Enhancing Advanced Traffic Management Systems Using Connected Car Data

Effective Traffic Management Is a Cornerstone of the Smart City

Traffic from automobiles and commercial vehicles is one of the most pressing problems on roads and highways across the globe. It’s the source of pollution, frustration, and a significant number of accidents. According to Global Market Insights, traffic management systems represented a $20 billion market in 2019, with an expected compound annual growth rate of 5% through 2026.

It’s no surprise that municipalities across the globe are looking to deploy advanced traffic management systems or active traffic management systems, the latest evolution of intelligent transportation systems (ITS).  While some transportation professionals use these two terms interchangeably, we’ll use this blog post to distinguish between the two strategies and describe how to enhance their key capabilities with data from the growing population of connected cars now on the road. 

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Advanced Traffic Management Systems Improve upon Road and Traffic Monitoring

Advanced traffic management systems focus on reducing congestion on highways and surface streets by bringing together traffic flow sensors, data analysis, and communications technologies.

 Capabilities include: 

  • Centralized traffic monitoring, with information funneled to a Transportation Management Center (TMC)
  • Manual or automated updates to variable message signs (also known as dynamic message signs or matrix signs)
  • Public transportation updates, including expected wait times for trains and buses
  • Manual or automated updates to traffic signals
  • Manual or automated updates to ramp metering systems
  • Incident monitoring and emergency response
  • Road Weather Information System (RWIS) monitoring
  • Highway advisory radio
  • Chain controls in snowy weather
  • Predictive traffic modeling, through which traffic engineers analyze the data collected by advanced traffic management systems to design improvements to road infrastructure

Georgia NaviGAtor set an early standard for advanced traffic management systems in the United States. Originally launched in preparation for the 1996 Summer Olympic Games, this system provides trip times, incident reporting, alerts, and more through a website and mobile app. Georgia NaviGAtor primarily uses video analytics from a network of approximately 1,645 video detection system (VDS) stations installed every 1/3 mile along most major interstates around Atlanta. Coverage outside Atlanta is more limited.

Active Traffic Management Systems Directly Manage Traffic Flows

According to the U.S. Federal Highway Administration, “Active traffic management (ATM) is the ability to dynamically manage recurrent and non-recurrent congestion based on prevailing and predicted traffic conditions. ATM approaches focus on influencing travel behavior with respect to lane/facility choices and operations.” In other words, active traffic management focuses on increasing peak capacity and smoothing traffic flows on busy highways by changing driver behavior

Active traffic management system capabilities include incident monitoring, traffic signal timing, automated ramp metering systems, variable message signs, and other capabilities associated with advanced traffic management systems. 

Additional techniques include:

  • Automated incident detection, including the ability to detect accidents, speeding, and wrong-way drivers
  • Dynamic junction control or dynamic lane access, through which lane access may be changed depending on traffic conditions
  • Dynamic merge control, to give drivers information about merges and smooth out the the process
  • Dynamic shoulder lanes, through which all vehicles or certain vehicles (such as buses and taxis) can use shoulders for travel during high-congestion periods
  • Dynamic speed limits, which can change based on traffic or weather conditions
  • Transit signal priority, through which traffic signals can detect buses and give them a green light faster than single-occupancy cars
  • Rerouting capabilities, which constantly recalculate routes based on current conditions

Germany, the Netherlands, and the United Kingdom are among the countries that have proven the success of active traffic management systems. These systems reduce travel times as well as road accidents. 

What Data Sources Power Advanced and Active Traffic Management Systems?

Of course, all of the techniques employed for advanced and active traffic management systems require reliable, near real-time data on road and traffic conditions. Today, the vast majority of transportation agencies collect this data from video analytics and/ or road sensors, which can be mounted at the edge of the road or embedded in pavement. RFID sensors such as toll tags can also be used. Video detection systems and road sensors require significant capital investments, and they must be periodically monitored, maintained, and upgraded. (You can get more details on the pros and cons of each source in a recent blog post by Matan Tessler.)

Connected Car Data Offers a Strong Value Proposition for Traffic Management

Today, there’s a new data source available to intelligent transportation systems: connected car data. By 2023, IDC predicts that 90% of new vehicles in the United States will be shipped with embedded connectivity and that worldwide shipments will reach 76.3 million units. 

Connected cars are constantly emitting a critical mass of data about what’s happening on roads and highways, and platforms like the Otonomo Platform make it simple and practical for transportation agencies to ingest this data into their traffic management systems. 

Connected car data offers a number of important advantages for traffic management systems:

  • Lower capital expenditures and operating costs: There are no installation or maintenance costs for connected vehicles. Essentially, each vehicle operates as a low-cost sensor.
  • Broader scale: Since there’s no new capital equipment to install, agencies can extend traffic management systems outside of the densest metropolitan areas
  • New and richer datasets: Connected vehicles collect datasets that extend far beyond speed and location. With information like braking, door status, hazard signals, air bag deployment, ambient temperature, windshield wiper operation, road signs, and headlight operation, agencies can hone in on incidents more quickly and make better predictions about the future. 
  • Data de-identification: Data passing through an OEM’s data centers can be stripped of identifiable information, such as the VIN, to protect driver privacy. This can be difficult to do for video detection systems. 
  • Consumer consent: Unlike video monitoring, consumers can be educated about connected car data usage by their OEMs during the vehicle purchase process. 

The Future of Traffic Management: Infrastructure-to-Vehicle (I2V), Vehicle-to-Vehicle (V2V) Communication and more

Enhancing today’s intelligent transportation systems with connected car data also positions transportation agencies for their future. The next wave of traffic management system innovation will make travel management more autonomous: through infrastructure-to-vehicle (I2V), vehicle-to-infrastructure (V2I), and vehicle-to-vehicle (V2V) communication. All of these new traffic management models depend on connected car data. 

In the United States, several state departments of transportation are the early stages of developing applications or tools that leverage I2V or V2I connectivity. According to a 2017 survey conducted by the Federal Highway Administration, 17% of agencies report that they are developing these types of applications, while 42% are considering doing so. The State of Wyoming is the farthest along; its Connected Vehicle Pilot is using advanced dedicated short-range communication (DSRC) technology to improve safety and mobility, specifically focusing on weather information.  

Perhaps the most ambitious goals come from the United Arab Emirates. Sheikh Hamdan bin Mohammed bin Rashid Al Maktoum, Vice President and Ruler of Dubai, wants driverless transport to account for 25 percent of journeys in the emirate by 2030. The expected impact of driverless transport:

  • A 44% reduction in overall transportation costs, or savings up to 900 million United Arab Emirates dirhams (AED) per year
  • A 12% reduction in environmental pollution, equating to AED 1.5 billion a year
  • AED 18 billion in annual economic returns by increasing the efficiency of the transportation sector in Dubai

Is It Time to Get Started?

Fully connected traffic management systems may be years off, but the barriers to getting started with connected car data are incredibly low. If you work for a transportation agency, we’d love to show you how easy it is to integrate with our traffic data API. 

Reach out to us, or sign up for a 30-day free trial and take a look for yourself!

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