(Re)envisioning Hamilton Street Railway

A systematic review of Hamilton’s transit network

Hamilton City Council approved the 10 Year Local Transit Strategy in March 2015. Building upon previous plans that considered how to prepare for moving people quickly and efficiently across Hamilton, the 10 Year Local Transit Strategy focuses on refining the customer experience, addressing system deficiencies, revising service standards, adding capacity, and adding rapid transit (the BLAST network) in Hamilton. Completing the implementation of the Strategy will ultimately mean a 50 per cent increase in transit service across the city, and will involve a total of $300 million capital investment in public transit.

As recommended in the strategy, we will be reviewing the design of the transit network to ensure it is serving the needs of our customers. Some of the day-to-day challenges that HSR faces are linked to the design of the network, and it appears that with the amount of growth and development that Hamilton has experienced – and is continuing to experience – we may no longer have a transit system that is designed to take customers where they want to go, when they want to go there. We are working with the Civil Engineering Department of McMaster University and the McMaster Institute for Transportation and Logistics (MITL) on a project with two key objectives:

  1. To arrive at an understanding of the perceived and desired quality of HSR service from the point of view of a wide range of Hamilton residents including those who use transit regularly or not at all.
  2. To suggest a multi-criteria reconfiguration of HSR service based on the evidence from data collection and modelling efforts.

Project Timeline

Reenvisioning HSR Project TImeline

Benchmarking

July to December 2018
What is the current quality level of HSR service? How is it perceived?
The first objective of the project is to benchmark the quality level of current HSR service using two sets of measures: customer perspective (current and potential) and performance quality.

To measure public perception, the level of quality perceived by current customers as well as the desired quality of both current and potential customers will be assessed. This is to measure: the significance and the impact of each service attribute on the probability of increased ridership, the willingness-to-pay for each service attribute, and the influence of attitudinal orientation on ridership. This will provide a blueprint for accommodating customers’ perspectives in the quality improvement process of HSR service.

To measure the performance quality of HSR service, two measures will be used: a survey of transit operators’ perspectives; and performance quality measures (service reliability, dependability, and bus bunching.) Advanced Vehicle Locators (AVL) data will be combined with machine learning tools to quantify service discrepancies from schedule adherence and routes of critical performance.


Initial Engagement

September 2018 to January 2019
User surveys, data analysis & service quality benchmarking
A combined stated preferences / revealed preferences survey will be developed for current and potential customers. Data will be collected through a survey of approximately 1000 households, administrated by a third party. To strengthen the representation of current customers, the survey will be available through various online channels as well as through planned community outreach events. A survey developed specifically for HSR operators will be administered by the HSR in conjunction with the customer survey.

Deliverables:

  • User survey
  • Data analysis
  • Service quality benchmark working paper

Network Reconfiguration

January to October 2019
How can we reconfigure the network?
The second objective of the project is to reconfigure the HSR network based on results from the surveys. Three ‘families’ of measures will be used to inform the scope and details of an HSR network reconfiguration:

  • Service quality
  • Travel demand modelling
  • Network optimization and system robustness

A comprehensive travel demand model for the City of Hamilton will be developed based on the 2016 Transportation Tomorrow Survey data. An optimization model of HSR service with a multi-objective approach reinforced by machine learning techniques will use Automatic Vehicle Locator (AVL) data and incorporate several parameters: quality, operation, travel demand, cost, fleet size, current service, and human resources (operators).


Additional Engagement

February 2019 to October 2019
How can we reconfigure the network?
Extensive public engagement will occur once potential network reconfiguration options have been developed. Engagement efforts will make use of both traditional (Public Information Centres, open houses/workshops) and modern (real-time consultation-on-a-bus, network modelling) techniques. 

Deliverables:

  • Transportation Tomorrow Survey data analysis
  • AVL performance assessment
  • System reconfiguration Reinforced learning and optimization
  • Travel demand and service reconfiguration working paper
  • Robustness analysis
  • Network vulnerability index
  • Network analysis working paper

Network Robustness

September 2019 to February 2020
How do we limit the vulnerabilities of the system?
Following that, a network-based assessment model will be developed to quantify the HSR network robustness. All nodes (station and/or stop) and links (routes) will be evaluated with respect to the overall network robustness. An HSR system Vulnerability Index (VI) for each system component (stations and routes) will be created to test system-wide performance. The network assessment and service reconfiguration work will happen in parallel.


Council Presentation

March 2020
The final project report will be presented to Council.

 

HSR Reenvisioning partner logos