough, huge tranches of data potentially containing sensitive information about individual vehicles and the identity of their owners can be intercepted by black hackers and identity thieves. ITMS research must also include measures for safety and cyber-security.
Day-to-day operations of traffic management centers still involve human intervention. Most centralized traffic control systems are being manned by human personnel, irrespective of how sophisticated and advanced such systems are.
The Future of ITMS
With the growing inroads made by AI and machine learning research, it is expected that Artificial Intelligence systems capable to reason about human traffic behavior, in the manner of human expert traffic operators, would be developed and deployed. In the meantime, the following inventions are already coming to life in advanced societies:
Smart junction optimization systems
Smart parking systems in communication with driverless cars
Dynamic, smart traffic light signals with custom controls
Multi-agent, autonomous traffic information advisory systems (think ChatGPT, but for transportation)
Advanced, real-time safety and pollution analytics
Electronic road pricing and toll payment for smart cars
These options once sounded futuristic and like scenes from science fiction movies, but the future is never ever as far off as it seems.