Transit data platform scope

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Transit data platform scope

Transit data platform scope

Suggested general requirements

Commercial off-the-shelf (COTS) cloud-based Software-as-a-Service (SaaS) platform that is already developed, deployed, and functioning in the real world

Hosted by the vendor such that no system software needs to be maintained by the Agency (cloud-based)

Accessible through any modern web browser. The solution should be entirely cloud-based and shall not require VPNs

99.9% uptime or greater, with over-the-air updates and upgrades included in the license for no additional cost

Unlimited platform logins for agency staff

Data storage for a minimum of 3 years, unless the contract is terminated prior

Data quality and monitoring

Ability to ingest incoming Automatic Vehicle Location (AVL) data from various devices up to every 1 second

Ability to combine multiple vehicle position feeds, in real-time, with the intent of producing a higher level of data accuracy and data redundancy in case one feed goes down

Ability to ingest vehicle assignment data

Automatic assignment technology to ensure that data is correctly matched to the right route, trip, etc. even if an operator does not login to provide assignment

Ability to automatically ingest and process GTFS schedule data, up to every hour if changes have occurred. No human input should be required

Tools to automatically monitor data feed uptime and health

Ability to generate and store data attributes, such as on-time performance, actual headways, and scheduled headways for every Global Positioning System (GPS) position update—not just when a vehicle is at a stop or a timepoint

Real-time passenger information

Passenger predictions

Ability to generate accurate ETAs/predictions for passengers based on historical data and real-time road conditions which update with every new GPS coordinate in real time

Ability to support GTFS-rt, including:

  • GTFS-rt Vehicle Positions
  • GTFS-rt Trip Updates
  • GTFS-rt ServiceChanges v3.1

Ability to factor in real-time service adjustments including:

  • Canceled trips
  • Added trips
  • Detours
  • Skipped stops
  • Modified departure times

Ability to avoid “ghost buses” in predictions

Ability to include real-time vehicle crowding levels in predictions when data is available

Ability for passengers to access passenger information, including ETAs and service alerts, via an automated SMS service

Ability for passengers to access passenger information, including ETAs and service alerts, via an automated Interactive Voice Response (IVR) service

Passenger-facing service alerts

Ability to create and edit real-time service alerts at the system, route, or stop level

Ability to view upcoming, current, and past service alerts through real-time vehicle monitoring functionality

Ability to publish passenger-facing service alerts in the GTFS-rt Service Alerts format and to Twitter

Ability to automatically populate passenger-facing service alerts based on real-time changes to service

Proof of successful outcomes at a transit agency of similar size around service alerts to riders

Real-time and historical analytics

Live map and AVL monitoring

Ability to view a live map of all fixed route vehicles that are reporting location in real time

Ability to display relevant vehicle information, including route, trip, block, operator, and on-time performance for vehicles throughout the network

Ability to filter and toggle through map, list, and ladder views to easily find and identify potential service issues

Proof of successful outcomes at a transit agency of similar size around AVL monitoring

Dynamic service management

Ability to control which agency staff can adjust service

For approved staff, ability to create the following service changes:

  • Add trip
  • Cancel trip
  • Create detour
  • Close stop
  • Modify departure times

For approved staff, ability to change the assignment of a vehicle, shifting it from one route/trip/block to another

Ability to see real-time changes to service through the real-time vehicle monitoring functionality

Ability to continue to provide real-time information and predictions for detoured routes

Ability to reflect service changes through GTFS-rt data feeds and automatically update passenger-facing data

Ability to integrate detours created by the system with common mobile applications, like Transit App, to better inform riders

Ability to incorporate information about changes to service into historical data reports

Proof of successful outcomes at a transit agency of similar size around dynamic service management

GPS replay

Ability to play back historical vehicle locations and movements in a dynamic map, by route or a specified vehicle, and by date/time range

Ability to investigate vehicles by:

  • Route
  • Destination
  • Trip or block being operated
  • On-time performance or headway adherence
  • Date and time range

Proof of successful outcomes at a transit agency of similar size around vehicle movement data

On-time performance reporting

Ability to view a summary of network-wide on-time performance for all routes, including daily, weekly, and monthly trends

Ability to investigate on-time performance issues by:

  • Route
  • Stop along a route
  • Distribution of how early and how late
  • Time of day
  • Tabular heatmap format organized by schedule

Ability to:

  • Edit how “on-time” is defined
  • Adjust the dates/times over which the reports are run

Reports include information about service changes that impact on-time performance

Reports include all scheduled stops with, as well as without, an observed departure time (including missed data and missing service)

Proof of successful outcomes at a transit agency of similar size around on-time performance monitoring

Speed map

Ability to display average vehicle speeds for a selected route at a resolution of up to 25 meters to determine specific intersections or route segments that may be causing delays

Ability to view speeds by different percentiles, averages, and by variability to compare the median speed relative to free-flow speeds

Ability to customize views based on:

  • Route
  • Route direction
  • Date and time range
  • Day types (weekday, Saturday, Sunday)
  • Relative speed ranges

Ability to download speed data to CSV

Ability to access data via API and import into GIS

Proof of successful outcomes at a transit agency of similar size around speed map analysis

Operator performance reports

Ability to view on-time performance at the operator level, for all operators

Ability to view operator on-time performance reports by:

  • Route, trip, and stop
  • All stops or timepoints only
  • Customizable dates and time ranges
  • Layover use and utilization
  • On-time performance

Proof of successful outcomes at a transit agency of similar size around operator reports

Run-time analysis

Ability to analyze run-times and schedule optimization, including:

  • Overall system performance
  • Route-level running times
  • Trip-level running times for a route

Ability to generate suggested run-times that maximize potential on-time performance based on historical run-time data

Ability to calculate impact on on-time performance if suggested runtimes were used in the schedule

Ability to view and filter run-times data on:

  • Stop-to-stop route segments
  • Timepoint-to-timepoint route segments

Proof of successful outcomes at a transit agency of similar size around running time analysis

Headway reporting

Ability to view a summary of the overall headway adherence across all routes, including the number and percentage of departures that are bunched, gapped, and expected based on acceptable headway criteria

Ability to investigate headway performance by:

  • Route
  • Stop along a route
  • Time of day

Ability to:

  • Edit definitions of “expected,” “bunched,” or “gapped” headways
  • Adjust the dates/times over which the reports are run
  • View all stops or timepoints only

Proof of successful outcomes at a transit agency of similar size around on-time performance monitoring

Driver-facing onboard application

Driver-facing onboard application that gives schedule and headway adherence guidance to operators as well as a visual map of their route

Ability of application to run on commercially available tablets

Ability to inform vehicle operators of changes to service

Map view that includes detours and other changes to service, including stop closures, modified departure times, etc.

Ability to use text-based communication between dispatch and operator within the application

Ability to count passengers in real time

Proof of successful outcomes at a transit agency of similar size around driving-facing applications

Connections with onboard hardware

Automatic Passenger Counters (APC)

Ability to track boardings and alightings with greater than 95% accuracy

Ability to collect boarding and alighting data and match to GTFS route IDs, trip IDs, block IDs, direction IDs, stop IDs, etc. (i.e. no additional data feeds or configuration should be required)

Ability to determine accurate vehicle occupancy figures off of the raw boarding and alighting data

Ability to provide passengers with live crowding estimates within the GTFS-rt format as well as a JSON API for riders to access this data in commonly used mobile apps

Ability to display live crowding estimates within a live map and other real-time vehicle monitoring tools

Ability to store data and keep accessible for historical ridership analysis for a minimum of 3 years

Proof of successful outcomes at a transit agency of similar size around APC data

Automatic Voice Announcement System (AVAS)

Ability to function fully off public GTFS and GTFS-rt data feeds already available (i.e. no additional data feeds or configuration should be required)

Ability to comply with all ADA guidelines for next stop announcements

Ability to trigger arrival announcements as a vehicle nears a stop, within a user-configured distance of the stop

Ability to trigger next-stop announcements as a vehicle departs a stop, within a user-configured distance of the stop

Ability to customize and configure announcements for events including stop requested, door opening, door closing, lift requested, and other common on-vehicle announcements

Ability to indicate arrivals on a LED display within the vehicle

Ability to access and manage settings via online portal

Proof of successful outcomes at a transit agency of similar size around automatic voice announcements

Application Programming Interface (API)

A secure and authenticated API that allows API keys to be created for each individual consumer of the data, as well as rules surrounding which data they can access

Ability to support all common GTFS-realtime data feeds, including:

  • GTFS-rt Trip Updates
  • GTFS-rt Vehicle Positions
  • GTFS-rt Service Alerts
  • GTFS-rt ServiceChanges v3.1

Ability to process real-time and historical data in a human-readable format such as JavaScript Object Notation (JSON)

Ability to provide thorough API documentation to help staff and partners understand how to access the data

Automated ridership data validation

Ability to automatically ingest raw Automatic Passenger Counter (APC) data from hardware or existing data pipelines without requiring new hardware purchases

Ability to accurately match APC data with schedule information, enriching it with route, stop, and trip details

Automated detection and correction of common APC data errors, including incomplete data sets, anomalies in rider load data, and partial APC coverage

Ability to filter out extraneous data, such as driver boardings and layover activity, ensuring only relevant ridership data is used

Automated expansion of APC data for agencies with partial fleet-wide coverage, filling gaps based on historical ridership patterns

Ability to output highly accurate APC data for National Transit Database (NTD) reporting, compliance, grant writing, and operational efficiency improvements

Ability to automate the validation process, reducing manual effort and staff workload while maintaining data accuracy

Proof of successful outcomes at a transit agency of similar size around automated ridership data cleaning

Ridership data analytics and performance monitoring

Ability to transform raw ridership data into actionable insights for service planning and operations

User-friendly dashboard that visualizes ridership trends with interactive graphs and maps

Ability to analyze ridership data across multiple variables, including:

  • Dates and times of day
  • Routes, stops, and trips
  • Blocks and service levels

Ability to track and analyze long-term ridership trends, identifying shifts in demand and seasonal variations

Ability to assess the impact of service changes on ridership and performance through historical benchmarking

Ability to identify inefficiencies and optimize service at the micro level by analyzing data at the stop, trip, and route levels

Ability to generate, save, and distribute custom reports for internal analysis and decision-making

Ability to monitor APC system health, ensuring agencies are aware of outages or issues that might contribute to inaccurate ridership data

Open access to detailed ridership data across departments, enabling teams to self-serve analytical needs without reliance on pre-aggregated reports

Ability to automate common analytical workflows, including corridor planning, trend analysis, and geographical mapping, reducing staff workload and improving efficiency

Ability to reduce reliance on individual staff members for data analysis, eliminating knowledge silos and minimizing contingency risks

Proof of successful outcomes at a transit agency of similar size around ridership analysis and reporting

Ability to manage full-scale data pipeline from raw data processing to dashboards that inform service planning

Ability to leverage GTFS, vehicle assignments, and raw APC data to automatically determine valid events, clean data as necessary, and ensure an accuracy level of 95%+ (as defined by the NTD) for both UPT (“unlinked passenger trips”) and PMT (“passenger miles traveled”)

Ability to assign confidence values to each APC event; allowing the system to dynamically determine the proper cleaning methods to be applied at the time of processing

Ability to understand APC hardware's health and automatically scan vehicles to detect whether they’ve delivered anomalous data

Ability to schedule proactive notifications when issues are detected

Ability to easily visualize, route, stop, trip, block, and vehicle-level analytics with tabular, graphical, and geospatial analyses

Ability to calculate advanced KPIs, such as ‘boardings per revenue hour’ and ‘passenger miles traveled’

Ability to upload custom shapefiles so that ridership can be grouped, filtered, and analyzed by geography

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