Integrated Corridor Management Initiative – ICMS Surveillance and Detection Needs Analysis for the Transit Data Gap

5.0 Applicable ICM Techniques

Integrated Corridor Management is a complex topic. With seven possible transportation modes (arterial roadway, limited access roadway, roadway with managed lanes, toll roads, transit utilizing roadway right-of-way, transit using separate/exclusive right-of-way, and waterways), the number of possible combinations and permutations is 27 or 128 possible combinations. It is no wonder that no commercial-off-the-shelf (COTS) products for ICMS exist today. Adding to this the variations in configuration, capacity, and demand for each transportation mode in any given corridor, the complexity of corridor management might almost seem insurmountable.

5.1    ICM Strategies

There are some common threads through all of the ICM strategies. The events and scenarios used to justify ICMS deployments have common factors:

1. Recurring congestion (capacity overload)
2. Incidents (temporary decreases in capacity)
3. Planned events (need to temporarily re-allocate capacity from one use to another; add capacity; divert capacity demand to alternate modes, routes or schedules; and restrict capacity to prevent capacity overload or enhance safety of roadside workers)
4. Emergency events (implement pre-planned disaster plans to re-allocate capacity from one use to another, add capacity, divert capacity demands to alternate modes or routes, or restrict capacity to prevent capacity overload)

The response strategies also have common threads:

1. Information sharing/distribution
   • Coordinate responses to reduce the impact of events on system capacity.
   • Allow traveling public and trip planners to select alternative routes, schedules, and modes of travel based on current or anticipated travel conditions.
   • Share information on transit service regarding incidents, service status, vehicle location, and transit schedules.
2. Improvement of operational efficiency of network junctions & interfaces
   • Signal priority for transit – Give higher priority to high occupancy vehicles (HOV) to increase capacity (volume of people moved) of existing assets.
   • Signal pre-emption/”best route” for emergency vehicles – Optimize existing capacity for enhanced public safety.
   • Multimodal electronic payment – Decrease capacity bottlenecks by increasing the number of vehicles/passengers that can be processed per hour and facilitate shifts between travel modes and networks.
   • Transit hub connection protection – Decreases travel time (for some) and increases passenger satisfaction to encourage shifts of travel demand to under-utilized transit capacity.
   • Multi-agency/multi-network incident response – Reduce the impact of events on existing system capacity.
   • Coordinate operation between freeways and arterials – Coordination of ramp metering with arterial signals keeps freeway capacity restrictions from causing disproportionate arterial capacity restrictions or overloads. Coordination of off-ramp queues with arterial signal systems keeps arterial capacity restrictions from causing disproportionate freeway capacity restrictions or overloads.
   • Coordinate operation between arterial traffic and rail transit traffic – Allows better utilization capacity at intersections un-affected by rail operations to mitigate the capacity reduction caused by closed crossings congruent with rail operations.
3. Accommodation/Promotion of cross-network route and modal shifts
   • Modify transit priority parameters to accommodate timelier bus/light rail service on arterials – This should increase the volume of people moving through the corridor while reducing the travel time for transit travelers. This may be implemented as a function of the passenger count and amount of time a transit vehicle must be behind schedule before signal pre-emption is allowed.
   • Modify arterial signal timing to accommodate traffic shifting from freeway – Presumably this would allow additional traffic volume to shift from freeways to arterials without allowing the traffic volumes to reach critical limits on the arterial system. The major concern with this strategy, as expressed by stakeholders, is that freeway capacity is usually several times the potential capacity of adjacent arterial roadways, and un-restricted “dumping” of freeway demand on adjacent arterial roadways can result in arterial gridlock (capacity overload).
   • Modify ramp metering rates to accommodate traffic, including buses, shifting from arterial – This could involve giving priority to transit vehicles or HOV traffic to promote higher efficiency transportation modes, but could also involve throttling ramp metering rates to keep arterial traffic from overloading freeway/HOV lane capacities which results in congestion.
4. Promotion of network shifts
   • Promote route shifts between roadways via en-route traveler information – Similar to the second bullet under “information sharing/distribution” but expressed as a method to reduce demand on a roadway by shifting the traffic volume to alternate freeway, tollway, or arterial traffic routes.
   • Promote modal shifts from roadways to transit via en-route traveler information devices – Similar to the above strategy, but specifically directed at reducing demand on a roadway by shifting the traffic volume to un-utilized capacity on transit systems.
   • Promote shifts between transit facilities via en-route traveler announcements – Similar to the “information sharing/distribution strategy,” but directed at reducing demand on a transit link by shifting the travel volume to alternate transit routes.
   • Re-route buses around major incidents – Similar to promoting route shifts between roadways but directed at transit vehicles.
5. Management of capacity
   • Convert regular lanes to “transit-only” or “emergency-only” – This strategy reduces one form/direction of capacity in favor of higher efficiency transportation modes (transit vehicles) or to promote public safety (emergency vehicles) during emergencies.
   • Add transit capacity by adjusting headways and number of vehicles – This strategy adds capacity (passenger miles per hour) but assumes that the transit agency has the additional vehicles and personnel to provide the capacity.
   • Add transit capacity by adding temporary new service – This strategy can bridge gaps caused by loss of service on other transit routes or where there is a temporary demand surge associated with a planned event. This strategy also assumes that the transit agency has the additional vehicles and personnel to provide the capacity.
   • Lane use control (reversible lanes/contra-flow) – The strategy reduces one form/direction of capacity in favor of increased capacity in a direction or form that is more efficient or in higher demand.
   • Coordinate scheduled maintenance and construction activities among corridor networks – This strategy is directed at coordinating activities that will reduce transportation capacity in the corridor so that remaining capacity is sufficient for normal demands, or alternate capacity is provided to accommodate the demand shift from capacity restricted locations.

5.2    ICMS Tools and Techniques

While most of the research being done on transit management focuses on obtaining data for person capacity and schedule adherence, it is becoming increasingly apparent that ICMS deployments will be more focused and dependent on capacity data. The underlying truth is that you cannot reliably manage what you cannot measure. The review of the ICM strategies in the preceding section identifies five major strategies that the ICMS must support and how transit capacity monitoring is critical to the strategy:

1. Information sharing/distribution – Information sharing to coordinate responses and reduce the impact of events on system capacity will depend on the capability to monitor and model the impact of events on system capacity. This dependency means that it will be critical for ICMS implementations to collect real-time capacity data for both transit vehicles and the associated parking facilities, archive this data, and use AMS analysis of the historical data to calculate the remaining un-used capacity within the system.
2. Improvement of operational efficiency of network junctions & interfaces – Coordinated operation between freeways, tollways, HOV lanes, arterial roadways, and transit facilities will only be possible if real-time transit capacity and history-based capacity measures are available. This data can be used to give transit vehicles priority if the vehicle is behind schedule and to provide transit hub connection protection. Multimodal electronic payment of HOV, transit, and parking will also improve the efficiency of the network junctions and encourage commuters to make better transportation choices.
3. Accommodation/Promotion of cross-network route and modal shifts – This capability focuses on changing demand (volume) on one part of the network by shifting the volume to:
   • other routes;
   • non-peak travel periods; or
   • other travel modes.

This capability will be dependent on the availability of transit and parking capacity and transit vehicle location data at the ICMS to use for modeling and to compare with historical data. This capability is also dependent on the ability to modify transit priority parameters to accommodate a modal shift.

4. Promotion of network shifts – This capability will also be dependent on the availability of current speed and volume data at the ICMS to use for modeling and to compare with historical data. This will be used to reroute transit vehicles when necessary. In addition, it is necessary to disseminate pre-trip and en-route traveler information to promote network shifts.
5. Management of capacity – Management of capacity is concerned with providing enough capacity to meet demand. Adjusting transit capacity is dependent on the ability to add transit vehicles, adjust headways, modify schedules, or implement lane controls. The use of transit-only lanes, the road shoulder, and signal priority can increase the capacity. Transit capacity can be affected by parking capacity. Strategies to increase parking capacity, such as temporary lots and shuttles, can assist in increasing the transit capacity.

5.3    Pioneer Site Techniques

The pioneer sites identified collection of transit data as an important element of their planning. All of the pioneer sites have some transit vehicles with Automatic Vehicle Location (AVL). Most of the sites have, or are planning to have, complete AVL coverage on all transit vehicles. Several sites have bandwidth or other communication limitations that restrict how much and how often data can be collected from the transit vehicles. Vehicle location data on rail transit is not necessarily acquired using global positioning equipment as is done on bus transit. Several of the rail transit systems rely on sensors that detect when a vehicle passes a monitored location along the railway.

The AVL data is used to determine speed and schedule adherence. All of the sites have implemented Automatic Passenger Counters (APC) and are using the data to determine ridership and available capacity (although not in real-time). Most of the pioneer sites collect APC data at the end of the day.

The sites identified a need for multimodal electronic payment for tolls, parking, and transit. At this time, multimodal electronic payment is used primarily for the benefit of the consumer. Some agencies use electronic payment data for determining or validating ridership statistics. Most of the pioneer sites collect payment data at the end of the day.

Most of the sites plan to collect transit data by expanding the transit AVL capability, in order to determine travel time and schedule adherence. Many of the sites indicated a need for parking lot utilization information and the ability to provide the information to the traveling public.

Three of the sites specifically outlined transit performance requirements. These performance requirements included overall system performance measures such as the quality of service from the passenger’s point of view and route level performance measures. Route level performance measures include travel time, trip mileage, wait time, dwell time, speed, and passenger load. Most of the sites plan to monitor delays and schedule adherence, though these were not specifically cited as transit performance measures.

All of the sites had at least one strategy to improve the efficiency of network junctions. Two sites indicated that the data would also be used to coordinate transit priority between vehicles and signal systems.

Some of the sites had implemented Automatic Passenger Counters on some of the transit vehicles. However, the data from these devices appeared to be used for historical purposes.

Several sites indicated that en-route mode shifting is not feasible at present. Vehicle operators are the primary information source for passengers, but operators lack the necessary information to compare travel times between the modes and to determine availability of parking. This represents two problems:  getting the right information to travelers in a timely manner, and being able to analyze and predict sudden increases in passenger demand quick enough to make an effective response. Transit vehicle operator observations alone may not be enough to allow transit agencies to act in time to accommodate a sudden increase in demand.

The sites have found that mode shifting for planned events is feasible and transit providers are able to accommodate the extra capacity demand with pre-planning. Most of the sites plan to share congestion, volume, or travel time data with the public as a way to encourage mode, route, or departure time shifts. Many of the sites indicate that congestion data is used internally to determine the need to modify transit routes due to an incident.

All of the sites had strategies for shifting travel demand away from modes or locations with capacity problems, but none of the sites have clearly expressed how they plan to compare capacity on transit vehicles with vehicle capacity on roadways. No clear decisions were expressed about how to compare HOV capacity with traffic on other roadway segments. One site recognized that it would be useful to try and collect data about how many occupants were in the vehicles traveling on HOV lanes as well as passenger counts on transit vehicles so that person-miles of travel performance measures could be calculated accurately.

Where signal priority for transit vehicles was included as a management strategy, priority was based on schedule adherence criteria, and no mention was given as to weighting signal priority based on the number of passengers carried by the transit vehicle or the number of vehicles that would experience travel delays as a result of using signal priority. No mention was given to monitoring the operational status of the transit vehicles. For example, an empty bus dead-heading to the start of a route or a bus headed to a timed transfer point might merit additional consideration for signal priority.