Implementing an Intelligent Transportation System: A Bottom-Up Approach to Value Creation

Every year, the French begin their mass migration from the northern regions to the coveted south. Exuberant and excited, they pack up their belongings (kids and pets included) in their vehicles and buckle up for a journey to the azure beaches of Le Sud.

Most journeys happen without a hitch. Unless it’s the first Saturday of the week when July meets August — a notorious date when half of the country races back north, whereas the other half attempts to make it down south.

Known as the “jam of crisscrossing,” this travel pattern has been bringing highway A7 to a standstill in both ways for nearly 30 years.

Similar traffic clashes happen every day in most every big city. Morning and evening rush hours, scheduled deliveries, school drop-offs/pick-ups — humans move around in predictable patterns, even though they are well aware of the risks of getting stuck in a jam.

You can’t break these patterns — but you can fix the problems they produce.

That’s what intelligent transportation systems intend to accomplish

What is an intelligent transportation system?

Transportation systems have many moving parts (quite literally). Thus, there’s no clear-cut intelligent transport system definition.

Think of an intelligent transportation system (ITS) as an umbrella term for the cohort of emerging technology systems and solutions for enabling coordinated, efficient, and “smart” transportation management across different modalities — car, rail, sea, and public transport.

An ITS is modular and can feature any number of the following:

• Traffic signal controls
• Traffic management systems
• Freeway management systems
• Transit management systems
• Road incident management systems
• Traveler information services
• Emergency management services
• Advanced traffic analytics
• Electronic fare payment systems
• Public transport management systems
• Connected car infrastructure
• Road network performance monitoring
• Railroad grade crossing safety systems
• Commercial vehicle operations systems

Intelligent transportation systems can be designed to facilitate a single means of transportation (e.g. car traffic or railway systems) or multi-modular journeys and complex passenger transportation scenarios. What stays the same in each case are the outcomes an intelligent transportation system is meant to accomplish — improve the safety, reliability, efficiency, and quality of transportation infrastructure.

What makes transportation systems intelligent?

Unlike earlier predecessors, an intelligent transport system comes with:

• Greater connectivity through 4G/5G, telematics, and V2X standards
• Better sensing capabilities courtesy of IoT devices and advanced controllers
• Robust analytics, leveraging the above data and augmented by predictive algorithms

This combination of technologies enables traffic managers to include, engage, and supervise road users through a variety of channels such as connected car systems, personal mobile devices, and smart road infrastructure.

This, in turn, helps rationalize the use and performance of existing transport systems and optimize the construction of new infrastructure.

New actors are entering the transportation market — free-floating carsharing services, electric vehicles, and digital mobility platforms, among others. As this happens, intelligent transport systems will take an even more crucial role as city-wide orchestrators, ensuring that all its users, no matter the mode of transportation, enjoy high levels of physical safety, convenience, and efficiency. An intelligent transportation management system should effectively generate profits within its area of responsibility and offset the carbon impacts of operating a large transport infrastructure.

Benefits of intelligent transport systems

• Global management of traffic flows across all types of multi-modal journeys. With great visibility and granular controls, logistics operators can precisely manage traffic and prevent congestion through intelligent planning, scheduling, and real-time controls.
• Reduction in road accidents. Road traffic accidents take thousands of human lives a year globally. Injuries from road events cost an estimated 2% of gross domestic product in EU countries. Traffic management and intelligent transportation systems can reduce the death toll through implementing targeted controls against speeding and distracted driving.
• Progressive decrease of emissions. The majority of countries have pledged net-zero emissions targets. Transportation accounts for one-fifth of global CO2 emissions, and passenger travel accounts for 60% of total transportation emissions. Better traffic management can reduce congestion in urban areas and thereby reduce pollution. Additionally, the introduction of smarter public transport options can prompt more road users to opt for alternative transportation means, including those powered by renewables.
• Better capacity management. An intelligent transport system can provide managers with a consolidated view of traffic flows so they can develop more effective routes, drive the use of public transport services through multi-modal traveler information systems (TISs), and add innovative mobility services to the smart transportation repertoire.
• Unlock new pockets of value creation. Private mobility as a service (MaaS) providers, offering carsharing and bike rental services, among others, are drawing away profits from city authorities. At the same time, they are constraining effective traffic management due to a lack of data sharing. Integrating these parties into your ITS will not only improve visibility (and thus oversight) of their operations but can also prompt new strategic partnership opportunities.

How to approach the implementation of an intelligent transportation system from the bottom up

Intelligent transportation systems are meant to serve one underlying purpose — generate value for end users by delivering better service. Cost optimization, carbon reduction, and profit generation will fail to follow unless your system provides tangible value for road users.

Importance ratings of transportation aspects, 2021 and change vs 2018

Source: McKinsey — Urban transportation systems of 25 global cities

1. Start with collecting and consolidating data

Managing transportation is already a digital activity. Yet many operators rely on disparate systems for routing, scheduling, traffic management, and road infrastructure maintenance. This, in turn, prevents managers from seeing the bigger picture of gains and inefficiencies worth exploring.

An intelligent transportation system is a mass data aggregator, infused with analytical capabilities for translating scattered insights into a roadmap for improvement.

As part of the pre-planning stage, your task is to locate:

• Missing internal and historical data points
• Subsystems lacking connectivity
• External sources required for better analytics and planning

Intelligent transport thrives on data. And there’s plenty of traffic data sources you can leverage:

• Connected CCTV cameras
• IoT devices and road sensors
• Public transport telematics
• Connected cars data
• Floating car data
• Floating cellular data
• In-vehicle driver consoles
• Toll payment devices
• Public weather data
• Geographic information systems (GIS)
• Road infrastructure controllers
• Government-backed data access and exchange programs

The above can be obtained either directly from the source or via public and private APIs offered by intelligent transport systems companies.

What’s even better is that ETSI is working on standardizing transport data formats to ensure even better interoperability in the present and future. This means it will become easier to commission data and exchange it with other participants in the transportation ecosystem, be they public authorities or private intelligent transportation systems companies.

Currently, ETSI is working on a new set of standards and technical specifications for:

• Autonomous driving (platooning, C-ACC, and maneuver coordination services)
• Sensor sharing (collective perception and cooperative observation services)
• Integrated transport solutions for supporting smart cities
• Infrastructure-based services (SPAT, MAP)
• Roadside platform architectures
• Digital maps
• In-vehicle platform architectures
• Urban mobility management solutions (VRUs)
• Freight and fleet management solutions

Once you have identified the required data sources and integrations, you need to build a technical process for operationalizing the incoming intelligence.

Data management framework for an intelligent transportation system

2. Take charge of traffic management

Effective traffic management is at the core of every effective intelligent transportation solution. If you cannot grapple with the situation on the roads, how can you persuade people to opt for public transportation? Likewise, it’s hard to stomach higher tolls or enjoy real-time road traffic information when it’s jam-o’clock all day.

Focus on translating obtained knowledge into improved traffic flows to reduce travel times, congestion volumes, and public frustration with the state of local transport infrastructure.

A comprehensive traffic management system should include the following elements:

• Management and collection of traffic source data
• Fusion and analysis of traffic data
• Real-time traffic data publication
• Information systems for travelers
• Remote, real-time traffic management

What type of data do you need to power the above elements?

• Floating car traffic data or statistics based on automatic number plate recognition (ANPR) data to understand common patterns in user journeys
• Historical traffic data to understand how traffic circulation changes under different conditions and pinpoint when and why most congestion occurs
• Passenger counts on public transport across different transport modes to better align schedules and routes

Your goal is to collect sufficient data for establishing common origin–destination travel flows. Then model various scenarios for improving road infrastructure to facilitate common journeys.

To illustrate this, let’s take a look at several examples of successful intelligent transportation systems.

Orange County authorities were facing persistent congestion along the Santa Ana Freeway, State Route 22, State Route 57, and connecting streets in Anaheim’s Commercial Recreation Area. To solve the problem, local operators first analyzed data from existing information systems on a regional level to better understand congestion patterns. Then they used the results of this analysis to devise a better traffic management strategy at a central level.

Today, local operators use centralized traffic signal management to control 180 traffic signals in the region. They also provide real-time traffic information to guide motorists via 12 electronic message signs. Plus, they use a low-band highway advisory radio channel to broadcast real-time traffic and parking information. The implementation of this integrated traffic management system has substantially reduced delays and helped alleviate congestion in the area, especially during large public events.

At Intellias, we also helped a Dutch transportation company implement a pilot IoT-based smart data traffic solution for managing road congestion. The solution aggregates data from car sensors, road cameras, weather stations, mobile devices, and traffic feeds to a cloud-based analytics platform. Processed data is then sent back to motorists’ smartphones and regional traffic management centers to alert in real time about road hazards, accidents, traffic jams, and other road incidents.

3. Integrate data from connected vehicles

Connected cars are hitting the global roads in large quantities.

For traffic managers the paced yet imminent arrival of connected cars presents major opportunities to orchestrate traffic flows. Equipped both with cellular connectivity and vehicle-to-everything (C-V2X) communication protocols, connected vehicles can accumulate, transmit, and exchange a wealth of data with:

• Connected road infrastructure (V2I)
• Other connected vehicles (V2V)
• Any other digital services via built-in device-to-cell tower communication

Such extended communication capabilities provide vehicles with real-time situational awareness. This means your car can automatically adjust the route based on a real-time update. Or it can prevent you from accelerating if a connected road sign urges you not to.

In the future, connected car technology can also enable platooning for commercial vehicles — a semi-automated way of dispatching truck convoys across routes, aimed at reducing CO2 emissions, travel times, and road accident rates. EU countries plan to roll out multi-brand platooning technology as well as to standardize communication protocols by 2022.

Ultimately, both commercial and passenger connected vehicles can provide traffic managers with new data on how, when, and where vehicles travel. At the same time, connected vehicles can reduce dependence on a centralized traffic control center, as they can communicate independently with other vehicles, infrastructure, road services. Such decentralization, in turn, reduces latency and eliminates operational risks associated with having a single point of failure (the traffic management center).

Individually, counties in the US are actively investing in connected infrastructure. New York City recently pioneered a Connected Vehicle Pilot Program, aimed at analyzing data from connected vehicles and accelerating the implementation of new V2X initiatives. Authorities in the Netherlands are extending the use of smart traffic lights, capable of sending status information to connected cars and autonomous vehicles, to 60 new areas in the country.

Mapping how your intelligent transportation system will integrate with emerging connected vehicles is essential to retain an upper hand in the market.

4. Design with security in mind

Adopting intelligent transport systems means opening your ecosystem to third-party service providers and connected infrastructure devices.

Increased data connectivity, however, opens your systems up to new vectors of cyberattacks:

Source: U.S. Department of Energy Office of Scientific and Technical Information — Cybersecurity challenges in vehicular communications

According to the, Upstream Security Global Automotive Cybersecurity Report 2019, the main attack vectors for connected vehicles in 2019 were server attacks (21%), keyless entry attacks (19%), and exploit attempts via the OBD port (10%).

At present, it’s not yet clear what types of cyber attacks can be performed via V2I and V2V communication. But the feasibility of such attacks has already been proven.

Recently, a security expert managed to hack NYC’s wireless vehicle detection system with a cheap wireless device. In this system, vulnerabilities allowed anyone to take control of such a device and send fake data to traffic control systems. Despite the expert’s inability to control a traffic signal, fake vehicle data emissions could cause severe traffic congestion and increase accident risks.

It follows that cybersecurity in ITS has to be implemented by design. The U.S. Department of Transportation has partnered with the National Institute of Standards and Technology (NIST) to adapt the NIST cybersecurity framework to connected cars.

Additionally, U.S. DOT is sponsoring several cybersecurity programs and urging private companies to implement the following security controls:

• Apply penetration testing to all ITS components
• Use secure credential management systems for V2V and V2I communications
• Introduce anomaly-based intrusion detection systems
• Implement security controls for firmware updates
• Train operators in necessary cybersecurity topics

UK authorities have also developed a set of cybersecurity principles for connected and autonomous vehicles for both OEMs and companies involved in the development and deployment of connected car infrastructure:

• ITS and connected car systems are developed by implementing secure design principles, with all aspects of security (physical, personnel, and cyber) integrated into the development process.
• Security risk assessment and risk management practices and tools have to be in place in every organization and extend to all supply chain participants, subcontractors, and service providers.
• Every company needs to have a cybersecurity program for identifying critical vulnerabilities and rapidly mitigating risks.

How can you implement the above requirements in practice? Here are our suggestions:

Must-follow cybersecurity best practices for intelligent transportation systems

• Create and implement end-to-end ITS penetration testing plans
  • Physical penetration tests of connected infrastructure
  • Embedded hardware and firmware penetration tests
  • Wireless communication penetration tests
  • Network penetration tests
  • Application and management software penetration tests
• Implement next-generation firewalls (NGFW) or unified threat management (UTM) gateways to exercise better control over incoming and outgoing traffic.
  • Consider virtual firewalls and firewall-as-as-service solutions.
  • Use UTM gateways to consolidate multiple systems and services as a single engine or appliance to streamline monitoring.
• Apply data encryption to ensure the utmost data privacy, integrity, and protection. Follow standards
  • Wireless Access for Vehicular Environments (WAVE)
  • European Telecommunications Standards Institute (ETSI ITS) standards
• Implement standard cybersecurity systems:
  • Anti-malware/anti-phishing systems
  • Breach detection systems
  • Vulnerability scanning
  • Intrusion detection and/or intrusion prevention systems
  • Security patch management

To conclude

Transportation networks are complex multifaceted structures. Their level of complexity increases in proportion to the number of people and goods traveling through them. The goal of implementing an intelligent transportation system is to provide better controls for orchestrating the flows of those goods and people.

Simple data processing, integration, and analytics tools no longer meet the needs of complex ITS data processing and distribution tasks. But emerging technologies such as big data analytics, IoT, computer vision, and machine learning have already proven to drive strong gains for municipalities around the globe. Now is the optimal time to give a green light to new innovative initiatives!

Contact Intellias for a preliminary consultation on intelligent transportation system development and implementation.