The descriptive statistics for the period between 2009 and 2013 shows similar trends to those discovered in the additional category A SPaD analysis (Section 5.3.5). The majority of the driver-related SPaDs tend to happen in locations where conflicting movements can occur. All of the worst performing locations fall into this category.
The conflicting movements are often caused by presence of turnback facilities and sidings at these locations. Hence the association with passenger overcarried and wrong route events. One of the unique features of the sidings and depot is presence of ground position lights. As the name suggests, these signals are located on the ground level and are often combined with direction indicators, all of which differ from the arrangements elsewhere in the system. Furthermore, due to the metrocar design visibility of such signals is obstructed from short distances or requires stand-up driving. As some of the SPaDs in these locations happened in sidings, the GPL are potentially an important causal factor.
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High proportion of the disruption related SPaDs means that drivers had encountered signals they have not expected to see. As drivers do not receive the most up to date information about the state of the system, their SA drops. Moreover, prolonged stops (waiting for a signal to clear) cause disengagement from a driving task thus
increasing risk of SPaDs due to lower SA (Naweed and Rainbird, 2014). Madigan et al. (2016) discovered that events not encountered in normal operations are important contributory factor in rail incidents, especially in SPaDs. Repetitive experience can form an expectation bias and cause loss of the SA (O'Connell et al., 2015). The semi-structured interviews revealed that more experienced drivers know how to interpret different signs to build up their situation awareness. For example, not meeting a train in opposite direction in a usual spot advices about a disruption further ahead. Dray et al. (1999) also found that experience, or lack of it, can be the PSF for metro drivers.
Research from the automotive industry does not show relationship between experience and SA (Underwood et al., 2013), but it does not take into account repetitiveness of the task in timetabled driving. The problem is acknowledged in the railway industry with work being done on improving drivers’ SA by using emerging technologies, e.g. DAS (Roth et al., 2006; Young and Grenier, 2009; Tschirner et al., 2013). Apart from being low on priority list of SDCs, the reliance on analogue radio system can limit communication capabilities (Roth et al., 2006). One of the solutions explored by Tyne & Wear Metro is linking the in-cab DAS with the customer services twitter account to provide live alerts to Tyne & Wear Metro drivers too.
Associations found with locations of different ATP and signal faults. Even though the semi-structured interviews and workshops did not reveal any associations of these incidents with drivers’ performance, there is a bigger concentration of signals and ATP equipment at stations with conflicting movements. Hence there is an elevated risk of SPaDs but also higher probability of a technical fault.
Tyne & Wear Metro owned infrastructure has significantly inflated category A SPaD rates compared to Network Rail infrastructure. The main difference between two parts of the system is use of different design signalling. Tyne & Wear Metro drivers receive reduced advanced warning on the Metro infrastructure, which is the busiest part of the system. This is not a direct failure mechanism but PSF increasing SPaD risk. It contradicts findings from mainline railways, where Li (2004) demonstrated that 4-aspect signals have more multi-SPaD occurrences. However, these findings do not account for levels of service and frequency of red aspects encountered. In mainline
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railways 2-aspect and 3-aspect signals are used in less busy systems than 4-aspect counterparts. On the contrary, the Network Rail part of Tyne & Wear Metro does not have so many conflicting movements thus affecting the incident propagation. Such relationship is also supported by category A SPaD correlation with number of trains in the network (see Table 12). The importance of fatigue and arousal levels is demonstrated by statistically significant correlation with proportion of drivers who have been on shift for two hours.
As for non-disruption situations, the causal factors identified in Section 5.3.5 are similar to the findings presented by Li (2004) from mainline railways but with less emphasis on immediate physical environment PSFs. The daily profile of category A SPaDs occurrence in Tyne & Wear Metro is similar to mainline railways except for a night peak, which is usually attributed to freight trains. According to Li (2004) these peaks are consistent with circadian patterns and thus support importance of personal factors. The discussions facilitated during the workshop revealed that many of the SPaDs are Start Against Signal SPaDs (SASSPaD), although specific locations were not provided. This does not allow making any assumptions on effects of specific design features but allows exploring other PSFs. Even though DOO dispatch
eliminates risks of poor communication between a driver and dispatcher in SASSPaD propagation, it increases drivers’ workload (Basacik et al., 2009). Monitoring of the platform-train interface is a task which competes with signal checks on departure even though a correct sequence is established in the rulebook. The daily incident peaks coinciding with the maximum passenger flow times suggest a more
demanding PTI monitoring task which can in turn distract from the signal checking task.
Frequency distribution of category A SPaDs in mainline railways is also similar to Tyne & Wear Metro but for February peak. The peak in summer is assumed to be caused by heat, pollen levels, sun height, foliage, operational factors, sociological factors and individual factors (Li, 2004). Assuming direct relationship of these factors with human performance, there must be summer peaks in other driver-related
incidents but none are observed. Hence it is possible to shortlist only seasonal PSFs directly affecting interaction with signals, e.g. foliage obstruction, sun height. On the other hand, most of the driver-related incidents in Tyne & Wear Metro have a peak in period 11 onwards. In the semi-structured interviews, the drivers noted that lower
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number of daylight hours cause fatigue and drowsiness, whereas sociological factors are more acute due to the “financial pressures imposed by Christmas”.