Some advances in model design developed for the practical assessment of road pricing in Hong Kong

Transpn.

Rex.-A

Vol.

2OA.

No.

2. pp.

135-143.

1986 0

Rmwd m Great Bntain.

SOME ADVANCES THE PRACTICAL

13.00+ hmdn

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IN MODEL DESIGN DEVELOPED FOR ASSESSMENT OF ROAD PRICING IN HONG KONG W.

The

0191-2607186 1986 Pcrgamon

J.

and C.

HARRISON

MVA Consultancy,

F%LL?

London WC2, England

P. M. JONES TransportStudies Unit, Oxford University, Oxford OX2 6NB, England and

H. ASHTON The MVA Consultancy, London WC2, England Abstract-The methods used in a study commissioned by the Hong Kong Government to assess the impacts of road pricing schemes in the territory are- outlined. Three aspects of the methodology are described in more detail. First, a programme of social research is outlined, which assisted in the understanding of the likely responses to road pricing and hence guided the tasks of assessment framework design, policy option identification and model design. Next, one area of model development is described, involving the use of stated preference survey techniques to estimate a work trip time adjustment model. The final area highlighted involved the development of speed/flow relationships based on an area network concept.

Section 2 sets out the practical constraints on model development imposed on the study and outlines the overall model structure that was developed. The next three sections describe some aspects of the work in more detail, covering the exploratory social research, the development of a time switching model and the application of an area speed flow approach to network-loading simulation. In the final section, the authors critically review the methodology that was used and propose a number of areas for future development. Given the size and complexity of the transportation planning work, it is only possible to describe some aspects of work that has been carried out over the past two years. The interested reader is referred to the final report covering this aspect of the study (MVA Consultancy, 1985) and the various technical documents referred to therein.

INTRODUCTION

The use of road pricing as a theoretical and practical means of traffic restraint and management has attrdcted . >.considerable interest since the pioneering work- of Thompson (1962), Smeed (1964) and Roth (1967). A review is found in The MVA Consultancy (1983). A form of electronic road pricing is generally considered to be the most flexible means of pricing road use and that which is best able to reflect the optimal theoretical charge. But technological problems have prevented such a scheme from being introduced in practice. The pilot electronic road pricing (ERP) project in Hong Kong represented the first demonstration of the practicability, and the first full assessment of the benefits, of an ERP scheme, compared with more traditional methods of restraint, such as annual road fund license or parking controls. [The background to the project is described in Dawson (1983) and Dawson and Catling (1986).] This paper outlines the methodology used in the transportation planning component of the pilot ERP project, to assess the likely impacts of a road-pricing scheme on travel behaviour and to provide an overall economic assessment of the costs and benefits of implementation. With the exception of the more limited Singapore arealicencing scheme (Holland and Watson, 1978) there is little practical evidence of how motorists would respond to road charges, so that considerable effort had to be put into developing appropriate techniques for modelling travellers’ responses to road pricing, using both “revealed” and “stated” preference approaches.

OVERALL MODEL STRUCTURE The were

main

objectives

to design

a range

of the transport of alternative

planning strategies

study for use

of the ERP technology in Hong Kong and to assess them in comparison with a minimum change option, car-ownership restraint and supplementary Iicencing. The study was restricted to considering the effect of charging private-car travel, although taxi travel was also considered at the same time, to ensure that the traffic system improvements from car restraint would not be neutralised. Public service vehicles and goods vehicles were not considered to be charged under the schemes being tested. The model design process had to meet four objectives: (i) forecast the overall transport patterns up to a design year of 1991 and to an initial year of 1987188, taking

tCument address: Deloitte Haskins & Sells, Management Consultants, P.O. Box 198, Hillgate House, 26 Old Bailey, London EC4M 7PL, England. 135

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W. J. HARRISONer al.

account of the impacts on travel of planned major changes in road and rail infrastructure since the base data date of 1981; (ii) predict the detailed responses of car users and a segment of taxi passengers to marginal changes in cost and level of service associated with different levels and patterns of ERP charge; (iii) assess the changes in level of service of the road network throughout the day, as experienced by road-based public transport, car, taxi and goods vehicles; (iv) provide sufficient data to perform an economic evaluation across different modes and times of day. In addition, the models had to retain comparability, where possible, with currently used transport models in Hong Kong, while time and budget constraints severely limited the possibilities for new survey work. The conceptual elements of the main model structure are shown in Fig. 1. Three principal model blocks are shown. One block, dubbed the “reference models,” comprises a four-stage transport planning model which is largely based on existing model specifications and calibrated using existing data at a zonal aggregate level. It was used to forecast the transport demands for the design years of 1987 and 1991, without the introduction of road pricing. The second block called the “impact models,” focusses entirely on changes in travel demand that would result from the introduction of a road pricing strategy. The third block, the network model, was used to assess the road network supply characteristics corresponding to the various demand patterns predicted by the other models. Four main data inputs to the modelling process are shown in Fig. 1: (i) existing data, principally a full census undertaken in 1981, and a major household interview survey (Travel Characteristics Survey, or TCS) of some 22,000 households carried out by the Hong Kong Government in the same year. The survey was a conventional one, recording the households’ motorised trips on the previous day; (ii) guidance from the social research programme; (iii) policy options, comprising socio-economic, demographic, public transport and taxi fares, fiscal measures relating to car taxes and other governmental influences; (iv) design options, comprising the alternative methods of implementing road pricing, covering a range of practical strategies for applying ERP.

The model results were incorporated into an evaluation process, including consumer surplus benefit measurement, and an appraisal framework additionally recognising criteria relating to practical feasibility. equity and political attractiveness. The trip-end model used trip rates for five purposes (home-based work, school and other, non-home-based and employers business) and two car ownership groups, segmented at the zonal level by ten area development codes. A household-level car-ownership model was developed using a logit formulation, and incorporating an accessibility dummy, the log of household income and the log of average car total running cost in the utility function. The car-cost parameter was necessary for interpreting later fiscal car-ownership restraint options. and was estimated using time-series data additionally available for 1982 and 1983. The model was applied by using the full TCS database after the forecasting of household and income growth. Distribution and mode split were undertaken for two time periods-an average morning peak hour and an average interpeak hour. The measure of generalised cost used in the distribution model was derived from the inclusive value of the logit mode-split model. Three modes were considered: highway (car and taxi), road-based public modes and rail [the Mass Transit Railway (MTR) and the electrified suburban KCR line]. Daily trips for home-based work and home-based school purposes were distributed using the peak period supply characteristics; other home-based, non-home-based and employers business daily trips were assumed to respond to the interpeak characteristics. Mode split was formulated as a hierarchical decision; public/private, with a subsequent road-based/rail split for public. This relatively conventional series of models were used to forecast daily trip demands for a 160 zone system by purpose, car ownership and mode, for input to the impact models. The impact models were developed using a marginal approach, predicting only the changes in travel demand resulting from road pricing. Drawing on existing data and the early social research, the modelling effort was con-

Fig. 1. The main model structure.

Advances in model design for assessing road pricing centrated on market segments expected to change behaviour, and on the most sensitive aspects of that behaviour . There are two groups of travellers that could be subject to ERP charges: private-car travellers and possibly taxi travellers. The majority of the first group come from carowning households. Taxi travellets come from both carowning and non-car-owning (NCO) households. A positive relationship was found between the income of NC0 households and the number of taxi trips made, such that 60% of NC0 taxi trips are made by members of the wealthiest 44% of NC0 households. For these reasons two market segments were defined for the model: members of car-owning households and members of highincome NC0 households. Low-income NC0 household taxi trips were assumed to be essential and hence inelastic with respect to price. In the social research, reported later, a number of likely short and medium term responses to road-pricing charges were identified; to change mode, time Period or route were reported to be the most likely responses. In the main model process, the assumption was made that the charge structure would not affect routeing and hence was ignored in the impact models. Thus the impact model concentrates upon changes in mode choice and time period resulting from the introduction of an ERP charge. Changes in behavior can be derived from the incremental logit model [see Kumar (1980)]. This relates the new probability of selecting a choice to the initial probability and the changes in the characteristics of the-choices; thus

p*(i) =

p*(i)

p(i) exp(dUi) 1 - p(i)[l

= new probability

- exp(dUr)]’

of choosing choice i,

p(i) = initial probability of choosing choice i, dUi = change in utility of choice i. The only changes in travel characteristics considered were the road-pricing charge and the reduction in travel time. (It was assumed that access and egress times and costs do not change.) The initial (without road pricing) probabilities p(i) were provided by the reference model. The changes in utility dUi were derived from estimated utility functions. The sensitivity of the response is determined completely by the utility function coefficients related to toll charges and in-vehicle time. The objective at model estimation is limited, therefore, to obtaining accurate estimates of the values of these two coefficients. The mode choice model used individual observations collected in TCS, supplemented by other data sources including: (i) telephone interview survey (used to estimate the availability of drivers licenses); (ii) network models (used to derive in vehicle time and cost); (iii) clerical coding (used to supplement access and egress times reported in TCS). With these data, nested or simultaneous logit mode-split models were estimated for

137

each trip purpose for both market segments. The models have robust and consistent values for the coefficients of toll costs and in-vehicle time. The impact models also included models for work-trip time adjustment (described later) and partial redistribution of a proportion of nonwork trips. The evaluation process recognises the benefits accruing to each of five separate groups of road user: car, taxi, road-based public, access legs to rail mode and goodsvehicle traffic. Three separate network assessment periods were used: peak, interpeak and freeflow. Changes in consumer surplus were calculated and summed for these 15 segments, reflecting the demand shifts between modes and times of day. SOCIAL

RESEARCH

Despite the well-established body of transport survey data available in Hong Kong to examine existing travel patterns, it was recognised that some additional investigations would be required to improve the understanding of responses to the potential effects of road pricing. On the demand side, there were a number of points which could not be clarified satisfactorily using existing data alone: (i) definition of market segments (to assist with reference and impact model segmentation); (ii) attitudes to travel and the role of the car in Hong Kong (as inputs to mode choice and car-ownership modelling); (iii) awareness and comprehension of ERP, both as a concept and in practical terms (to aid the generation of design options); (iv) likely responses to road pricing (to help focus the development of the impact models); (v) important variables not available in published data, but necessary to the analysis (e.g. characteristics of car-licence holders). Although the interviews were designed primarily to provide findings for the modelling and evaluation phases of the project, these were also of value in other aspects of the project, such as the design of information brochures and other publicity material. In order to meet these requirements, a two-phase survey strategy was adopted. An exploratory phase of social research was carried out in November/December 1983, in which approximately 70 Chinese and 20 expatriate car drivers took part in a series of group discussions and indepth household interviews; see Jones (198-I). This was followed by larger-scale quantitative telephone and home interview surveys in the spring of 1984. By phasing it, in this way it was possible to provide guidance at an early stage in the project on modelling issues such as segmentation and response strategies, and it gave the opportunity to add questions into the quantitative surveys in the light of insights gained during the exploratory stage. Rather than attempt to summarise the range of findings from the various surveys, we briefly describe the main responses to road pricing which were identified during interviews and some of the features of travel behaviour and attitudes in Hong Kong that affect these responses. Public transport provision in Hong Kong is betterand perceived to be better-than in most other cities (in terms of diversity, availability, etc.), and distances for

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most trips are short, so that for many owners a car is a convenience rather than a necessity. Thus the hardship of giving up a car would be less than in most other places, and social and individual attitudes towards the use of public transport were found to be relatively favourable, especially among Chinese drivers. Practical experience of public transport services among car users also appeared to be widespread, with most car drivers reported as using one or more of these modes either as an alternative (e.g. leave car at home) or as a supplement (e.g. park and complete journey by public transport) to car use on a regular basis. Indeed, TCS shows that about 40% of car-owning households do not use their vehicles on a typical weekday. Taxis were viewed as a satisfactory alternative to car for shorter journeys in the main urban centres, with bus or PLB (public light bus) being used for longer trips. The MTR was particularly highly regarded for its speed, reliability, comfort, etc. but did not provide a realistic option for many journeys because of its limited coverage. Parking difficulty was cited as a major restriction on car use by nearly all respondents. This appears to have restrained non-company-supported car commuting in some areas; it was also given as the reason for an increased use of chauffeur-driven cars by some companies. For urban leisure journeys, people reported parking short of their destination and completing their journey by another mode-but parking problems did not appear to be amajor influence on destination, except for journey to the-beaches or parks in the summer. Lack or cost of residential-parking was reported to be a restraint on car ownership in some areas. By comparison, congestion is regarded at the present as much less serious, more localised in its effects and generally getting better as a result of new road construction and the reduction in car ownership resulting from the recent fiscal measures. People reported taking alternative routes or adjusting journey timing to avoid congestion where possible, but it was not seen as a significant restraint on car use-though the MTR was used for some business cross-harbour journeys because it was faster and most reliable (i.e. subject to less journey time variability) than a car. Respondents did recognise, however, that in the longer term, congestion could become a very serious problem in Hong Kong. Asked what government should do to deal with traffic problems in Hong Kong, respondents argued for “positive” measures, such as more road building and better traffic management and traffic law enforcement. Again, in the long term, however, most people seemed to accept the need for some form of car restraint, albeit reluctantly. The interviews probed the likely effects on travel behaviour of a cordon-based ERP system with a four-level charging system (i.e. peak, interpeak, evening and night). Among car drivers who said they would modify their behaviour. the main response was to change mode of travel with the alternative ranging from taxi-to-bus, depending on circumstances. The only evidence for ERP increasing car use was where a reduction in congestion on the approaches to the harbour tunnel would make car

more competitive with MTR and result in a mode shift for some short-distance cross-harbour business trips. Other important responses were to modify the time of travel or change route; the latter was only possible for a few drivers with the charging scheme that was used in the interviews, but under other systems could be very important. As a consequence of these responses there might be some modifications to the pattern of travel (e.g. no longer make a detour to drop off another household member where this would involve crossing an additional cordon point) but these would be minor effects. Change of primary destination or the abandonment or generation of a trip were hardly ever mentioned by respondents and in the context of Hong Kong seem unlikely to be very important-unless evening or Sunday roadpricing charges were substantial-although in other metropolitan areas with a more dispersed urban structure or a less-attractive public transport system, there might well be significant responses. In broad terms, only IO-15% of motorists said that if they left their car at home it would be used by someone else during the same period; but around 50% claimed that if they decided not to use their car for a regular journey (e.g. because of the expense of road pricing) then they would get rid of that car. This may be an overreaction, but is a particularly significant response since it was not one of the options that was presented to respondents. Corroborative evidence supporting the realism of these responses comes both from other aspects of the surveys reported above (e.g. motorist willingness to consider public transport as an alternative, or lack of sensitivity of destination choice to car access) and from the monitoring of the Singapore scheme (Holland and Watson, 1978). The latter found that about two-thirds of motorists who altered their behaviour changed mode, and a third advanced their time of travel. An American study of motorists’ reported reactions to hypothetical toll increases in New York also found change mode and change time to be the main responses (Levinson, Regan and Lessieu, 1980), although the predominance of the former was less, as might be expected in a more car-originated society. From a modelling point of view, the surveys established that (i) mode choice, route choice and trip timing are the main responses to road pricing that need to be modelled in detail; (ii) trip generation, destination choice, journey restructuring and car reallocation are likely to be minor responses and can be handled in a more ad hoc way; (iii) there need to be clear and explicit links between car-use costs and the car-ownership model; (iv) company supported motoring is a sufficiently large factor to be considered explicitly in the segmentation, in some way. The surveys also identified several areas where policy initiatives will need to be coordinated and the role of road pricing seen in a wider context. As expected, the role of taxis within a road pricing system must be carefully detined. If these vehicles were not charged, there would be a substantial switch from car to taxi, but with an abundant supply of taxis there would be no net reduction in congestion levels. On the other hand, the taxi

Advances in

model design for assessing road pricing

market extends well beyond car owners, and a high charge might seriously affect this larger market. Another strong conclusion from the exploratory surveys was that parking difficulty is a much more effective deterrent to car use at present than congestion. The Hong Kong Government’s present policy is to relax this constraint in the territory (rather than increase the perceived difficulty and expense of parking, as was done in Singapore at the time the supplementary licence system was introduced), and this is likely to mean that road-pricing charges will need to be somewhat higher to achieve a given level of restraint than would otherwise have been the case. In general, it appears that motorists perceive the need for road pricing as a long-term rather than short-term solution to Hong Kong’s traffic problems, so that the government faces the problem of educating the public to take a long-term rather than a short-term view. WORK-TRIP

RETIMING MODEL

The choice of changing time period to reduce roadpricing charges could not be modelled from existing data, for no such choice presently exists in Hong Kong because there are no peak/off-peak pricing differentials. Thus it was necessary to ask travellers how they would behave in a variety of hypothetical situations, rather than observing how they behaved. These stated preferences describe behaviour in the same way that revealed preferences do, but they may require different interpretation. In revealed preference data, an equilibrium state is assumed; a reasonable assumption if the characteristics of the alternatives have been largely unchanged for some time prior to the survey. In contrast, when stated preference data are collected the choices observed are in response to hypothetical disturbances of the equilibrium state. Experience has shown that there is a tendency to overstate reaction. The expense of collecting quality stated preference data made it necessary to limit this form of analysis to a small number of the most important market segments. It was decided to concentrate data collection and quantitative modelling resources on the home-based work trips for car-owning households, because the low proportion of trips made by members of non-car-owning households that would be chargeable, and thus likely to be retied, precluded efficient surveying of this segment. Further, it was assumed that the timing of school trips is inelastic and thus no time-switching model was required for these trips. Two experiments were designed and in each one the respondents were asked to rank nine alternatives, in which trip timing and level of ERP charge varied. For those on fixed work hours, eight of the alternatives described extensions of the work day either in the morning or evening by different amounts in return for various savings in toll. For those on variable hours, the eight alternatives described options in which the whole working day was brought forward or retarded in return for a variety of toll savings. In both cases the ninth alternative was the ex-

139

isting trip timings at the full road-pricing charge. It was, of course, possible that a respondent would rather switch to public transport than either change timing or pay the road-pricing charge. To investigate this each respondent was asked to include the public transport alternative in the ranking. To ensure that the levels of charging and savings sounded reasonable to the respondents and encorporated their tradeoff region, the values were related to a transfer price question given earlier in the questionnaire, in which motorists were asked at what ERP price level they would switch from car to public transport. A priori it is to be expected that, because of activity rescheduling problems, disutility will be nonlinear in time. For example, a switch of 40 min will be more than twice the disutility of a 20-min switch. It is also to be expected that for two alternatives that involve the same retiming but different ERP savings, the one with the largest saving will be preferred. The survey data was checked for consistency in this respect, and any interviews which violated this order of ranking were discarded. These data were used to estimate discrete-choice models, that related the decision to change trip time to the time change and the ERP saving. By asking the respondent to rank nine alternatives, eight discrete choices are observed, the first from a set of nine, the second from a set of eight, and so on. However, as the majority of the information contained in the data is described in the fist few choices, and experience with this type of data has shown that the ranking of the less-favoured alternatives can be poor, and so only the top half of the ranking was considered. In addition, in this survey the introduction of the public transport alternative showed at which point timing changes/price levels combinations became unacceptable. The analysis of these data was limited to those alternatives ranked above the public transport option. The estimated multinominal logit models describing the choice to retime the trip or not, for those on fixed work hours, are given in Table 1. In each model, the utility function is a linear function of the saving and the square of the time change. Three segments are identified; low income, high income and high income with employer’s contribution. People in the last of these segments are provided typically with a car by the employer and thus are unlikely to have to pay any tolls themselves. The indifference curves that would be described by these estimated time and saving coefficients are shown in Fig. 2 and can be interpreted as showing the trade-off between time and cost at which 50% of car drivers in each segment would switch. A combination of saving and retiming that lies “inside the bowl” will attract more than 50%; one that lies “outside the bowl” will attract less than 50%. These indifference curves agree with intuitive expectation that low-income car drivers are willing to extend more time away from home for a given monetary saving than high-income earners. The number of respondents who work variable hours was small, and it was not possible to estimate models for which the coefficients were significantly different from zero.

W. J.

140

Variable

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HARRISON er al.

t ratio ---

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-0.000511

-2.652

0.071752

-3.693

2 Minutes

late

Employers saving

(HKS)

Fig. 2. Indifference curves for fixed work hours time-switching behaviour.

Advances

in model design for assessing road

The dashed line in Fig. 2 shows the value of time estimated in the revealed preference mode-split model for work trips by members of car-owning households. Although it is difftcult to make direct comparisons between the nonlinear relationships estimated for the three segments in the retiming model with the linear relationships estimated for a single segment in the mode-split model, it is clear that the trade-offs between time and cost derived from stated preference data for high-income respondents are similar to those derived from revealed preferences data. However, within the range of time switching considered in the experiments (60 min), lowincome respondents appear to be valuing time less highly in the stated preference data than in the revealed preference data. This implies that they overstate their sensitivity to ERP charges.

NETWORK-SUPPLY

MODELLING

The purpose of the work described in preceding sections was to determine the expected travel responses by those affected by a levied charge for using road space. This section describes the methods developed and used to estimate the network effects caused by those responses. The operational and economic benefits from road pricing are directly associated with the change in travel speed for all road users, and a reliable means of estimating this speed change was essential. The highway network in Hong Kong consists of a strategic system of four- or six-lane grade separated roads, linked to a dense urban and suburban road network. In the urban areas the junction density is high, and all but local road intersections have traffic signal control. Traffic flows are generally not peaky either by time of day or by direction, except at the edge of the urban area when a modest 57:43 peak hour directional split is observed. Within the urban area, traffic flows vary little during the working day as “peak” period commuting traffic gives way to “interpeak” business and commercial traffic, and in several districts speeds fall in the interpeak as kerbside activity increases. In this context the modelling of junction delay would be desirable but would require considerable detail in modelling and data collection which lay well beyond the scope of the project’s budget constraints. Instead it was necessary to work within the framework of traditional link-based capacity restraint, but it was proposed that this approach would be modified to incorporate area speed/ flow relationships. Besides enabling the more efficient and appropriate modelling of the interaction of junctions, and hence more accurate estimation of aggregate delays, this approach promised more stable results from iterative assignments. While such an approach involves a loss of precision in assigned link flows, this, in the context of area restraint (rather than a link-specific infrastructure study) is not a drawback. The urban highway network was subdivided into three groups of links: (i) strategic links, which are mainly grade separated; (ii) links within speed/flow areas, which were about 0.5-l .O sq km in extent; (iii) other links outside designated speed/flow areas.

pricing

141

The speed on links in groups (i) and (iii) were determined by link speed/flow relationships in which the limiting capacity of the link is related to carriageway width in the former groups and downstream junction characteristics in the latter. Within speed/flow areas, the speeds on individual links were set as observed, but capacity restraint acted on the area as a whole. Data collection and analysis was undertaken in two parts, firstly to enable link speed/flow curves to be estimated, and secondly to generalise these relationships for designated speed/flow areas. In the first stage the most appropriate model form for link-based speed/flow relationships was found to be as follows: V = Vo

for Q < QF,

and V=Vo-b:

for Q > QF,

where V is the overall speed (kph) on the link including any junction delay, Q is the flow (pculhr) on the link, Vo, b are calibration coefftcients. QF is the maximum flow (pculhr) at free flow speed, and C is the link capacity or downstream junction capacity. This link-based model was calibrated for four highway link types: (i) suburban-high speed, good alignment; (ii) suburban-lower speed due to poor alignment, frontage access and run-ins; (iii) urban-district distributors with at-grade intersections, high frontage activity, generally with high public transport flows; (iv) urban-local distributors with signalised and priority junctions, high kerbside activity and parking or loading. For speeds less than 5 kph, a tail was added to the curve in line with standard practice in the United Kingdom. The tail gave a calculated journey time increasing linearly with flow to represent queueing delays. The second stage of data collection and analysis was designed to investigate and develop area speed/flow relationships. In the development of these relationships, it was hypothesised that, within a range of approximately -C20% of existing traffic flows, the average speed in a particular area would depend only on the total level of traffic flow in that area and would be independent of traffic pattern and distribution by link. The relevant physical data, such as link length and width and junction characteristics, were surveyed together with link flows in the peaks and interpeak period. Four areas were chosen, in which journey time data were available for validation purposes. Area speed/flow relationships were calculated by aggregating journey time estimates for each area link obtained from the application of the link-based speed/flow curves. The proportion of area traffic flow attributable to each link was known from the survey, allowing the total vehicle time, and thus average speed, in the area to be calculated for different levels of area traffic. The resulting relationships for the three time periods are shown in Fig. 3 for one area. The relationships are very similar

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W. J.

HARRISONer al.

for all time periods, and this was consistent for all four areas, giving support to the initial hypothesis. The modelled journey time at observed traffic levels was within 4 kph (20%) of the observed average speed, which is sufficiently accurate for the purposes of assessing the impact of a change in vehicle flow in an area. Prediction of the absolute speed in an area was not crucial, as it was the differences in travel times between ERP options which entered the evaluation. When the area relationships were expressed in terms of pcu-km/lane-km they showed different characteristics between areas. This is shown in Fig. 4. This process was extended to apply to a total of 10 areas of highway network. A simpler set of data was required for implementation. It included link length and junction characteristics (to calculate link capacity) and a sample of the interpeak flow. The knowledge of the traffic flow was required both to enable the link journey time to be calculated and to provide an estimate of total pcukm. This was used as a check on the values produced by the model which had to be scaled up in three areas where the modelled network did not include all trafficable roads. The accuracy of the area speed/flow relationship in predictive mode was tested in one area by comparing its prediction with the results from a TRANSYT program run in which the traffic pattern was held constant. TRANSYT is a program for the detailed analysis of junction delays in fixed time-linked signal systems (see Vincent er al., 1980). This gave results which indicated that speed changes would be more sensitive to flow changes than had been predicted. This was partly due to the dominance of one or two critical junctions in the TRANSYT network where no rerouting was allowed, and therefore made the TRANSYT results oversensitive.

-

It was concluded that the area speed/flow relationships satisfactorily represented the likely change in network performance and, if anything, underestimated the time savings and thus benefits that would be attributable to a road-pricing strategy. The network-supply model was used to estimate invehicle journey times for three time periods-morning peak, interpeak and freeflow. Time changes in the first two periods were estimated after demands had been modified by road-pricing charges, and these time changes formed one of the key inputs to the evaluation process.

CONCLUSIONS The conclusions presented here are of necessity partial; large sections of this integrated study have been only briefly introduced and cannot be cited in supporting conclusions. At a genera1 study design level, however, two conclusions can be drawn. Firstly, the usefulness of exploratory social research was fully proven for broadening understanding of travel demand responses. This usefulness extended beyond guidance as to model specification into the generation of design options: the evaluation process and the presentation of results. Qualitative social research was confirmed as a valuable means of exploring issues and uncovering unexpected insights, but was shown to sometimes exaggerate the importance of certain conditions or responses. Secondly, the specialisation of the model components into the conventional “reference models,” the marginal “impact models” and the network model proved both practical and efficient. At a more detailed modelling level, the development and application of an area-based concept

a.m.peak

-.-

O,,.pesk

-

p.m peak

Fig. 3. Area speed/flow curves-Wanchai.

Advances in model design for assessing road pricing

143

?.Deed(hph)

Fig. 4. Normalised area speed/flow curves.

of speed/flow was most successful and performed satisfactorie . The study also sought to improve the application of stated preference techniques through the offering of responses in addition to the main tradeoffs and the tailoring of cost levels using the respondents’ transfer price; but the results still appear to be oversensitive, and this problem requires further investigation. Acknowledgements-The

work described here formed part of a large team effort: Particular thanks are due to John Spiers, John Miller and Sarah Shutt. AGB MacNair (Hong Kong) assisted in the social research fieldwork, and the Traffic and Transport Survey Division, Transport Department of Hong Kong, assisted in the speed flow surveys. The paper stems from a study commissioned by Transpotech Ltd., Consultants to the Hong Kong Government.

REFERENCES Dawson J. A. L. (1983) Electronic road pricing in Hong Kong, the pilot stage. Tr@Ic Eng. Control 24, 272-274. Dawson J. A. L. and Catling 1. (1986) Electronic road pricing in Hong Kong. Transpn. Res. 20.

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