ADHVARYU [2006]_Design of Bus Station_A Case Study in Brighton_{TEC}

$: ADHVARYU [2006]_Design of Bus Station_A Case Study in Brighton_{TEC}$
182 Calculating bus station capacity

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Design of bus station: acase study in Brighton

There are two key concerns in developing the proposals.The first is to generate workable solutions that are com-patible with the existing physical constraints of the

area and the operational constraints of buses and taxis. Thesecond is to make the bus station more accessible to wheel-chair users. The study emphasises that the process of bus sta-tion design could be enhanced by use of simple analyticaltools and hence need not be purely driven by architecturaland urban design considerations.

INTRODUCTION

This paper is based on a study undertaken on design of a busstation in Brighton - a town about 100 km south of London.The study covered the review of models for bus stop capacityestimation, issues realting to adapting such models for esti-mation of bus station capacity, use of a microsimulationmodel for estimating capacity of existing situation and theproposals, use of a graphic simulation tool for formulatingproposed physical layouts for the bus station, developing amethodology to evaluate bus station designs, and taxi rankcapacity estimation and its physical layout to the extent thatit enhances the performance of the bus station. However, inthis paper the discussions on development of a method forevaluation of bus station designs and capacity estimation fortaxi ranks and its alternative physical layouts are omitted, be-cause it would require a separate dedicated space. Also, onlytwo layouts of bus stations out of the proposed four are in-cluded in this paper. The discussion on models for estimat-ing bus stop capacity have able been considerably shortenedin this paper.

ESTIMATION OF BUS STOP CAPACITY: ABRIEF REVIEW

Estimation of bus stop capacity is now a well-researchedfield. There are various mathematical models available forestimating bus stop capacity. The theoretical basis for esti-mating bus stop capacity is briefly explained below. How-ever, firstly the time periods associated with a bus stop needto be highlighted.

Time periods associated with a bus stopA bus arrives at a bus stop and stops. The doors open andpassenger exchange takes place (ie, alighting and boarding ofpassengers), which may be serial or parallel. Doors then closeand the bus departs. The time elapsed during this period isknown as dwell time (tdwell). Tyler (2002) has distinguishedsix time-periods associated with a bus stop, which are ex-plained briefly as follows:

1 Queuing time (tq) is the time spent by a bus in a queueprior to entering the bus stop.

2 Clearance time (tclear) is the minimum [theoretical] timebetween the departure of one bus and the arrival of a sub-sequent bus in the bus berth.

3 Dead time (tdead) is the time that elapses in opening andclosing of doors plus the time associated with extendingramps/lifts/other equipment to facilitate alighting andboarding of disabled persons, if any.

4 Passenger service time (tpst) is the time elapsed while pas-senger exchange takes place.

5 Internal delay (tint) is the time spent by a bus waiting toleave the bus berth after it is ready to leave, but cannotactually leave as it is obstructed by other bus(es) in thebus stop area.

6 External delay (text) is the time spent by a bus waiting toleave the bus berth after it is ready to leave, but cannotactually leave as it is obstructed by other traffic outsidethe bus stop area.

If we reflect back on the definition of dwell time discussedabove, it would constitute a sum of time periods 3 to 6(above). Time periods 5 and 6 often occur concurrently, inwhich case the higher of the two would be used in estimationof dwell time. Clearance time has to be added to dwell timeto take into account the time taken to enter and leave theberth. Thus, the simplest possible theoretical model for esti-mating bus stop capacity may be given as:

The degree of saturation, which is a key performance mea-sure of a bus stop defined as the ratio of flow to the theoreti-cal capacity can be found as:

Bhargav Adhvaryu, University of Cambridge, UK

This paper1 investigates the design of busstations in a physically constrained area througha case study of Brighton Bus Station, which issituated in the historic core of the city abuttingthe railway station complex. Bus and passenger

data collection is primarily done manually andis supplemented by videography. The analysisof capacity of the existing bus station iscompleted using microsimulation software. Inaddition, a graphic simulation tool for tracking

the swept paths of buses, taxis, and lorries isused to formulate the proposed physical layoutsfor the bus station. The proposals wereevaluated using a simple evaluationmethodology developed in this study.

The author:Bhargav Adhvaryu

is ResearchAssociate at the

Martin Centre forArchitectural and

Urban Studies,Department of

Architecture,University of

Cambridge sinceDec 2004.

Before joining theMartin Centre, he

was in Indiawhere he spentfour years as a

lecturer and fouryears in an urban

planningconsultancy firm

as a projectmanager. He can

be contacted byemail at ba247

@cam.ac.uk

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Saturation = (Q/Qc) x 100 (%), where Q is the observed busflow.

Some models for estimating bus stop capacity The Convoy ModelThe Convoy Model which is based on the São Paulo (Brazil)experience is given as:

where,

The Highway Capacity Manual (HCM) 2000 ModelThe HCM 2000 Model (TRB, 2000) introduces a new conceptof using failure rate. Failure rate, which is derived from basicstatistics, is the probability that a queue of buses will not beformed behind a bus stop. Za represents the area under onetail of the normal curve beyond the acceptable levels of prob-ability that a queue will form at a bus stop. Typical values ofZa are obtained from standard tables. Suggested values of Zafor CBD stops range from 1.44 to 1.04 resulting in probabili-ties of 7.5% to 15.0%, respectively that queues will develop.For outlying stops, 1.96 is suggested as the value of Za result-ing in queues beyond bus stops only 2.5% of the times.However, in general, Za values of 1.44 (representing 7.5%probability) are acceptable.The theoretical capacity of the berth is then given as:

The value of Neb has to be discounted for more than oneberth depending on whether the bus stop is in-line or off-line. It is suggested that values of off-line would be lesserthan in-line.

Microsimulation ModelsFernández (2001) tested the Convoy Model for a one-berthbus stop at Manor House Station, London. The results were2.7 times the observed data, and hence the model did not de-liver good results in this case. It was pointed out that theconstants assumed in the formula, which are essentially ap-plicable to high capacity busways, were not applicable to abus stop in the UK urban environment, and hence the over-estimation in capacity.

The HCM 2000 model is simple and straightforward andhas a good conceptual underpinning. However, its inherentnature of using gross values makes it too simplistic for appli-cation to real-life situations. In addition, since the gross val-ues used in the model are derived mainly from US-based em-pirical studies, its application to the UK may not render ap-propriate results.

It appears that tackling the issue of not using gross valuescould be dealt with by use of microsimulation models. Inthat, observed individual values could be used instead ofgrossed or averaged ones, allowing the user to adapt themodel to the context it is being used for. IRENE (Gibson etal, 1989 as reviewed in Fernández, 2001 and PASSION [PAral-lel Stop SimulatION] (Fernández, 2001)) are both microsimu-lation models. The assumption in IRENE that buses arrive atrandom and that almost any bus that arrives satisfies thewaiting passenger seems reasonable when the bus system isderegulated or informal with many services sharing the sameroutes and high bus flows and passenger demands. However,there is no empirical evidence that this is the actual case, andmany not be true if services, frequencies, and demand arelower (Fernández, 2001). In addition, the assumption thatthe mean arrival rate of passengers remains constant duringthe simulation period might not be applicable when passen-ger arrivals are dependent on other services such as a railway.In a nutshell, IRENE applies well in situations with high andhomogeneous bus and passenger arrivals, but does not repre-sent passenger arrivals in detail.

To overcome this particular deficiency of IRENE, a differentapproach in modelling is required. Elaluf (1994) made someadvances on these lines. Her study recognised that theprocesses at a bus stop happen in parallel and hence it wouldbe reasonable to use a parallel computing technique to simu-late bus stop operations. Fernández (2001) furthered this ap-proach by developing a microsimulation program PASSION.PASSION addresses the deficiencies of IRENE, by having adedicated input section for passenger arrival data. Owing tothese merits PASSION was used for estimating bus station ca-pacities in this study.

ESTIMATION OF BUS STATION CAPACITY

The brief literature review of capacity estimation models in-dicates that these models are primarily used for bus stops.No model specifically refers to estimating capacity of a busstation. Prima facie, one can argue that bus station capacitycould be estimated by summing up the individual capacitiesof the bus stops/berths within the bus station. HCM 2000(TRB, 2000) mentions the use of discounted values as a multi-plier instead of the number of berths, ie instead of multiply-ing the capacity of a bus stop by three for a three-berth busstation, it suggests using 2.45 and 2.60 respectively for in-lineand off-line bus stops, to get the effective capacity. In otherwords, this multiplier represents the effective number ofberths. The author feels that there are issues that are differ-ent in bus stops and bus stations (briefly discussed in thenext section ) and hence the worthiness of this ‘natural ex-tension’ is an area warranting further research. However, inthis study PASSION was used for each of the three bus stopsand bus station capacity was derived by summation of the ca-pacities of the three bus stops in case of independent busstops and using discounting factors in case of interdependentbus stops (see Table 1).

IS ESTIMATING BUS STOP CAPACITY ANYDIFFERENT FROM ESTIMATING BUSSTATION CAPACITY?

Estimation of bus stop capacity uses dwell time and clearancetime. However, in case of bus stations, two aspects emerge asbeing different: [1] the additional time of manoeuvring thebus from bus station entry to bus berth and from bus berth tobus station exit, which could be termed at the internal run-



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ning time2 and [2] a component of the internal delay attrib-uted to jaywalking passengers (if any), which could betermed as additional internal delay. The latter might be par-ticularly high in case of an island type layout but could alsoexist in perimeter or concourse layouts if pedestrians areundisciplined or the design of the station is such that it en-courages jaywalking. Contrastingly, these two componentsin case of bus stops would be nonexistent or minimal (ifany). This discussion suggests two things: either bus stop ca-pacity estimation models need appropriate modifications inorder to consider these two components or a separate simula-tion model for estimating bus station capacity should be de-veloped.

CAPACITY OF BRIGHTON BUS STATION

The bus station capacities for existing and proposed situa-tions were estimated using PASSION. In that, separate inputfiles were created for each of the bus stops for both existingand proposed situations. A primary survey was conducted torecord bus arrivals and passenger alighting and boarding (foreach route) for a period of 90 minutes.

Existing situationBrighton station has three bus stops (see Figure 1). However,in practice, stop A and B act as one bus stop (stop A is merelya flag-poled stop, without shelter) and buses for stop A oftenstop at B if B is empty. In the 90-minute survey period onlythree buses were observed at stop A. Hence, for the existingsituation stops A and B were combined. The key outputs ofthe microsimulation runs, with a traffic signal at exit, areshown in Table 1. Table 2 shows the outputs with free-exitfor comparison. Please note that microsimulation runs withobstructed exit were also performed but are not presented inthis paper.

From the microsimulation outputs it is revealed that thesaturation for the existing situation is 33% (16% to 51%),which is much below the generally acceptable maximum de-sign value of 60% (Tyler, 2002), although queuing was ob-served on some occasions. Thus, adding new berths to thebus station was not necessary and hence the proposed de-signs consider only three bus berths.

Proposed situationThe congestion and queuing observed at Brighton Bus Sta-tion can be attributed to the following factors:

Factor 1 Internal delay (due to interdependency of berths)(ie, a bus from a stop cannot depart if a bus is parked at

preceding stop and a wrongly parked bus at the following

stop will delay a bus wishing to enter the preceding stop)

Factor 2 Internal delay (due to pedestrian jaywalking)Factor 3 External delay (due to hindrance from taxis

queuing at bus station exit)Factor 4 External delay (due to taxis and cars using bus

station area)Factor 5 External delay (due to traffic signal at exit)Factor 6 High passenger service time (probably attrib

uted to cultural factors, ie Brighton being slowpaced as against London which is a fast-paced city!)

Factor 7 Irregular bus arrival pattern

It can be appreciated that factors 1 to 4 can be manipu-lated easily, ie these are generally within the scope of a busstation design exercise. How these have been achievedthrough the proposed design is discussed later in the paper.Factors 5 to 7 could be changed, but would generally be partof a larger transport planning exercise, which would com-prise rerouting of buses, area-wide traffic management, andsignal redesign.

To address Factor 1 (above), which is of prime importance,

Table 1:Summary of

simulation runswith signal-at-exit

Table 2:Summary of

simulation runswith free-exit3

N

A

B

C

Figure 1: Existing layoutand bus stops

Table 1: Table 2:


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the three berths are construed as being independent of eachother in the proposals. The arithmetic sum of individualberths is the capacity of the bus station. The three berthscater to the same twelve routes that come to the station atpresent. However, some minor reallocation of routes wasdone based on their frequency and destinations.

Separate input files were created for simulation of the pro-posed situation using exactly the same bus arrivals, passengerarrivals, and route opted by each passenger as used in theinput files for simulation of existing situation (as summarisedin Tables 1 and 2).

As can be seen from Table 1, the capacity of the bus stationfor the proposed situation turns out to be 127 buses/h asagainst the existing capacity of 82 buses/h. The increase in ca-pacity can be attributed to making the berths independent (ie,the presence of a bus at any of the berths does not affect func-tioning of the other two berths). In addition, the reallocationof bus routes also helped in bringing the saturation level downto 23% (14% to 43%) as against the existing value of 33% (16%to 51%). Based on the analysis using PASSION, it could be saidthat because of the independence of berths, the overall delay,which was occurring in the existing situation, is eliminated inthe proposed situation. The possible physical layouts for theproposed situation are discussed in the next section.

THE DESIGN APPROACH

Conceptual bus station layoutsConceptually two different layouts could exist with referenceto the location of the bus station in the context of the accessroad. In the off-line layout, the road(s) that leads to the busstation abounds the station area. In other words, no part ofthe road space is used as bus berths. On the other hand, inthe in-line layout, part of the road leading to the bus stationitself is used as bus berths. Off-line and in-line layouts incontext of Brighton Bus Station can be explained by help ofthe schematic diagram in Figure 2.

Generally, most major bus stations would be off-line.However, in-line bus stations might have to be considered ifthe site is in a physically constricted area-a case commonwith inner-city bus stations. Brighton Bus Station is indeedsituated in the historic core of the city and hence it was nec-essary to explore the possibility of an in-line type layout.

Vehicle swept-path simulationAfter having decided the conceptual layout, a software usedby London Buses, Transport for London (TfL) called MISS(Mobil Interactive Swept-path Simulator) was employed. Ve-hicle parameters such as the outer dimensions, distance be-tween front and rear wheel axles, and steering sensitivity areinputs to the MISS. On the site area in the drawing, a path istraced along which one expects the bus to be driven. Usingthe ‘calculate path’ command, the swept path of the vehicleas it moves is simulated (see Drawing BO1.2 ).

The first step is to mark out tentative areas for the bus plat-form islands or the areas where bus should not run (based onthe design concept discussed above) before running the ‘elec-tronic bus’ on the bus station site in the drawing. Then vehi-cle swept paths are obtained. Bus platforms and channelisersare then formed such that they are clear off the bus sweptpaths. The bus platforms so formed are checked against theminimum standards of space required for wheelchair ma-noeuvre and for providing a shelter (if necessary). Thisprocess ideally has to be repeated until the optimum layout isobtained (ie, the one that minimises space requirements andmore importantly satisfies the horizontal gap between thebus and the platform of accessibility considerations of the

wheelchair users). However, owing to limitations on timeand resources, this process was carried out only once in thestudy. Thus further refinements to the proposed layouts arecertainly possible. As a special note it is worth mentioningthat currently the MISS software is programmed to simulatethe swept paths of the vehicle regardless of the external con-ditions such as the type of kerb. This means that if a Kasselkerb4 is put in place then the steering mechanism and themanoeuvrability of the bus changes, which currently is notreflected in MISS. Should such modifications be made to thissoftware then it could still become a more powerful tool fordesigning bus station layouts.

Drawings depicting the physical layout of the bus stationand how it has been achieved by use of swept-path simula-tion can be referred to in drawings labelled BO1.1, BO1.2,and BI3.1. Drawing showing swept-paths for achieving thelayout for BI3.1 are not included in this paper. In the evalua-tion methodology developed in this study for comparing theproposed design (not discussed in this paper), the proposalBO1 ranked the highest. There was not room to display all ofthe bus station layouts and the proposed taxi rank alterna-tives in this paper.

HOW THE PROPOSED LAYOUTS WOULDREDUCE CONGESTION AND QUEUING?

This section discusses how the above-discussed factors havebeen addressed in the proposed layouts.

Factor 1 Internal delay (due to interdependency ofberths)Dealt with by making the three berths independent. How-

ever, in case of in-line type layouts bus drivers’ error could

make it interdependent.

Factor 2 Internal delay (due to pedestrian jaywalking)Dealt with by making more area available to pedestrians

and by having designated pedestrian crossing points.

Factor 3 External delay (due to hindrance from taxisqueuing at bus station exit)Dealt with by having a higher ‘turnover’ rate for taxis

thereby reducing incidence of queuing and by having more

space for taxi set-down.

Factor 4 External delay (due to taxis and cars using busstation area)Dealt with by having a higher ‘turnover’ rate for taxis

thereby reducing incidence of queuing and by having a

physical layout that deters taxis and private cars from en-

tering the bus station area and stopping there (which is oc-

curring frequently in the existing situation).

Bus Station Area

N"In-line""Off-line"

Bus Station Area

N

Figure 2: The concept ofoff-line and in-line bus stationsin context ofBrighton



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SCOPE FOR FURTHER RESEARCH

The topic of bus station design has been little dealt with inthe literature. Most literature on the subject relating to ca-pacity estimation is on bus stops and does not explicitly referto a bus station. Thus, development of a microsimulationsoftware, for bus stations or the likely adaptation of a soft-ware like PASSION specifically for bus stations, needs to befurther researched. In addition, modifications to the swept-path simulation software that are sensitive to external condi-tions could make it a more powerful tool for enhancing thephysical layouts of bus stations. Lastly, further research ondevelopment of a framework or guidelines for evaluation ofbus station designs would certainly help the cause of bus sta-tion design.

CONCLUSIONS

This study tries to demonstrate that bus station design shouldand can be a more scientific process. Capacity and accessibilityconsiderations should be at the forefront. In other words, thelayout of the bus paths, bus berths, pedestrian infrastructure,kerb design, bus platform area, etc need not be purely drivenby architectural and urban design considerations.

In case of Brighton, the existing constraints, namely lack ofspace and not drastically disturbing the activity pattern in thearea, were the key considerations in developing the proposals.However, if such a project is undertaken the opportunities oflooking into a wider context should not be foregone. In otherwords, since Brighton Bus Station is located in the historic coreof the city, aspects such as decongesting the area and making itmore pedestrian friendly should be dovetailed with such pro-jects, if possible.

The author believes that local planning councils and trans-

port departments could adapt the framework developed in thisstudy to get a reasonably accurate assessment of the existingsituation of their bus stations. Such an assessment could thenbe used to formulate schematic alternatives for the purpose ofbudgeting and terms of reference for detailed design.

Footnotes1 Is based on an MSc Transport dissertation at Imperial CollegeLondon & UCL, under the supervision of Professor Nick Tyler, UCL.2 Coined by the author.3 The purpose of comparing signal-at-exit and free-exit conditions isto understand the impact of free-exit conditions on capacity andsaturation. From the simulation results, it can be seen that theindividual berth capacities and hence the bus station capacity andthe saturation level are markedly improved. Although, it is autopian idea to totally eliminate other traffic from the bus stationarea unless it is part of a major town center revitalization project,investment in bus-actuated signals could markedly improve thecapacity.4 A type of kerb that has been used in some areas of London andsome cities in the UK, which enables the bus to be aligned with thebus platform without any horizontal gap.

REFERENCES

Elaluf, Silva Monica (1994). Transputer-based microscopicsimulation of bus-stop operations. Unpublished MSc dissertation,University of London.Fernández, R E (2001). Modelling bus stop interactions.Unpublished PhD dissertation, University of London.Transportation Research Board (TRB) (2000). Highway capacitymanual 2000. Washington, DC: TRB.Tyler, Nick [ed] (2002). Accessibility and the bus system: fromconcepts to practice. London: Thomas Telford.

I would like toacknowledge theacademic inputs

from ProfessorNick Tyler, UCL;practical inputs,

base map andsupporting data

from LenHolloway,

Brighton & HoveCity Council; help

with MISS fromHugh Bailey and

Martin Edgar,Transport forLondon; andassistance in

primary surveysfrom Taku

Fujiama, UCL.


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These drawingswere producedwith softwareused by LondonBuses,Transportfor London (TfL),called MISS,(MobileInteractiveSwept-pathSimulator).


ADHVARYU [2006]_Design of Bus Station_A Case Study in Brighton_{TEC}

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