微观仿真在城市停车设施规划中的应用（中英文对照）外文文献翻译中文资料.doc

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1、外文资料原文Planning urban car park provision using MicrosimulationThe provision of available car parking is one of the most contentious issues for city drivers. Car park spaces can be hard to find and expensive to use. There may be queues to get into the most convenient car parks which require drivers to

2、 move on to alternative car parks. Some city centre traders regard the lack of suitable car parking as a significant reason for shoppers to prefer out of town shopping centres. In New Haven Connecticut, Gov. Rowland at a ceremony celebrating the renovation of the citys largest car park in 2002 decla

3、red: if you dont have parking, nothing else works.Car park hunting, the circulation of drivers looking for a parking space, can be a major contribution to city centre congestion. The proportion of cars searching for a space was found to be 26% when surveyed in Manhattan in 2006, while in Brooklyn it

4、 was 45%. The situation is not new. In 1927, a similar survey in Detroit found the figures to be 19% and 34% in separate locations. This long standing problem may at last be assisted by technology. While iPhone users can now notify each other as spaces become available, traffic planners can now take

5、 advantage of recent developments in traffic modelling, which demonstrate that car park access can be included in road traffic simulation models to support the design process.Car park location in urban planning policy is largely concerned with optimising the relationship between car parks, drivers a

6、nd their destinations. Charging regimes may be used to reduce localised inconvenience caused by parked cars and to favour one class of driver over another in allocating spaces. The perceived benefits include improvements to a citys commercial centre through better accessibility for the target consum

7、er. Policies may be supply- led by actively managing spaces or demand-led by simply increasing the number of spaces. Increasingly, active management policies are used to ration spaces and encourage sustainable travel patterns.Accessibility of car parks is addressed in road design guidelines. UK Depa

8、rtment for Transport advice on parking guidance and information systems includes reports of case studies that show that there are quantifiable benefits to be derived from installing variable message signs indicating car parking space availabilty. Benefits are described as quantitative, in terms of t

9、ime saved, and qualitative in terms of public image and driver safety. WebTAG guidance touches on the subject briefly in discussion of travel costs by including parking “costs”(which notionally include time spent searching and queuing for a space and walking to the final destination). A study in Nie

10、uwegein (The Netherlands) modelled a large expansion in travel demand and the provision of car park spaces for a major town centre redevelopment, where Saturday afternoon shopping was the critical period. It incorporated ITS within the microsimulation model to deliver information to drivers on avail

11、ability of spaces and routes to car parks. Another study, in Rochdale (England), models the distribution of spaces in conjunction with major town centre development plans. The goal is to optimise the provision of car parks with respect to adjacent land use and to minimise town centre congestion by c

12、onsidering car park access early in the design process. The third study, in Takapuna (New Zealand), is also investigating the effect of city centre expansion. It uses bespoke software to model the car park demand and a microsimulation model to assign the demand to the network. Once again the goal is

13、 to understand the effect of car park policy and minimise city centre congestion.CAR PARK MODELLING IN MICROSIMULATIONTypical design option tests for a microsimulation model include changes to road layout, public transport priority schemes, optimisation of signals, or changes in demand. Each individ

14、ual vehicle in the simulation will react to these changes, and the congestion they cause, as it moves to its destination. ArrivalsCar parks are an entity within the microsimulation model, and are linked to zone destinations and car parks may serve more than one zone. Allocation of vehicles to car pa

15、rks is undertaken by limiting car park access to specific trip purposes. If a car park is full then vehicle drivers within the simulation wait at the entrance for a predetermined time, after which they re-assess their choice of car park and possibly proceed to another. Using an external software con

16、troller it is possible to monitor car park occupancy within the simulation and change a vehicles destination before it reaches the queue.As an example of how this methodology can be used to implement a car park policy model, consider a city centre zone with a mix of retail and commercial use with se

17、veral car parks available within reasonable walking distance. Drivers will have a preferred location based on their proposed length of stay and the car park charging structure.Some drivers may have a contract for permit parking. A car park may have multiple adjacent entrances, each coded with a rest

18、riction to force vehicles to accept the appropriate parking charge. The effect in the simulation is that short stay vehicles enter car parks closer to their destination or with a lower charge. The long stay vehicles enter via the entry links with the higher charges or accept a longer walk time. The

19、modeller can test responses to car parking changes by adjusting entry charges for different car parks or by varying the level of permit parking. Land use changes may be modelled by adjusting the proportion of driver and vehicle types using a particular zone and related car parks.DeparturesThe assign

20、ment of all vehicles to an S-Paramics road network is controlled by a detailed (5 minute) time release profile. In its simplest form of use, the journey origin car park is determined by finding the minimum journey cost,which includes the walk time, or vehicles may simply be released in proportion to

21、 the size of the car park.MODELLING SOLUTIONSData collectionTravel demand matrices for the Nieuwegein model were derived from a pre-existing macroscopic model and refined with survey data. Further surveys were undertaken to determine the usage of the main car parks, the average length of stay and th

22、e residual numbers after the shops were closed.Because of the complex requirements of the Rochdale and Takapuna studies, more extensive data collection was necessary. Demand matrices for Rochdale were developed primarily from roadside interview data which identified the true destination of the journ

23、ey. The interview data was used to determine the parking type (eg long/short stay, on/off street, contract), and the likely parking duration (based on journey purpose).A full parking inventory of the town centre and occupancy data provided input to a car park location model, used to link car parks t

24、o destination zones. The time to walk to each destination from each car park was initially estimated from simple geometry and later used as an important calibration parameter.Parking inventory data was essential to provide accurate capacity estimates categorised by: short or long stay, on or off-str

25、eet; public or private, and charged or free. This included all car parks within, or adjacent to, the town centre. Residential parking areas adjacent to the town centre, were also included as these provided free parking, with longer walk distances, and were often used by commuters. Areas with high dr

26、op-off trips were modelled as a private parking type at their destination but could have been improved by having both the inbound and outbound legs of the drop-off trip in the matrix.The car park data also provided charging information for each car park. When combined with the car park interview dat

27、a it was found to be possible to group charges into a single short stay and long stay charge. This simplification was appropriate in Rochdale, but it would have been possible to use a car park specific charge if the variation was more significant. Demand matrix segmentationMatrix segmentation enable

28、s the modeller to control departure time demands for different classes of vehicles. The degree of segmentation must be supported by the data. Similarly car parks should be grouped to a level commensurate with the detail of model input data.In Rochdale, matrices were derived for cars categorized by c

29、ommuter, non-commuter and work. The interview data enabled the commuter and work matrices to be subdivided into private non residential (PNR) parking and contract parking. PNR parking supply, which is is notoriously difficult to estimate, was assumed to be unlimited in the model as the matrixes were

30、 explicity defined. For areas outside the town centre all drivers were assumed to park at their destinations.Takapuna adopted a similar approach, with demands segmented into long stay and short stay parking types.Long stay was further split into on site or general depending on access to workplace ca

31、r parking. Long and short stay demands were estimated from the purpose matrices of a strategic transport model, with adjustments based on car park number plate and turn count data. Car park searchingAs the primary goal of all three models was to study theimpact of car parking on urban traffic conges

32、tion, the strategies for allocating vehicles to car parks within the model and subsequent car park hunting were key to the success of the studies.The Nieuwegein study was specifically designed to test the effect of a proposed car park advisory system. VMS signs were positioned on all approaches to t

33、he town centre (Fig 2) and provided information on which car park to select (Fig 3). Based on the experience of the Town Parking Manager, the ITS system was configured to make only 20% of drivers follow the advice of the parking advisory system. This left the remaining 80% to proceed to their first

34、choice car park, and re-route from there if itwas full.The Rochdale and Takapuna models focussed on accessibility more than guidance. In Rochdale, policy decisions were used to determine car park choice, which restricted the allocation of car parks to zones, eg contract parking areas were linked to

35、work-related, rather than shopping-related zones. In Takapuna, parking was less constrained by policy and all car parks were linked to all zones with less predetermined allocation of spaces.Vehicles arriving at a car park would queue for a fixed time then move on to the next best car park based on t

36、he vehicle trip cost, walk cost, and parking cost. The Takapuna model augmented this selection process with a car park availability control and a search limit implemented through an external software controller. The search limit reflects drivers willingness to circulate through numerous car parks in

37、 order to find a parking space, by setting a limit on the number to be tried before giving up, and looking for something highly likely to have spaces. The availability control monitors car park occupancy any car parks that have been full for 10 minutes are removed from the list. As soon as a vehicle

38、 leaves a car park, it is reintroduced into the selection procedure.First choice car parkThe first choice car park issue arose in both Rochdale and Takapuna. This occurred when the first choice car park for a vehicle was small and quickly filled. Most vehicles that selected this car park to minimise

39、 journey costs would have to re-route to their second choice. In reality many drivers make the same trip regularly and learn that this car park is usually full. They discount it as a first choice and select a larger car park with a better chance of finding a space.Two solutions were developed to add

40、ress this problem.Takapuna used their car park availability controller to overwrite the drivers choice, to provide a proxy for the driver learning process. The second solution was to group smaller car parks, typically those with less than 50 spaces, to avoid excessively large demand being allocated

41、to a specific car park as first choice. Car park destination catchments and walking times were adjusted in parallel to prevent too many vehicles having the same first choice car park.A high level of matrix segmentation is in use for Rochdale to allocate car parks. This methodology offers a solution

42、through further segmentation by driver familiarity. Drivers with knowledge that the smaller car parks are full tend to avoid them and make their first choice the larger car parks.THE MODELS IN OPERATIONNieuwegeinThe base model was calibrated for a typical Saturday afternoon.The test scenarios includ

43、ed planned new developmentsin the city centre.Two future year simulations were compared. In thefirst, without the advisory system, large queues formed at the most attractive car parks. With the parking advisory system, the vehicles were more equally distributed over the available parking capacity wi

44、th spaces available in most car parks. This resulted in fewer vehicles searching for a parking spot and fewer queues in the city centre. This was achieved with just 20% of drivers taking heed of the parking advisory system. Future tests will extend the range of the ITS system and redesignate some ro

45、ads as pedestrian areas.As the model simulated a future year scenario of 2015 and the detailed design of the town centre will probably differ from that which has been simulated, the predicted benefits were conservatively interpreted in evaluating the scheme. Despite that, the conclusion was that an

46、investment in a parking advisory system to make the best use of the parking capacity in Nieuwegein is justifiable.RochdaleThe Rochdale model has been used to test part of a major town centre redevelopment planned for 2012. Key features include relocating the town centre bus station and council offic

47、es, removing the main town centre multi-storey car park, and redesigning key junctions on the A58 through the town centre. Further developments in the modelling process may include a similar external software controller as implemented in Takapuna and Nieuwegein. This could include explicit car park

48、guidance at route decision points as well as a car park space opportunity cost which would be added to the generalised cost associated with each car park before the first choice is allocated. This cost would bring the likelihood of space availability at each car park in to the destination choice alt

49、hough more survey data would be required to help calibrate this.TakapunaThe S-Paramics model for Takapuna is to be the operational transport assessment tool for all significant planning applications and district plan change proposals within central Takapuna. In this way, all assessments will be made under a common and consistent modeling framework as has previously been successfully achieved in two other developing areas of North Shore City.With the recent economic downturn,