MODELLING PARKING CHOICES IN IRELAND S CITIES

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1 Proceedings 1st - 2nd September 2016 SIDDLE, COLLEARY: Modelling Parking Choices in Ireland s cities Mr David Siddle Technical Director Jacobs MODELLING PARKING CHOICES IN IRELAND S CITIES Mr Barry Colleary Head of Transport Modelling National Transport Authority Abstract The National Transport Authority (NTA) has developed a Regional Modelling System (RMS) for Ireland that allows for the appraisal of a wide range of potential future transport and land use options. The regional models are focussed on the travel-to-work areas of major population centres (e.g. Dublin, Cork, Galway, Limerick, and Waterford). Within the urban areas, the availability and cost of parking are big factors in the decisions that people make regarding their mode of travel and choice of destination. Within the RMS, there has therefore been a focus on parking choices to ensure that they are represented accurately. The RMS incorporates several innovative parking models including representation of free workplace parking, park-and-ride, parking distribution (remote parking) and parking constraint. This paper provides some details about how each se sub-models work and there interaction with the rest RMS. Background The NTA has a number of roles and responsibilities which include the development and implementation of transport strategies and policy in the Greater Dublin Area (GDA) and other regional cities. To assist in the development se strategies, the NTA has commissioned the creation of five new regional models covering each major urban areas. These models replace the NTA s existing model which only covered the GDA. The new models are a significant advancement on the previous models as improvements in computing power have allowed for greater segmentation and enhanced functionality. One key areas for improvement has been the representation of parking as this is regarded as one most important factors affecting mode and destination choice within urban areas. In the previous GDA model (as in many other models), the effect of parking restriction on car trips with destinations in the city centre was represented simply by a time penalty prior to the mode choice stage. This functionality provides a basic ability to model the impact cost and availability of parking on mode choice, but also has a number of weaknesses, including: Charges do not vary by arrival time or duration of parking, or the availability of free workplace parking spaces; Parking capacity or parking turnover rates are not modelled; and, There is no modelling of parking location choice. The previous model also included some basic representation of park and ride trips, but there were also a number of weaknesses with the methodology employed, including no modelling of informal park and ride, and no choice between alternative sites. Based on the identified weaknesses, it was agreed that enhancement parking submodels would significantly increase the accuracy and robustness overall model. Model structure The parking model forms part overall demand model structure, feeding into the process at several stages. Figure 1 below gives an overview model structure and how the different elements parking model fit within that structure. The internal workings three main parking model components are described in more detail in their respective sections below.

2 SIDDLE, COLLEARY: Modelling Parking Choices in Ireland s cities 1 st - 2 nd September 2016 Proceedings Figure 1: Location of parking modules within the demand model structure Parking charges The parking charges applied to each zone in the model are difficult to determine accurately, as there are a number of factors to consider such as parking location (on- or off-street), cost per hour and parking duration which will differ for each individual trip. One main varying factors is free workplace parking which is provided to some employees. Since the behaviour of free-parkers will be significantly different from those that pay, a separate mechanism is provided to separate out the free and paid parking trips and this is discussed in more detail later in this paper. Parking charges are therefore considered to only apply to those trips for which free parking is not available.

3 Proceedings 1st - 2nd September 2016 SIDDLE, COLLEARY: Modelling Parking Choices in Ireland s cities Parking Capacity The number of available spaces in each zone is an important input to the model and is used by the Parking Constraint and Distribution Model to ensure that the number of trips to any one particular zone does not exceed the number of spaces. This is particularly important where there are large attractors such as the city centre where parking will be spread over a number of adjacent zones. Determining the number of parking spaces in each zone can often be challenging. Fortunately some councils were able to provide detailed and comprehensive information on the location of parking meters and the number of associated spaces. By allocating the parking meters to the zone in which they are located it is possible to calculate the total number of on-street spaces in each zone. This method is not entirely accurate as some spaces associated with a particular meter may be located in a different zone than the meter itself. Nevertheless this error will be small and the resulting distribution of spaces will be sufficiently accurate for our purposes. Unfortunately, the same information was not available for most council areas, although this shouldn t cause too many problems for the model since the extent of parking controls (and therefore parking constraint) is relatively limited in these areas. Nevertheless, some reasonably accurate estimate of parking spaces is required for every zone in the model. To solve this issue we have used GIS to determine the total road length (in metres) for each zone, doubled this number (to account for parking on both sides road), and then divided the result by five (to account for the average length of a parking bay) to give the total parking capacity zone. Since parking will not be appropriate on some sections of road, this number has to be factored down to account for these areas, and the adjustment factor is calculated using data from suburban parts Dublin Council area, where the exact number of spaces is known. The result should be a reasonable estimate parking capacity in each model zone. As a check, the number of spaces in each zone has been divided by the zone area to give an indication of parking density. An example of a parking density map (covering Dublin) is provided in Figure 2 below. As can be expected the figure shows that the areas of greatest density are in and around the city centre. Figure 2: Parking density in Dublin

4 SIDDLE, COLLEARY: Modelling Parking Choices in Ireland s cities 1 st - 2 nd September 2016 Proceedings The parking capacity of each zone is not used as a hard limit on the number of vehicles able to park in that particular zone. This type of constraint should be avoided as it could result in a significant number of trips being moved to another mode or destination, thereby distorting economic outputs without the modeller s knowledge. Instead the parking constraint and distribution mechanisms described later in the paper can be used to increase costs in high demand zones to discourage trips to that zone. Free Workplace Parking A key characteristic feature of many urban areas is the large number of people who have a free parking space available to them at their place of work. This also applies to some education trips and so affects both purposes. In this paper, any references to free workplace parking (and the mechanisms used to deal with this issue) should also be considered to apply to free educational student parking. Although free parking may be offered to some people, they may still choose to travel by a different mode. There is an assumption that, in this event, the space (which has considerable value) would be offered to someone else. The proportion demand matrix offered a free parking space should therefore be increased in each model run, such that the number of trips with free parking equals the number of spaces available, wherever possible. In some scenarios where the Public Transport network is improved significantly or where the cost of parking or driving increases, a situation may develop whereby the proportion of people offered a free spaces is increased to 100%, but the number of people choosing to drive is less than the number of spaces. For this reason, the number of free spaces can be considered to be an upper limit (i.e. the number of car trips with free parking should never be more than the number of available spaces, but can be less). Furthermore, it is assumed that the number of free spaces in each destination zone will not increase in future years, but may be decreased due to policies in future. The workplace parking mechanism would operate by applying the mode choice function to all trips assuming that parking is free for all. This gives the percentage of trips for each OD pair who would choose to drive (out of those with access to free parking), and also gives the total number of potential free-parkers for each destination zone. On the basis se numbers it is possible to work out how many people for each OD pair (and regardless of final mode) would be needed to achieve the correct number of parkers once the mode split is applied. This is done by comparing the total number of car trips by the number of spaces in each destination zone. The result of this process is to effectively strip out those people with access to free workplace parking from the total demand matrix and store these as separate free car and PT matrices. The remaining trips are then subject to mode choice with parking charges applied as normal. The PT matrices from both mode split functions are then recombined, whereas the free and paid car matrices are stored separately so that the latter matrix can be subject to the parking constraint process. The free parking mechanism is shown illustrated in Figures 3 and 4 below. One additional complication not illustrated in the diagrams below involves the use of composite costs by the destination choice module. Composite costs would usually be derived using a variation mode choice function and using the same coefficients. However, since the mode choice is done separately for free and paid parking, the costs used by the destination choice module must be a weighted average free composite costs and the paid composite costs. To calculate the weighted average, the ratio of free and paid parkers would be required but is unknown at that point in the calculation. The ratio from the previous iteration demand model must therefore be used, potentially introducing a small error into the process.

5 Proceedings 1st - 2nd September 2016 SIDDLE, COLLEARY: Modelling Parking Choices in Ireland s cities Figure 3: Free Workplace Parking Mechanism

6 SIDDLE, COLLEARY: Modelling Parking Choices in Ireland s cities 1 st - 2 nd September 2016 Proceedings Figure 4: Adjustment free parking proportion As the free workplace and educational parking is specific to each destination zone, the above methodology only works if destination choice is applied before mode choice (in other words, each individual must choose where they work before they can know if they have free workplace parking or not). If mode choice occurs before destination choice then there may be difficulty in applying the methodology. It is felt as though this is unlikely as destination choice nearly always occurs first for work and education trips. Although unlikely, an alternative method has been devised in the event that calibration demand model requires that mode choice occurs before destination choice. In the alternative methodology, the mode choice function is applied first based on the composite cost of travelling by each mode. In the case of car, this composite cost will need to be an average of two functions: one based on free parking and the other assuming paid parking. As with the main methodology above, the issue here is that the ratio between free and paid parking is unknown at this stage process. Following mode choice, the other modes are subject to destination choice as normal. However, car trips would undergo destination choice assuming free parking is available to all users. Following this step, and similarly to the main method, the number of free parkers would then be capped, with the remaining car trip undergoing a second destination choice calculation which assumes paid parking.

7 Proceedings 1st - 2nd September 2016 SIDDLE, COLLEARY: Modelling Parking Choices in Ireland s cities As discussed above, because the number of free parking spaces is assumed to be an upper limit, it is possible for the number of free parking trips to be less than the number of available spaces if charges are applied to the individual trip-maker. Examples of this may include tolls, or other increases in travel costs such as fuel prices. The inclusion se additional costs may, in some extreme cases, be sufficiently high to discourage commuters from using their car even if free parking is made available to all. However, it is important to note that the free parking mechanism cannot predict changes in the availability of spaces as a result of costs applied at an establishment level. For example, the model cannot predict how businesses would react to the application of additional tax levied against workplace parking. In this case, it is up to the modeller to decide (possibly using an external process) how such a change would impact on the number of free spaces available, and adjust this number manually within the model. There are two sources of data regarding the number of free workplace parking trips. The first is the travel diaries collected as part National Household Travel Survey (NHTS). This describes the trips made by each respondent, the mode by which they got there and (for car trips only) whether or not a free parking space was available. The second data source is the valuation survey undertaken by the Valuations Office. As city centre parking spaces are rateable, there is detailed information on the number of spaces owned by each business premise. However, the data outside the central Dublin is not as detailed which can be evidenced by comparing the surveyed number of spaces against Google Street View images. A comparison has been undertaken on the number of free workplace parking spaces available according to each available data sources. Since the valuation survey is unreliable outside of central Dublin, this comparison is limited to the area encompassed by the canals. This has been done for the NHTS dataset by isolating only those trips with a destination within the canals, which were made by car and which had a free space available and comparing this to the total number of trips with destinations within the canals. This gives an estimate proportion of trips with access to free parking. For education trips this estimate is based on those pupils/students who drove themselves and who had access to free parking, as a proportion of all education trips by car. The total number of work and education trips with city centre destinations can then be determined by interrogating the census journey-to-work and education data (POWSCAR) which provides information on the number of such trips made to each destination. Applying the proportion of trips with free parking from NHTS to the total number of trips from POWSCAR by purpose provides a reasonable estimate total number of free spaces within the canals. This results in an estimate of 44,143 spaces, which is almost double the 26,941 spaces recorded in the valuation survey. There are several potential reasons for this: There is an inherent overestimation of total trips in the POWSCAR data, since not everyone in the survey would necessarily travel to work every day. Furthermore, they may have not have exclusive use free workplace parking space; Within the HSTD data, there may be more than one person travelling in the same car, meaning that several spaces are recorded even though just one is required; People who work close to the canals may choose to park in a free space outside of the canals area; The valuation survey may not be accurate and may underestimate the number of spaces. Given that the POWSCAR and NHTS data will provide the basis home-based work and education trips, it seemed appropriate to start with the number of spaces derived from this data. A factor has been applied to reduce the number of free workplace parking spaces to the correct level. This factor is determined by comparing the number of car trips in POWSCAR with destinations inside the canals area against the number of cars observed crossing the canal cordon (with adjustments for other trip purposes). This factor has then been applied to all zones.

8 SIDDLE, COLLEARY: Modelling Parking Choices in Ireland s cities 1 st - 2 nd September 2016 Proceedings Park and Ride The Park & Ride mechanism offers an alternative mode to either driving for the whole trip, or using Public Transport for the whole trip. The Park & Ride mode is considered to be a choice in itself and forms one main choices in the mode choice model; although the costs used for this are generated by combining costs from the other modes, and trips generated need to be split into their component parts. Because of this limitation, Park & Ride is only available at clearly defined points, which could either be formal Park & Ride sites, or informal sites such as on-street parking around stations or close to busy bus routes. Park & Ride applies to all two-way home-based trip purposes, but does not apply to one-way trips. One-way trips are excluded to ensure that mode choice can be applied consistently throughout the day. If one-way trips were to be included in the Park & Ride model, higher costs in one period could result in different numbers of trips using the Park & Ride site in each direction. This leads to the impossible situation whereby cars are driven to a Park & Ride site, but not removed (or vice versa). The exclusion of one-way trips from the Park & Ride model also results in the exclusion of all non-home-based trips (since these are all, by definition, one-way trips). While in practice these trips occur as part of longer trip chains which eventually include home based legs, almost all intermediate non-home-based trips will either made exclusively by car or by public transport. The Park & Ride model actually consists of two separate components. The first se calculates the Park & Ride cost by combining costs from the car and PT assignment models. The cost of Park & Ride is given by: the cost car leg between the site and the home location (in both directions); the cost public transport trip between the site and the destination location (in both directions); the fixed cost of interchanging at the site (walk and wait times); parking charges; and, any search cost at the site introduced by the Parking Constraint function. The second model component takes the Park & Ride demand matrices output from the mode choice model and splits this into the constituent car and PT legs. This generates two trips for each park and ride trip: A two-way car trip between zone containing the P&R site and the home zone; and, A two-way PT trip between the zone containing the P&R site and the non-home end of the trip. The original two-way trip between the home and non-home zones is removed. For each Park & Ride site, it is important to define an origin and destination catchment which will limit the number of trips which can use each site. In other words, a particular Park & Ride site will only be available as a choice to trips which start in the origin catchment and end in the destination catchment of that particular site. This is to prevent the model from having to undertake unnecessary calculations for choices which are unviable, thereby increasing model runtime. The catchments for each site therefore need to be carefully defined in such a way that it captures all potential trips which may use the site, without then creating excessive choice between different sites. Catchments were originally defined automatically by allowing the Park & Ride module to model trips between each Origin and Destination to use any Park & Ride site. Any movement which exceeded a pre-defined threshold would then be included in the catchment for that Park & Ride site, while all other movements will be barred. Unfortunately, this process resulted in a number of implausible movements whilst barring a large number of apparently logical movements. The catchments were subsequently adjusted manually, but it is our intention to improve the automated process in future. The catchments were further

9 Proceedings 1st - 2nd September 2016 SIDDLE, COLLEARY: Modelling Parking Choices in Ireland s cities adjusted so that every home zone has at least one park-and-ride option (but not to every destination zone). Park & Ride sites are not, as a general rule, be modelled as separate zones and are assigned to the zones in which they are geographically located, along with other land-uses. This can cause problems at large sites where access to the P&R site is significantly quicker than to the zone which contains the site: Red Cow is the most obvious example of this as it is located just off a major intersection. In these cases, negative interchange costs have to be applied to account for the difference between the zone access costs and the equivalent (lower) costs for the Park & Ride access. Where a particular trip has a choice of two or more P&R sites, it is subject to a further P&R choice mechanism (similar to the destination/mode choice mechanisms). This choice function calculates the proportion of trips using each P&R site. As a result of this additional choice function, the costs passed to the mode choice function are actually the composite of costs via all P&R sites. Furthermore, Park & Ride demand needs to be split to the relevant sites via the site choice. To facilitate the processing choice model inputs and outputs, the proportion of trips using each site are stored in three-dimensional matrices (O x D x P&RSite). Parking Constraint and Distribution The parking constraint and distribution models provide car users with an additional choice within the overall demand model structure: where to park their car. In many models, parking charges are generally applied to the destination zone trip, but this can lead to issues with detailed zone systems where areas of high demand (e.g. major shopping centres) may be located in a separate zone to the nearest car parks. The parking distribution model allows trips to park in a different zone to the destination zone, whilst the parking constraint model ensures that the parking demand in any given zone is not excessive. As the parking distribution forms another choice in the model hierarchy, the impact on runtimes is significant a further iterative loop is introduced to the model process. This also means that this part model has a high potential to lead to instability or convergence issues. Parking constraint increases the cost of trips to a particular zone as demand approaches capacity, nominally representing an increased search time. We have undertaken a literature review of several parking constraint models and the majority use exponential or similar curves to increase costs. Our chosen approach is illustrated in Figure 5 below, as this does not increase asymptotically when demand = capacity (as is the case in some models). This particular method is capped so that costs don t increase once demand exceeds a level twice that capacity. The reason for this is to improve stability and reduce convergence times in future years as demand increases. It also means that the other choice mechanisms (mode and destination choice) aren t distorted by implausibly large parking costs being sent back up the hierarchy through the composite costs. This is particularly an issue where a model doesn t have parking distribution as cars are forced to park in their destination zone and the only mechanism to remove them is destination choice (for singly-constrained purposes) or mode choice.

10 SIDDLE, COLLEARY: Modelling Parking Choices in Ireland s cities 1 st - 2 nd September 2016 Proceedings Figure 5: Parking search time (minutes) curve The parking distribution module allows a group of potential parking zones to be specified for each destination zone. Trips are given a choice to park in their destination zone, or in another nearby zone which will have a different access cost and will also include an additional cost to represent walk time to final destination. Due to the way in which the constrain mechanism increases parking costs as demand approaches capacity, the parking distribution model provides a mechanism to spread the parking demand between city centre and other attractive zones. Furthermore, because the parking charges differ between zones, some people may choose to park remotely from their destination zone in the first place, to avoid higher charges. The model works by calculating the total costs (travel time + search time + parking charge + walk time) for every potential parking zone as an alternative to those zones which are subject to capacity constraint. The distribution of trips between potential parking zones is then determined using a multinomial choice function: nn iijjjj = NN iiii ee λλ(gg iiii +CC pp +SS pp +WW pppp +αα iiiiii ) ee λλ(gg iiii +CC pp +SS pp +WW pppp +αα iiiiii ) pp Which determines the number of trips (n) between zones i and j, via zone p (where j and p could be the same zone). In the equation: N is the total number of trips between zone i and zone j; G is the generalised car cost between zone i and zone p, C and S are the parking charges and search times associated with zone p and W is the walk time between zones p and j. A calibration factor (α) may also be required. This mechanism is very similar to the park-and-ride model but with two crucial differences: The non-car leg journey is limited in length and can only be undertaken on foot; and, The choice of where to park is much more sensitive to cost and thus appears at a different location in the overall choice hierarchy. This means that parking location choice is a sub-choice to car, whereas park-and-ride is a main mode and is therefore an alternative to car.

11 Proceedings 1st - 2nd September 2016 SIDDLE, COLLEARY: Modelling Parking Choices in Ireland s cities As the search times (S) in each parking zone vary by the number of trips in the zone, this calculation must be performed iteratively. On each iteration, the parking constraint mechanism is used to increase costs in over capacity zones, and the distribution is recalculated. This is repeated iteratively until a converged solution is reached. This process is shown diagrammatically in Figure 6 below. Figure 6: Parking Constraint and Distribution Model Our understanding is that this differs slightly from the similar implementations used elsewhere. In other models with parking distribution, only the excess parking demand is skimmed and redistributed, rather than allowing all trips to redistribute on the basis changing costs. The skimming method has the advantage in that it will converge more quickly, but may not result in a realistic parking distribution. The demands which are passed to the road assignment model are the trips between the origin zone (i) and the parking zone (p), rather than to the destination zone (j). The model also generates walk trips between zones p and j and these are assigned to the active modes model. This causes a potential issue in that the costs skimmed from the road assignment

12 SIDDLE, COLLEARY: Modelling Parking Choices in Ireland s cities 1 st - 2 nd September 2016 Proceedings model need to be allocated to the original destination zone, rather than the parking zone for the purposes of passing the costs back up the model hierarchy to the destination and mode choice models. It is therefore important that there is a distinction between the assignment matrix produced by the parking distribution model (which describes where the vehicle is travelling to), and the demand matrix which describes where the person is going to (which must remain unaltered). The two matrices are linked by a three-dimensional conversion matrix (O x D x Parking zone) which describes the proportion of trips from each OD which parks in each zone. This will allow the demand matrix to be converted to the assignment matrix, and the assignment cost skims to be allocated to the correct OD. Summary This paper has provided details various parking mechanisms within the Regional Modelling System. The three main components and the recommendations for each are summarised below Workplace parking model approximates the impact of free workplace (and educational establishment) parking by removing the parking cost from the mode choice model for a defined number of users. The model is applied by firstly assuming free parking for all trips and from this determining the proportion of trips which should be offered free parking, such that the total number of free car trips matches the estimated number of spaces. The remaining trips are then subject to mode choice with parking charges included. The number of free workplace parking spaces has been determined by combining data from the Household Survey Travel Diary and the POWSCAR and comparing this to data collected from the Valuations Office. Park & Ride is treated as a main mode, with the costs for each site determined by combining the relevant costs from both the road and PT assignment models. Where multiple sites offer similar levels of service, a choice mechanism is used to determine how many trips would use each site. Allowing choice between sites increases both model runtimes and the time required to calibrate the model. Parking constraint applies where there is meaningful pressure on parking supply and is determined by comparing trip ends to parking capacity for each zone. The function used by the parking constraint mechanism increases costs exponentially as demand approaches capacity, but with a cap to prevent extremely high costs from distorting other parts demand model. The parking distribution model is a choice model which applies in areas subject to parking constraint and allows trips to each zone the option to park in an alternative nearby zone. The costs in the alternative zone may be lower due to reduced parking charges or a smaller penalty applied by the constraint mechanism, but would be increased due to the walk time between the alternative zone and the destination zone. The distribution model is applied iteratively since the constraint mechanism varies the parking costs according to the number of cars parked in each zone.