Office of Operations Active Transportation and Demand Management

Guide for Highway Capacity and Operations Analysis of Active Transportation and Demand Management Strategies

2 The ATDM Strategy Tool Box

Active management of transportation and demand can include multiple approaches spanning demand management, traffic management, parking management, and efficient utilization of other transportation modes and assets. Some example approaches are included in Table 1. It should be noted that the strategies covered by this Guide deal primarily with Active Traffic Management strategies. Active Parking Management strategies are not covered at all, and only static demand management strategies are covered.

Table 1: Example ATDM Approaches Strategies
Active Demand Management Active Traffic Management Active Parking Management
Dynamic Ridesharing Dynamic Lane Use/Shoulder Control Dynamically Priced Parking
On-Demand Transit Dynamic Speed Limits Dynamic Parking Reservation
Dynamic Pricing Queue Warning Dynamic Way-Finding
Predictive Traveler Information Adaptive Ramp Metering Dynamic Parking Capacity

2.1 Active Traffic Management

Active traffic management (ATM) is the ability to dynamically manage recurring and nonrecurring congestion based on prevailing and predicted traffic conditions. Focusing on trip reliability, it maximizes the effectiveness and efficiency of the facility. ATM approaches seek to increase throughput and safety through the use of integrated systems with advanced technology, including the automation of dynamic deployment to optimize performance. In addition to the approaches listed in the table above, other ATM strategies and their descriptions are:

  • Adaptive Ramp Metering: This strategy consists of deploying traffic signal(s) on ramps to dynamically control the rate vehicles enter a freeway facility. This has the effect of smoothing the flow of traffic onto the mainline, allowing efficient use of existing freeway capacity. Adaptive ramp metering utilizes traffic responsive or adaptive algorithms (as opposed to pre-timed or fixed time rates) that can optimize either local or systemwide conditions. Adaptive ramp metering can also utilize advanced metering technologies such as dynamic bottleneck identification, automated incident detection, and integration with adjacent arterial traffic signal operations. In an ATDM approach, real-time and anticipated traffic volumes on the freeway facility are used to control the rate of vehicles entering the freeway facility. Based on the conditions, the ramp meter rates are adjusted dynamically.

Figure 2: Freeway Ramp Metering, SR 94, Lemon Grove, California

Figure 2 is a picture of cars at a ramp metering system. The signal at the end of the ramp indicates stop.

Source: FHWA, Ramp Management and Control, A Primer (1).

  • Adaptive Traffic Signal Control: This strategy continuously monitors arterial traffic conditions and the queuing at intersections and dynamically adjusts the signal timing to optimize one or more operational objectives (such as to minimize overall delays). Adaptive Traffic Signal Control approaches typically monitor traffic flows upstream of signalized locations or segments with traffic signals, anticipating volumes and flow rates in advance of reaching the first signal, then continuously adjusting timing parameters (e.g., phase length, offset, cycle length) during each cycle to optimize operational objectives.
  • Dynamic Junction Control: This strategy consists of dynamically allocating lane access on mainline and ramp lanes in interchange areas where high traffic volumes are present and the relative demand on the mainline and ramps change throughout the day. For off-ramp locations, this may consist of assigning lanes dynamically either for through movements, shared through-exit movements, or exit-only. For on-ramp locations, this may involve a dynamic lane reduction on the mainline upstream of a high-volume entrance ramp, or might involve extended use of a shoulder lane as an acceleration lane for a two-lane entrance ramp which culminates in a lane drop. In an ATDM approach, the volumes on the mainline lanes and ramps are continuously monitored and lane access will be dynamically changed based on the real-time and anticipated conditions.
  • Dynamic Lane Reversal or Contraflow Lane Reversal: This strategy consists of the reversal of lanes in order to dynamically increase the capacity of congested roads, thereby allowing capacity to better match traffic demand throughout the day. In an ATDM approach, based on the real-time traffic conditions, the lane directionality is updated quickly and automatically in response to or in advance of anticipated traffic conditions.
  • Dynamic Lane Use Control: This strategy involves dynamically closing or opening of individual traffic lanes as warranted and providing advance warning of the closure(s) (typically through dynamic lane control signs), in order to safely merge traffic into adjoining lanes. In an ATDM approach, as the network is continuously monitored, real-time incident and congestion data is used to control the lane use ahead of the lane closure(s) and dynamically manage the location to reduce rear-end and other secondary crashes.
  • Dynamic Merge Control: This strategy (also known as dynamic late merge or dynamic early merge) consists of dynamically managing the entry of vehicles into merge areas with a series of advisory messages (e.g., displayed on a dynamic message sign (DMS) or lane control sign). As motorists approach the merge point, they are prepared for an upcoming merge and are directed to use a consistent merging behavior. Applied conditionally during congested (or near congested) conditions, dynamic merge control can help create or maintain safe merging gaps and reduce shockwaves upstream of merge points. In an ATDM approach, conditions on the mainline lanes and ramps approaching merge areas are continuously monitored and the dynamic merge system will be activated dynamically based on real-time and anticipated congestion conditions.
  • Dynamic Shoulder Lanes: This strategy enables the use of the shoulder as a travel lane(s), known as Hard Shoulder Running (HSR) or temporary shoulder use, based on congestion levels during peak periods and in response to incidents or other conditions during nonpeak periods. In contrast to a static time-of-day schedule for using a shoulder lane, an ATDM approach continuously monitors conditions and uses real-time and anticipated congestion levels to determine the need for using a shoulder lane as a regular or special purpose travel lane (e.g., transit only).
  • Dynamic Speed Limits: This strategy adjusts speed limits based on real-time traffic, roadway, and/or weather conditions. Dynamic speed limits can either be enforceable (regulatory) speed limits or recommended speed advisories, and they can be applied to an entire roadway segment or individual lanes. In an ATDM approach, real-time and anticipated traffic conditions are used to adjust the speed limits dynamically to meet an agency’s goals/objectives for safety, mobility, or environmental impacts.
  • Queue Warning: This strategy involves real-time displays of warning messages (typically on dynamic message signs and possibly coupled with flashing lights) along a roadway to alert motorists that queues or significant slowdowns are ahead, thus reducing rear-end crashes and improving safety. In an ATDM approach, as the traffic conditions are monitored continuously, the warning messages are dynamic based on the location and severity of the queues and slowdowns.
  • Transit Signal Priority: This strategy manages traffic signals by using sensors or probe vehicle technology to detect when a bus nears a signal controlled intersection, turning the traffic signals to green sooner or extending the green phase, thereby allowing the bus to pass through more quickly. In an ATDM approach, current and predicted traffic congestion, multi-agency bus schedule adherence information, and number of passengers affected, may all be considered to determine where and when transit signal priority may be applied.

2.2 Active Demand Management

Active Demand Management (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 because it redistributes or reduces overall traffic levels during congested conditions, thus becoming an integral part of an overall management philosophy to actively manage a facility or system. Example of ADM strategies include:

  • Dynamic Fare Reduction: This strategy involves reducing the fare for use of the transit system in a particular corridor as congestion or delay on that corridor increases. This encourages selection of the transit mode to reduce traffic volumes entering the corridor. Fare changes are communicated in real-time to the traveling public, through general dissemination channels such as a transit web site, as well as personalized messages to subscribers. In an ATDM approach, real-time and predicted highway congestion levels and/or the utilization levels of the transit system can be used to adjust transit fare in real-time to encourage mode shift necessary to meet agencies goals and objectives.
  • Dynamic High-Occupancy Vehicle (HOV)/Managed Lanes: This strategy involves dynamically changing the qualifications for driving in a high-occupancy vehicle (HOV) lane(s). HOV lanes (also known as carpool lanes or diamond lanes) are restricted traffic lanes reserved at peak travel times or longer for exclusive use of vehicles with a driver and one or more passengers, including carpools, vanpools and transit buses. The normal minimum occupancy level is 2 or 3 occupants. Many agencies exempt other vehicles, including motorcycles, charter buses, emergency and law enforcement vehicles, low-emission vehicles, and/or single-occupancy vehicles paying a toll. In an ATDM approach, the HOV lane qualifications are dynamically changed based on real-time or anticipated conditions on both the HOV and general purpose lanes. Factors that can potentially be dynamically adjusted include the number of occupants (e.g., from 2 to 3 occupants), the hours of operation, and the exemptions (e.g., change from typical HOV operation to buses only). Alternatively, the HOV restrictions could be dynamically removed allowing general use of the previously managed lane.
  • Dynamic Pricing: This strategy utilizes tolls that dynamically change in response to changing congestion levels, as opposed to variable pricing that follows a fixed schedule. In an ATDM approach, real-time and anticipated traffic conditions can be used to adjust the toll rates to achieve agency goals and objectives.

Figure 3: Minnesota Dynamic Pricing for HOT Lanes

Figure 3 is a picture of cars on the highway, with an high-occupancy tolls lane on the far left, and two normal lanes on the right.

Source: FHWA: Technologies That Complement Congestion Pricing (X2X) (Courtesy of MnDOT).

  • Dynamic Ridesharing: This strategy involves travelers using advanced technologies, such as smart phones and social networks, to arrange a short-notice, one-time, shared ride. This facilitates real-time and dynamic carpooling to reduce the number of auto trips/vehicles trying to use already congested roadways.
  • Dynamic Routing: This strategy uses variable destination messaging to disseminate information to make better use of roadway capacity by directing motorists to less congested facilities. These messages could be posted on dynamic message signs in advance of major routing decisions. In an ATDM approach, real-time and anticipated conditions can be used to provide route guidance and distribute the traffic spatially to improve overall system performance.
  • Dynamic Transit Capacity Assignment: This strategy involves reorganizing schedules and adjusting assignments of assets (e.g., buses) based on real-time demand and patterns, to cover the most overcrowded sections of network. In an ATDM approach, real-time and predicted travel conditions can be used to determine the changes needed to the planned transit operations, thereby potentially reducing traffic demand and subsequent delays on roadway facilities.
  • On-Demand Transit: This strategy involves travelers making real-time trip requests for services with flexible routes and schedules. This allows users to request a specific transit trip based on their individual trip origin/destination and desired departure or arrival time.
  • Predictive Traveler Information: This strategy involves using a combination of real-time and historical transportation data to predict upcoming travel conditions and convey that information to travelers pre-trip and en-route (such as in advance of strategic route choice locations) in an effort to influence travel behavior. In an ATDM approach, predictive traveler information is incorporated into a variety of traveler information mechanisms (e.g., multimodal trip planning systems, 511 systems, dynamic message signs) to allow travelers to make better informed choices.
  • Transfer Connection Protection: This strategy involves improving the reliability of transfers from a high-frequency transit service (e.g., a train) to a low-frequency transit service (e.g., a bus). For example, the train is running late, so the bus is held back so train passengers can make their connection with the bus; or providing additional bus services at a later time to match the late arrival time of the train. This ensures that the connections are not missed.

2.3 Active Parking Management

Active Parking Management 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. 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. Examples include:

  • Dynamic Overflow Transit Parking: This strategy dynamically utilizes overflow parking facilities in the vicinity of transit stations and/or park-and-ride facilities when the existing parking facilities are at or near capacity. The overflow parking are typically underutilized, such as large retail parking lots, and transit agencies could have agreements with these entities for occasional use of predesignated, underutilized areas of the parking lots. In an ATDM approach, the parking demand and availability is continuously monitored and real-time determinations are made if overflow parking is needed, and accompanying dynamic routing information would be provided to travelers.
  • Dynamic Parking Reservation: This strategy provides travelers with the ability to utilize technology to reserve a parking space at a destination facility on demand to ensure availability. In an ATDM approach, the parking availability is continuously monitored and system users can reserve the parking space ahead of arriving at the parking location.
  • Dynamic Wayfinding: This is the practice of providing real-time parking-related information to travelers associated with space availability and location so as to optimize the use of parking facilities and minimize the time spent searching for available parking. In an ATDM approach, the parking availability is continuously monitored and routing information to the parking space is provided to the user.
  • Dynamically Priced Parking: This strategy involves parking fees that are dynamically varied based on demand and availability to influence trip timing choice and parking facility or location choice in an effort to more efficiently balance parking supply and demand, reduce the negative impacts of travelers searching for parking, or to reduce traffic impacts associated with peak-period trip-making. In an ATDM approach, the parking availability is continuously monitored and parking pricing is used as a means to influence travel and parking choices and dynamically manage the traffic demand.

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