Procedimientos y análisis de la información

Among the 35 BHLS sites described, only 10 are applying the quality certification of the line by using this EU standard. Some of them do so in a contractual context, with possible “Bo- nus / Malus” impacts. Generally, it was very difficult to collect these quality indicators data. Various reasons can be highlighted, in particular the data confidentiality. Due to competitive tendering situations, operators are reluctant to share data with the public domain. Another reason seems to be the cost of collecting data and completing surveys. In some cases such data were not yet available.

Highlighted below are some results on the reliability objectives (% of passengers having a bus on time) received from sites:

Regularity, punctuality target

Threshold

achieved Observation

Nantes (Busway) 90% (i+2min) 98% High efficiency

Fastrack (B) 95% (H-1min;H+5min) 97,5% High efficiency

Twente (line 2, 3) 80% (H-1min;H+5min) 94,7 / 97,6% Good protection

Paris (TVM) 90% (i+2min) 95,8% Heavy loading rate

Grenoble (line 1) 90% (H-1min;H+5min) 95 Good results

Leeds 95% (H-1min;H+5min) 93% Good protection

Almere (network) 80% (H-1min;H+3min) 91,4% High efficiency Prague line 213 80% (H-0min; H+2min) 78 - 86 % Low level of RoW Gothenburg (line 16) 80% (H-30s; H+3min) 75% Passenger congestion

80 % (i +/- 20%i) 93 %

Lisbon (all net-

work)52 _{85% (H-0min to H+5min) 87%} Low level of RoW

Legend: where i=interval (regularity objective) and H = scheduled time (punctuality objective) Table 16: Regularity / punctuality data collected from some BHLS schemes

It was recognized that investment in infrastructure improvements resulted in good levels of regularity being achieved. RoW contributes to reduce the problems in peak hours (which are sometimes only for short periods along the day), so that people can rely on a consistent run-

52_{For routes with headways less than 20 minutes, the regularity is measured from the headway and not from the}

schedules. For example, a route with a programmed headway of 10 minutes (one bus each 10 minutes); the regu- larity target is achieved if a bus passes 8 to 12 minutes after the previous bus (i.e. planned headway +/- 2 min- utes). If the route has headways bigger than 20 minutes, then punctuality is measured from the schedules. The quality measurement thresholds achieved include all trips made (weekdays and weekends), but they do not penal- ise for any trips that were not made due to external factors, beyond the control of the Operator (for example, if there is an accident in the street).

Regularity allows capacity

ning time throughout the day. “Urban” RoW seems to be more a tool for offering regularity than a better speed at every time.

Through these examples, we can consider that:

- For a very good BHLS level, the objective of 95% appears to be achievable.

- An objective of 95% is considered for providing an efficient high frequency, and conse- quently the high capacity expected.

- The level recommended in the CEN Standard (80%, H-1min, H+5min) seems to be not enough for achieving a full BHLS level in working days (higher frequency).

Gothenburg Line 16 is presented here as an example of these issues in practice. The time table of BHLS line 16 of Gothenburg (shown below), has a maximum of 12 services during the core peak hours53. This line still faces some challenges to achieve a very high level of headway regularity, when operating at short headways (5 minutes in the peak). The specific issues are (based on a discussion with the authority):

- Vasttrafik service lines outside Gothenburg typically reach a good reliability of 90% + ; however, the best tram lines in Gothenburg have only 82% on-time services (city centre); trunk line 16 (bus) has 75% on-time services, including in the city centre..

- A large cause of the unreliability is the unpredictable/uneven travel demand. More or less people are at the stop for an individual bus, so the dwell time may be shorter or longer than the average. This can cause the bus to be a little earlier or later at the next stop. When a bus is even slightly in delay on a busy route, it is likely to have more passengers waiting for it at the next stop, and thus have a slightly longer dwell time. Meanwhile, the bus behind faces less passengers, and starts to catch up. The cumulative effect over a number of stops leads to the classic ‘bus bunching’.

- The delays also impact on comfort. Passengers always try to get on the first bus that arrives, even if there is another bus directly behind it. When the headways are disrupted and two buses get close to each other, the first bus carries the majority of the passengers, so the pas- senger density can become higher than the norm and feel overcrowded and uncomfortable. Meanwhile the bus behind has plenty of space and even spare seats.

- A second cause of delays to Trunk Line routes is other services using the stops (also a prob- lem for some trams where they share stops with buses). Some bus routes do sell tickets on the bus, and they can obstruct and delay buses or trams behind them. There are 8 other lines into a same central corridor with this line 16.

- For operating better such high capacity, there is a need to help driver to be firm in managing the door closings, for example, with the help of a ring announcing the door closing, like in a rail system.

- Drivers no longer sell tickets on the vehicle. When they stopped selling tickets, punctuality improved by 2-4%.

The timetable of the line 16, the biggest line with bi-articulated buses in Gothenburg

53 _{Like the scheme in Utrecht, the peak hours are heavily crowded, and so could fit with a tramway}

The calculation for the CEN norm does not provide insights on the irregularity level of de- layed passengers. On the other hand, there is a high need to control when and where the ir- regularity is observed. Hence, other indicators are needed and used, although these are usu- ally not published. We think that sharing such results and launching a benchmarking action or a relevant research action could be fruitful for increasing the knowledge in RoW.

Figure 24: Zurich, mean schedule deviation by time of day at stop level – line 31

The PT authority of Zurich, which has one of the best networks in Europe54 _{in term of use}

and efficiency, shows an impressive quality level although it does not use the CEN standard. Despite a high frequency of all tram and bus lines, all lines are scheduled, and the quality objective is to follow up the schedule adherence, at all stops, at all services. The authority has set up different and numerous analysis, regarding travel time (distribution), speed (distri- bution), punctuality (deviation at stops, % of departure on time), regularity (distribution at route and stop level).

As shown into the figure 24 (analysis of the bus line 31 described as a BHLS), the deviation at all stops allow to better identify when and where are the problems55_.

b - Loading rate indicator

Highlighted below are results of the loading rates (% of passengers having a bus with a ca- pacity below 4 passengers standing / m2), often responsible for irregularity:

Table 17 Threshold target Threshold achieved observation

Nantes (Busway) 80% Over 80

Paris (TVM) 80% 76,7% Often overcrowded

Gothenburg (line16) Problems of capacity at peak hours (schools university) Fastrack (Kent) No problem of capacity

Prague line 213 2,6 pass/m2 (average peak) 2,76 pass/m2

The results highlight the difficulty in providing passenger comfort, particularly at peak hours on BHLS services. “Comfort” is taken as a level below 4 persons per square meter according to the European CEN standard, i.e. as specified for the Busway in Nantes, the TVM in Paris, the line 11 and 12 in Utrecht, the line 213 in Prague.

A good BHLS line seems to be always more attractive than expected, modelling tools often result in underestimations of ridership. Such trends are also observed in tram or metro pro- jects.

54 _{590 trips per inhabitant, a PT market share of 45%.}

55 _{Reference, study “quantifying public transport reliability in Zurich” by Nelson Carrasco, ETH,}

c- Availability rate

This item concern technical and human factors, such as breakdowns or driver absentees at departure. There are several ways of calculation.

Highlighted below are results on the availability rate (% of available services):

Table 18 TVM Busway Grenoble _{(line 1)} Fastrack _{(Kent) (line 213)}Prague Barcelonna _{(route 64) (guided bus)} Castellón Availability factor 99% 99,90% 99,90% 99,52% 99,80% 98.51% 98.00% Regarding these figures, and even though few data have been collected (perhaps not on the same basis…), it can be stated that:

- The bus technology can achieve a very good level of availability (with diesel and gas). - For a full BHLS level, a rate over 99% can be achieved, which highly contributes to quality. - The slightly lower level of Castellón is perhaps due to the fact that this route has been re-

cently opened (June 2008) with trolleybuses.