Enhancing Active Transportation and Demand Management (ATDM) with Advanced and Emerging Technologies and Data Sources

Chapter 1. Introduction

Per the Federal Highway Administration (FHWA) Office of Operations, active transportation and demand management (ATDM) is defined as:

"…the dynamic management, control, and influence of travel demand, traffic demand, and traffic flow on transportation facilities. Through the use of available tools and assets, traffic flow is managed, and traveler behavior is influenced in real time to achieve operational objectives, such as preventing or delaying breakdown conditions, improving safety, reducing emissions, or maximizing system efficiency." ⁽⁵⁾

ATDM solutions aim to leverage data sources and technologies to manage capacity and demand on facilities to reduce congestion and delay; respond to incidents and provide traveler information based on real-time data; and balance resources across active traffic management (ATM), active demand management (ADM), and active parking management (APM) for optimal solutions.

ATDM concepts and the vision of Transportation Systems Management and Operations (TSMO) have been around since the beginning of intelligent transportation system (ITS) deployments. Figure 1 is a picture of the Lodge Freeway from the early 1960s. It has similar elements/strategies as a modern-day ATM system (e.g., variable speed limits (VSLs), dynamic lane use control, and ramp metering), but newer technologies and data sources were used to deploy these same types of solutions over time and they will continue into the future. These technological changes make the vision possible in ways we could only dream of in the past. It is important to be aware of technologies and data sources available today, be cognizant of what is coming next, and start planning for it now. This document is about how new technologies and data sources can improve the way we implement ATDM concepts and solutions that we will be using for the foreseeable future.

Figure 2 represents another example of an ATM implementation with the implementation of VSLs, dynamic lane management, and dynamic shoulder use. This system uses a more modern technology to help implement dynamic shoulder use. Video analytics cameras are used to monitor the shoulder and determine if there are any stopped vehicles in the shoulder before the ATM solution is put into effect. In older dynamic shoulder use implementations, manual methods (i.e., service patrol vehicles manually drive the shoulder length to verify it as clear) were used before activating the ‘should use' signs. Now using more modern technologies, along with this manual, an expensive and time-consuming method can be eliminated.

1.1 Document Purpose

This document informs agencies of the technology and data sources available to modify and enhance their ATDM solutions from static/responsive management to truly proactive management. Viable emerging technologies and data sources will be described, and information will be provided on how advanced and emerging technologies and data sources can enhance specific ATDM approaches and solutions under ATM, ADM, and APM. It should be noted that technologies change quickly, and the information contained in this Reference represents a snapshot in time. Much of the information in this document will be relevant to agencies applying new technology in the future but there may be additional technologies and data sources to be investigated as well.

This document will discuss the steps of the active management cycle (i.e., monitor the system, assess system performance, evaluate and recommend dynamic actions, and implement dynamic actions) and how these steps can be enhanced with new technology and data sources. Also, information is provided as it relates to design considerations, operations and maintenance (O&M) considerations, as well as challenges and pitfalls.

1.2 Objectives

The objectives of this document are as follows:

• Educate current and future implementers of ATDM concepts and solutions about new technologies and data sources that are available to help enhance their deployments.
• Increase awareness about the linkages and synergies between ATDM and advanced and emerging technologies and data sources.
• Investigate the potential impacts, opportunities, efficiencies, and challenges of leveraging advanced and emerging technologies and data sources to enhance ATDM deployments.
• Investigate how agencies can prepare for deploying and operating ATDM in a fast-changing world of technology.
• Advance improvements to existing ATDM operations and deployments and to see deployments of new ATDM solutions that use the latest technologies and data sources.

1.3 Target Audience

The target audience for this ATDM Reference include:

• Agencies and companies that currently deploy ATDM solutions and wish to understand how they can be enhanced.
• Engineering consultants, technology companies, systems integrators, ATDM software solution providers, and ITS equipment providers who can shape products, projects, and systems to ATDM.
• Legislative, executive, and policy staff who need to understand ATDM.
• City, County, and State transportation planners, system managers, and project development professionals who seek to identify and evaluate potential ATDM approaches in planning and development.
• City, County, and State project engineers, ATDM infrastructure designers, finance specialists, agency procurement departments, and legal professionals who need to plan, implement, and operate within the ATDM paradigm.

1.4 Document Organization

The document organization follows this structure:

• Chapter 1 – Introduction.
• Chapter 2 – Emerging Technologies and Data Sources.
• Chapter 3 – ATDM Applications.
• Chapter 4 – Planning and Organizational Considerations.
• Chapter 5 – Design and Deployment Elements and Methods.
• Chapter 6 – O&M Considerations.
• Chapter 7 – Case Studies.
• Appendix A – References.

1.5 Active Transportation and Demand Management Overview

ATDM is not simply a system deployment of hardware but rather an operational philosophy or concept. At ATDM's core is active management of the system and of demand. The culture of an actively managed operations includes:

• Focus on now.
• Recognition that conditions vary.
• Orientation towards customers and their service needs.
• Focus on performance.
• Emphasis on management of system rather than development of system.
• Operation runs 24/7, not just 9 to 5.
• Scaled to trip – not just a jurisdiction.

The ultimate vision of ATDM is to dynamically manage all components and aspects across the trip chain, as is illustrated in figure 3, by providing travelers with choices (e.g., destination choice, time of day choice, mode choice, route choice and lane/facility choice).

• Destination Choice – Decision on whether to make the trip and where to go. Traditionally, this is a long-term choice, but day-to-day or even hour-to-hour impacts are possible.
• Time of Day Choice – Decision on when a trip is to be made. Real-time traveler information, for example, can affect this choice on a direct hour-to-hour basis.
• Mode Choice – Decision on how trip is to be made, including decision to drive alone, carpool, use a form of public transport, or some other form of rideshare (e.g., slug lines). Dynamic information such as comparative travel times, real-time arrivals/schedule disruption/event/incident information, etc., play a role in choice scenarios.
• Route Choice – Decision on what road or transit route is to be taken, based on the most direct, fastest, or most cost-effective option.
• Lane/Facility Use Choice – This decision is influenced by current operational conditions on the travel route and may involve options related to higher cost/better level of service in comparison with normal costs and normal/substandard level of service, including toll lanes/high occupancy toll (HOT) lanes.

ATDM is divided into three approaches used to improve trip reliability, safety, and throughput of the surface transportation system: ^{(18, 19, 20, 21, and 50.)}

ATM:

• A suite of solutions that actively manage traffic on a facility.
• Dynamically manages recurrent and non-recurrent congestion based on prevailing and predicted traffic conditions.
• Current examples of ATM include dynamic lane use, dynamic speed limits, queue warning, dynamic shoulder use, adaptive ramp metering, and others.

ADM:

• A suite of solutions intended to reduce or redistribute travel demand to alternate modes or routes that incentivizes drivers by providing rewards for traveling during off-peak hours with less traffic congestion.
• Dynamically manages demand, which could include redistributing travel to less congested times or routes or by influencing mode choice.
• Current examples of ADM include dynamic ridesharing, on-demand transit, dynamic pricing, and predictive traveler information.

APM:

• A suite of solutions designed to effect the demand on parking capacity.
• Dynamically manages parking facilities in the region to optimize utilization while influencing travel behavior.
• Current examples of APM include dynamically priced parking, dynamic parking reservation, dynamic wayfinding, and dynamic parking capacity.

Active Management Cycle

Using the active management cycle, the transportation system is continuously monitored, with actions being performed in real-time to maximize system efficiency. A diagram of the active management cycle is shown in figure 4.

Monitor System – Through interfaces with sensors, data feeds, and other technologies, the system is continually monitored and, in most cases, these data are stored for future analysis and processes.

Assess System Performance –; Using data related to prevailing and predictive traffic conditions (i.e., the "monitoring" data), the system is continuously assessed for current and expected system performance.

Evaluate and Recommend Dynamic Actions – Using assessed system performance data and considering all potential ATDM approaches, the system will evaluate potential dynamic actions to take (e.g., control a traffic signal or dynamic message sign [DMS]) and recommend which actions are most suitable to implement.

Implement Dynamic Actions – The recommended system actions are then "activated" putting them into live operation.

Active Traffic Management

How Active Traffic Management manages recurrent and non-recurrent congestion

ATM manages recurrent and non-recurrent congestion using prevailing and predicted traffic conditions to manage lane/facility operations with direct interaction with the driver encouraging them to make tactical decisions.⁽⁶⁾

Description of Active Traffic Management approach

ATM is the ability to dynamically manage recurrent and non-recurrent congestion based on prevailing and predicted traffic conditions. Focusing on trip reliability, it maximizes the effectiveness and efficiency of the facility. It increases throughput and safety through the use of integrated systems with new technology, including the automation of dynamic deployment to optimize performance quickly and without delay that occurs when operators must deploy operational strategies manually. ATM approaches focus on influencing travel behavior with respect to lane/facility choices and operations. ATM solutions can be deployed singularly to address a specific need (i.e., utilizing adaptive ramp metering to control traffic flow) or can be combined to meet system-wide needs of congestion management, traveler information, and safety, resulting in synergistic performance gains.

ATM dynamically manages recurrent and non-recurrent congestion based on prevailing and predicted traffic conditions. Recurrent congestion occurs when demand increases beyond the available capacity. Non-recurrent congestion results from a decrease in capacity, while the demand remains the same. This kind of congestion usually results when one or more lanes are temporarily blocked from events such as crashes, disabled vehicles, work zones, adverse weather events, and planned special events. ATM expects changing conditions by evaluating current or prevailing traffic conditions based on real-time sensor data, as well as predicted traffic conditions based on archived data fused with demand modeling.

The primary classes of actions taken by ATM solutions are active management of capacity and the direct interaction with the driver to encourage them to make tactical decisions in vehicle or driver performance.

Strategies

An agency can deploy a single ATM approach to capitalize on a specific benefit or can deploy multiple active strategies to gain other benefits across the entire transportation system. Some example approaches are included in table 1.

Table 1. Active traffic management solutions.

Strategy	Description
Adaptive Ramp Metering	Use of traffic signals on ramps to control the rate a vehicle enters a freeway facility, thus allowing efficient use of freeway capacity.
Adaptive Traffic Signal Control	Continuously monitor arterial traffic conditions and queuing and optimize one or more operational objectives.
Dynamic Junction Control	Dynamically allocating lane access on mainline and ramp lanes in interchange areas.
Dynamic Lane Reversal or Contraflow Lane Reversal	Reversal of lanes to dynamically allocate the capacity of congested roads based on prevailing or predictive conditions.
Dynamic Lane Use Control	Dynamically open/close traffic lanes as needed and provide travelers advance warning.
Dynamic Merge Control	Dynamically managing entry of vehicles into merge areas with messages approaching merge point, preparing motorists for an upcoming merge and encouraging or directing a merging behavior.
Dynamic Shoulder Lanes or Part-Time Shoulder Use	Enables use of shoulder as a travel lane(s) based on congestion levels.
Dynamic Speed Limits	Adjust speed limits based on real-time traffic, roadway, and/or weather conditions.
Queue Warning	Provide real-time warning messages to alert travelers that slowdowns are ahead.
Traffic Signal Priority	Manage traffic signals by using sensors or probe vehicle technology to detect when a bus nears a signal-controlled intersection.

Active Demand Management

How Active Demand Management 'redistributes' travel

ADM redistributes travel by focusing on influencing travel behavior of the traveling public with incentives and disincentives by presenting choices in mode, time, route, or location of travel.⁽⁷⁾

Description of Active Demand Management approach

ADM uses information and technology to dynamically manage traffic demand. One key tenet of ATDM is the ability to influence travel behavior in real-time. This is consistent with the desire to maximize available choices of mode, time, route, or location of travel. Traditional demand management focuses on mode choice, but ADM goes a step further to use information and technology that could redistribute travel to less congested times of day or routes.

Incentives or disincentives, sometimes called financial levers, are important components of ADM. The specific list of financial levers varies by target, but could take the forms of:

• Travel time discounts or assessments.
• Direct financial incentives for avoiding peak-hour travel.
• Gift certificates through points accumulated by offering rides with dynamic ridesharing vendors.
• Shopping information or discounts to encourage changes in departure times during peak periods.

With advances in connectivity, ADM can match in-route travelers with others needing a ride or provide comparative travel times for traffic and transit to induce an in-route mode or route shift dynamically even after a trip has begun.

ADM uses information and technology to dynamically manage demand, which could include redistributing travel to less congested times of day or routes or reducing overall vehicle trips by influencing a mode choice.

ADM seeks to influence more fluid, daily travel choices to support more traditional, regular mode choice changes. ADM is very supportive of other active measures by redistributing or reducing overall traffic levels during congested conditions, thus becoming an integral part of an overall management philosophy to actively manage a facility or system.

Strategies

An agency can deploy a single ATDM approach to capitalize on a specific benefit or can deploy multiple active strategies to gain other benefits across the entire transportation system. Some example approaches are included in table 2.

Table 2. Active demand management solutions.

Strategy	Description
Dynamic Fare Reduction	Reducing transit system fares in a particular corridor.
Dynamic High-Occupancy Vehicle (HOV) / Managed Lanes	Changing of qualifications for driving in HOV lanes.
Dynamic Pricing	Dynamically changing toll rates based on changing congestion levels.
Dynamic Ridesharing	Through advanced technologies, such as smartphones and social networks, travelers are able to arrange short-notice, one-time shared rides.
Dynamic Routing	Uses variable destination messaging to disseminate information to make better use of roadway capacity.
Dynamic Transit Capacity Assignment	Reorganizing schedules and adjusting assignments of assets (e.g., buses) based on real-time demand.
On-Demand Transit	Travelers make real-time trip requests for services with flexible routes and schedules.
Predictive Traveler Information	Uses real-time and historical data to predict travel conditions and inform travelers before their departure.
Transfer Connection Protection	Improving reliability of transfers from a high-frequency transit service (e.g., a train) to low-frequency transit services (e.g., a bus).

Active Parking Management

How Active Parking Management optimizes utilization of parking facilities

APM provides travelers with real-time parking information. This information helps to maximize utilization of parking resources, and helps travelers make informed choices (e.g., timing, mode, and facility).⁽⁸⁾

Description of Active Parking Management approach

APM is the dynamic management of parking facilities in a region to optimize performance and utilization of those facilities while influencing travel behavior at various stages along the trip-making process: i.e., from origin to destination. Dynamically managing parking can affect travel demand by influencing trip timing choices, mode choice, as well as parking facility choice at the end of the trip. This ATDM approach can also have a positive impact on localized traffic flow by providing real-time parking information to users and ensuring the availability of spaces to reduce circling around parking facilities. The overall goal is to help maximize the nation's transportation infrastructure investments, reduce congestion, and improve safety.

A fundamental component of APM is information. With clear, detailed, relevant, and real-time parking information, travelers can make informed decisions regarding their trip. The information a user needs to make parking-related decisions can be conveyed in numerous ways and in various formats. These include, but are not limited to, traditional static road signs, DMSs, the internet, cell phones, smartphones and similar mobile devices, and navigation systems. Agencies can harness the power of an enhanced technology infrastructure (wireless and wired communications, embedded sensors, etc.) and combine it with the breadth of currently available technologies to convey information as well as to accept reservations and parking payments, monitor use, and conduct enforcement. These technologies can be applied to both on-street and off-street parking spaces to optimize use of all facilities in a region. Parking system operators also realize numerous benefits with APM. Agencies can reduce costs, improve efficiency, and increase parking utilization rates. By increasing the availability of limited parking spaces and optimizing the use of facilities at all times of the day, agencies can help reduce congestion in and around parking facilities, improve enforcement efficiency, foster public trust, and reduce the receipt of parking tickets by accommodating alternative payment methods. APM also helps a region as a whole by reducing pollution, encouraging the use of alternative modes, relieving congestion around commercial businesses, and helping improve access by emergency responders. In some cases, agencies can actually increase parking capacity in a limited footprint with innovative parking facility designs that stack vehicles and/or automate parking.

APM dynamically manages parking facilities in a region for optimum use.

Strategies

An agency can deploy a single ATDM approach to capitalize on a specific benefit or can deploy multiple active strategies to gain other benefits across the entire transportation system. Some example approaches are included in table 3.

Table 3. Active parking management solutions.

Strategy	Description
Dynamically Priced Parking	Use of dynamically generated parking fees based on demand and availability.
Dynamic Parking Reservation	Utilizes technology to reserve a parking space on demand to ensure availability.
Dynamic Wayfinding	Provide real-time parking location and availability to reduce time spent searching for parking.
Dynamic Overflow Transit Parking or Dynamic Capacity	Dynamically uses overflow parking near transit stations or park-and-ride facilities when existing parking is at or near capacity.

Active Transportation Demand Management Benefits

Benefits of Today's Active Transportation and Demand Management

Using today's data sources and technologies, the ATDM benefits include:

• A decrease in primary incidents by alerting drivers to congested conditions and promoting more uniform speeds.
• A decrease in secondary incidents by alerting drivers to the presence of queues or incidents and proactively managing traffic in and around incidents.
• Increased throughput by reducing the delay associated with the number of primary and secondary incident, thus reducing speed differential in traffic flow and reducing the shockwave effects of excessive breaking.
• Increased overall capacity by adding shoulder use during congested periods when it is needed most.
• Overall improvement in speed uniformity during congested periods.
• Increased trip reliability by increasing capacity and throughput and reducing incident delay and improving vehicle throughput.

Benefits of Tomorrow's Active Transportation and Demand Management

By adding the previously discussed emerging data sources and technologies to both existing and future ATDM solutions, the expected benefits of tomorrow's ATDM might include:

• Improvement of situational awareness for incident and event management through video analytics and high-resolution vehicle trajectories. Improved incident response, onsite monitoring, and management.
• Provision for new services for road hazard warnings—higher fidelity location information, more accurate confirmation of hazard types, and more timely warnings.
• New sources for speed warnings, intersection collision avoidance—specific recommendations to different vehicle types based on roadway conditions, and more timely warnings.
• Improved traffic signal timing—better operation in oversaturated conditions, more timely updates to fixed timings, broad-based adaptive controls, reduced reliance on physical sensor devices and maintenance, shift towards in-vehicle data delivery, and performance monitoring of signals with no physical links to Department of Transportation (DOT) communications infrastructure.
• Freeway ramp metering—more accurate and coordinated corridor metering algorithms.
• VSL recommendations and lane use control strategies—more accurate and coordinated responses, shift towards in-vehicle signage reducing needs for infrastructure investments.
• DMS displays—more accurate messaging, shift towards in-vehicle signage for more personalized recommendations, and reduced need for infrastructure investments.
• Work zone implementation—higher safety for workers and drivers, higher resolution maps of work zone geometries, real-time information on new zone locations, and less need to manually update locations.⁽¹²⁾
• Broadcasted and personalized traveler information—higher fidelity information, more accurate and timely information, and personalized recommendations.
• Congestion pricing, road user fees, and tolls—more granular toll rates, more accurate congestion prices, personalized tolls, and road user fees.
• Performance measurement, including weather and emissions monitoring—higher fidelity analysis, more comprehensive coverage of geography, and reduced need for infrastructure investments.
• Asset management and maintenance—reduced need for infrastructure investments and faster detection and response to equipment failures.

Related Efforts

In addition to the research referenced in appendix A, there is some very specific research directly associated with this effort that is worth noting:

• There were three pieces of related research that are connected to this effort.^{(24, 25, and 26)} First, FHWA's "Integrating Emerging Data Sources into Operational Practice" research was the follow-on to two projects that developed information resources on the impacts of connected and autonomous vehicles (CAVs) and technologies. After the "Integrating Emerging Data Sources into Operational Practice" project was completed, FHWA initiated the "Decision Support Systems for the Next Generation of Traffic Management Systems" project, followed by "Framing the Next Generation of Traffic Management Systems." These projects frame many of the emerging data and technology issues at an overview or conceptual level, and even begin to look at the cost and computing needs required to support.
• Another directly related ongoing effort is the Transportation Management Center (TMC) Pooled Fund Study called "Considerations of Current and Emerging Transportation Management Center Data." The goal of this study was to better understand current and emerging data types that can be used to improve TMC operations as well as other operational functions. It was also to learn about business models used for selling third-party data and possible ways for identifying the value of agencies' existing data.

This Reference explores more information related to the use of emerging data for ATDM. The same holds true for the possible consideration and use of technologies—what technologies, why, and to do what—along with how this compares to what people are using now, as well as how someone should compare and assess implications of using different technologies.