Managing Unplanned Rail Disruptions: Policy Implications and Guidelines Towards an Effective Bus Bridging Strategy

Abstract

Bus bridging is a key strategy used by transit agencies to handle rail service interruptions. In practice, buses are dispatched from scheduled services to act as temporary shuttles along the disrupted rail segment. This study provides a robust analysis of four factors affecting bus bridging policies: 1) initial dispatch direction of shuttle buses, 2) dispatch time (i.e., the response time for requesting shuttle buses), 3) uncertainty in predicting the incident duration, and 4) reduction of metro passengers demand because of disruption. A user delay modeling tool is used to assess various bus bridging policies based on their resulting users’ delays (for affected passengers) and other system performance measures. The tool was validated, and sensitivity analysis was conducted based on real disruption scenarios that suspended various segments of the metro service in the City of Toronto. The main results indicate that: 1) the initial dispatch direction of shuttle buses should take into consideration the demand at the disrupted segment while maintaining a moderate level of shuttle bus utilization; 2) a 1-min increase in the dispatch time causes about 0.4 min additional waiting time at disrupted metro stations per passenger; 3) incidents with high forecasting errors can cause excessive delays for metro passengers and significant wasted time of non-utilized shuttle buses; and, 4) significant users’ delay savings are observed at higher demand reduction levels. This paper provides transportation practitioners and planners with a better understanding of the different aspects of bus bridging policies based on users’ delays and shuttle buses’ performance metrics.

Public transport access to drug treatment before and during COVID-19: Implications for the opioid epidemic

“…From 2019 to 2020, thousands of residents across Toronto crossed these thresholds due to COVID-19 transit reductions, further tightening patients’ access windows and reducing their resilience to the often unpredictable clinic lines ( Lam et al, 2020 ), as well as transit disruptions. ( Itani et al, 2019 , Liu et al, 2020 ) At almost every travel window, whether weekdays from 8am-9am, 11am-12pm, 3pm-4pm, or Saturday 9am-10am, we estimate that hundreds of potential people using opioids within the city's 5th quintile of material and social deprivation had travel times to treatment cross 30 and 20-minute time thresholds. The third analysis found that residents only faced increases in travel time by over 10 minutes on weekdays (an additional 2.5 hours of travel time weekly).…”

Access to Opioid Agonist Treatment during COVID-19 Public Transport Disruptions

“…In the first two analyses, this paper analyzed DAs whose travel time exceeded 20 and 30 minute thresholds to their nearest clinics. From 2019 to 2020, thousands of residents across Toronto crossed these thresholds due to COVID-19 transit reductions, further tightening patients' access windows and reducing their resilience to the often unpredictable clinic lines (Lam et al, 2020), as well as transit disruptions (Itani et al, 2019;Liu et al, 2020). At every travel window, whether weekdays from 8am-9am, 11am-12pm, 3pm-4pm, or Saturday 9am-10am, we estimate that hundreds of potential opioid users within the city's low-income or carless populations had travel times to treatment cross 20 and 30-minute time thresholds.…”

Assessing the Bus Bridging Effectiveness on the Operational Resilience of the Subway Service in Toronto

“…The second metric is the total number of shuttle buses. Both metrics are part of the outcome estimated by the tool developed in Pender et al ( 6 ) and Itani et al ( 8 ). The estimated delays of subway passengers also consider the time needed to dissipate the queues after a disruption is over.…”

“…Data-driven analysis of bus bridging operations is key to understanding how this strategy affects the resilience of the subway service. A decision support tool was developed recently to help agencies manage unplanned service interruptions using optimized bus bridging strategies (7)(8)(9).…”