Explicit Park-and-Ride modeling and capacity constraint #965

Description

@dhensle

Is your feature request related to a problem? Please describe.
Park-and-ride is currently onerous to model. For most ActivitySim implementations, the selection of the actual PnR lot used for park-and-ride trips is handled through hyper-pathing in the commerical assignment software packages. These packages will generate probabilities across multiple paths including potentially different PnR lots and distributes the PnR demand coming out of ActivitySim along those paths.

Skims are then generated for PnR based on these paths. The skims are very expensive -- need to generate them for both directions (since the auto portion vs tansit portion changes based on inbound vs outbound) and all the normal transit variables like in vehicle time, cost, wait time, etc. Additionally, ActivitySim does not have any mechanism to implement capacity constraints on the PnR lots.

Proposed PnR methodology
We want to implement an explicit park-and-ride lot choice model in ActivitySim. This would run before tour mode choice. The choosers for this model are all tours that have walk-transit access at their destination end. The alternatives are all lots with non-zero PnR capacity.

Utilities used to make the choice are broken down into two components - auto from tour origin to PnR lot and walk-transit from PnR lot to destination. The number of parking spaces would act as the size term.

The PnR lot choice model output is the zone_id of the PnR lot the tour would use if that tour were to choose park-and-ride in the tour mode choice model. PnR utilities in tour mode choice would be built similarly as the lot choice model -- auto costs to lot + transit costs to destination.

Capacities at each lot can then be calculated after tour mode choice. Tours that arrive after the lot is full (or sampled randomly) can be re-simulated with a new PnR lot choice option with full lots removed and updated tour mode choice utilities. PnR lot choice and tour mode choice would iterate until all PnR lots are under capacity. This is very similar to how the simulation-based constraint mechanism in workplace location works.

Some minor updates to the write trip matrices is needed to split the PnR trips into auto and transit portions for the output demand matrices.

Implications

  • Allows the removal of costly PnR skims
  • Allows the ability to build utilities directly to PnR lots and eventually estimate the coefficients for PnR lot choice
  • Allows the ability to track the PnR lot capacity and have tour mode choice respond
  • PnR lot choice also needs to be run when calculating logsums in upstream models (there is an option to skip this but then the logsum would not include PnR availability)

Limitations / Future Enhancements

  • Iterating only with tour mode choice does not allow people to change other aspects of their tour.
  • Downstream stop attributes should be built from the PnR lot. (We are currently not allowing stops on drive-transit trips)
  • Increase in runtime because we are adding another model, particularly in the logsum calculations.
  • Getting PnR lot choices out of survey data is often not a trivial exercise for estimation. The first implementation of the model will have to rely on coefficients from tour mode choice before the model can be estimated.
  • It makes tour mode choice calibration slightly more complicated.

Status
Development is underway according to the above design. An initial implementation is expected to be completed by the end of August 2025.

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    , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all
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    }
    } catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
    })();
    (function(){
    try {
    var __m = "github.com";
    var __re = new RegExp('^' + "github\\.com" + '
    
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    Explicit Park-and-Ride modeling and capacity constraint #965

    Description

    @dhensle

    Is your feature request related to a problem? Please describe.
    Park-and-ride is currently onerous to model. For most ActivitySim implementations, the selection of the actual PnR lot used for park-and-ride trips is handled through hyper-pathing in the commerical assignment software packages. These packages will generate probabilities across multiple paths including potentially different PnR lots and distributes the PnR demand coming out of ActivitySim along those paths.

    Skims are then generated for PnR based on these paths. The skims are very expensive -- need to generate them for both directions (since the auto portion vs tansit portion changes based on inbound vs outbound) and all the normal transit variables like in vehicle time, cost, wait time, etc. Additionally, ActivitySim does not have any mechanism to implement capacity constraints on the PnR lots.

    Proposed PnR methodology
    We want to implement an explicit park-and-ride lot choice model in ActivitySim. This would run before tour mode choice. The choosers for this model are all tours that have walk-transit access at their destination end. The alternatives are all lots with non-zero PnR capacity.

    Utilities used to make the choice are broken down into two components - auto from tour origin to PnR lot and walk-transit from PnR lot to destination. The number of parking spaces would act as the size term.

    The PnR lot choice model output is the zone_id of the PnR lot the tour would use if that tour were to choose park-and-ride in the tour mode choice model. PnR utilities in tour mode choice would be built similarly as the lot choice model -- auto costs to lot + transit costs to destination.

    Capacities at each lot can then be calculated after tour mode choice. Tours that arrive after the lot is full (or sampled randomly) can be re-simulated with a new PnR lot choice option with full lots removed and updated tour mode choice utilities. PnR lot choice and tour mode choice would iterate until all PnR lots are under capacity. This is very similar to how the simulation-based constraint mechanism in workplace location works.

    Some minor updates to the write trip matrices is needed to split the PnR trips into auto and transit portions for the output demand matrices.

    Implications

    • Allows the removal of costly PnR skims
    • Allows the ability to build utilities directly to PnR lots and eventually estimate the coefficients for PnR lot choice
    • Allows the ability to track the PnR lot capacity and have tour mode choice respond
    • PnR lot choice also needs to be run when calculating logsums in upstream models (there is an option to skip this but then the logsum would not include PnR availability)

    Limitations / Future Enhancements

    • Iterating only with tour mode choice does not allow people to change other aspects of their tour.
    • Downstream stop attributes should be built from the PnR lot. (We are currently not allowing stops on drive-transit trips)
    • Increase in runtime because we are adding another model, particularly in the logsum calculations.
    • Getting PnR lot choices out of survey data is often not a trivial exercise for estimation. The first implementation of the model will have to rely on coefficients from tour mode choice before the model can be estimated.
    • It makes tour mode choice calibration slightly more complicated.

    Status
    Development is underway according to the above design. An initial implementation is expected to be completed by the end of August 2025.

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      , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
      Skip to content

      Explicit Park-and-Ride modeling and capacity constraint #965

      Description

      @dhensle

      Is your feature request related to a problem? Please describe.
      Park-and-ride is currently onerous to model. For most ActivitySim implementations, the selection of the actual PnR lot used for park-and-ride trips is handled through hyper-pathing in the commerical assignment software packages. These packages will generate probabilities across multiple paths including potentially different PnR lots and distributes the PnR demand coming out of ActivitySim along those paths.

      Skims are then generated for PnR based on these paths. The skims are very expensive -- need to generate them for both directions (since the auto portion vs tansit portion changes based on inbound vs outbound) and all the normal transit variables like in vehicle time, cost, wait time, etc. Additionally, ActivitySim does not have any mechanism to implement capacity constraints on the PnR lots.

      Proposed PnR methodology
      We want to implement an explicit park-and-ride lot choice model in ActivitySim. This would run before tour mode choice. The choosers for this model are all tours that have walk-transit access at their destination end. The alternatives are all lots with non-zero PnR capacity.

      Utilities used to make the choice are broken down into two components - auto from tour origin to PnR lot and walk-transit from PnR lot to destination. The number of parking spaces would act as the size term.

      The PnR lot choice model output is the zone_id of the PnR lot the tour would use if that tour were to choose park-and-ride in the tour mode choice model. PnR utilities in tour mode choice would be built similarly as the lot choice model -- auto costs to lot + transit costs to destination.

      Capacities at each lot can then be calculated after tour mode choice. Tours that arrive after the lot is full (or sampled randomly) can be re-simulated with a new PnR lot choice option with full lots removed and updated tour mode choice utilities. PnR lot choice and tour mode choice would iterate until all PnR lots are under capacity. This is very similar to how the simulation-based constraint mechanism in workplace location works.

      Some minor updates to the write trip matrices is needed to split the PnR trips into auto and transit portions for the output demand matrices.

      Implications

      • Allows the removal of costly PnR skims
      • Allows the ability to build utilities directly to PnR lots and eventually estimate the coefficients for PnR lot choice
      • Allows the ability to track the PnR lot capacity and have tour mode choice respond
      • PnR lot choice also needs to be run when calculating logsums in upstream models (there is an option to skip this but then the logsum would not include PnR availability)

      Limitations / Future Enhancements

      • Iterating only with tour mode choice does not allow people to change other aspects of their tour.
      • Downstream stop attributes should be built from the PnR lot. (We are currently not allowing stops on drive-transit trips)
      • Increase in runtime because we are adding another model, particularly in the logsum calculations.
      • Getting PnR lot choices out of survey data is often not a trivial exercise for estimation. The first implementation of the model will have to rely on coefficients from tour mode choice before the model can be estimated.
      • It makes tour mode choice calibration slightly more complicated.

      Status
      Development is underway according to the above design. An initial implementation is expected to be completed by the end of August 2025.

      Metadata

      Metadata

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        None yet

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        , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
        Skip to content

        Explicit Park-and-Ride modeling and capacity constraint #965

        Description

        @dhensle

        Is your feature request related to a problem? Please describe.
        Park-and-ride is currently onerous to model. For most ActivitySim implementations, the selection of the actual PnR lot used for park-and-ride trips is handled through hyper-pathing in the commerical assignment software packages. These packages will generate probabilities across multiple paths including potentially different PnR lots and distributes the PnR demand coming out of ActivitySim along those paths.

        Skims are then generated for PnR based on these paths. The skims are very expensive -- need to generate them for both directions (since the auto portion vs tansit portion changes based on inbound vs outbound) and all the normal transit variables like in vehicle time, cost, wait time, etc. Additionally, ActivitySim does not have any mechanism to implement capacity constraints on the PnR lots.

        Proposed PnR methodology
        We want to implement an explicit park-and-ride lot choice model in ActivitySim. This would run before tour mode choice. The choosers for this model are all tours that have walk-transit access at their destination end. The alternatives are all lots with non-zero PnR capacity.

        Utilities used to make the choice are broken down into two components - auto from tour origin to PnR lot and walk-transit from PnR lot to destination. The number of parking spaces would act as the size term.

        The PnR lot choice model output is the zone_id of the PnR lot the tour would use if that tour were to choose park-and-ride in the tour mode choice model. PnR utilities in tour mode choice would be built similarly as the lot choice model -- auto costs to lot + transit costs to destination.

        Capacities at each lot can then be calculated after tour mode choice. Tours that arrive after the lot is full (or sampled randomly) can be re-simulated with a new PnR lot choice option with full lots removed and updated tour mode choice utilities. PnR lot choice and tour mode choice would iterate until all PnR lots are under capacity. This is very similar to how the simulation-based constraint mechanism in workplace location works.

        Some minor updates to the write trip matrices is needed to split the PnR trips into auto and transit portions for the output demand matrices.

        Implications

        • Allows the removal of costly PnR skims
        • Allows the ability to build utilities directly to PnR lots and eventually estimate the coefficients for PnR lot choice
        • Allows the ability to track the PnR lot capacity and have tour mode choice respond
        • PnR lot choice also needs to be run when calculating logsums in upstream models (there is an option to skip this but then the logsum would not include PnR availability)

        Limitations / Future Enhancements

        • Iterating only with tour mode choice does not allow people to change other aspects of their tour.
        • Downstream stop attributes should be built from the PnR lot. (We are currently not allowing stops on drive-transit trips)
        • Increase in runtime because we are adding another model, particularly in the logsum calculations.
        • Getting PnR lot choices out of survey data is often not a trivial exercise for estimation. The first implementation of the model will have to rely on coefficients from tour mode choice before the model can be estimated.
        • It makes tour mode choice calibration slightly more complicated.

        Status
        Development is underway according to the above design. An initial implementation is expected to be completed by the end of August 2025.

        Metadata

        Metadata

        Assignees

        Labels

        FeatureNew feature or request

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          None yet

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          , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
          Skip to content

          Explicit Park-and-Ride modeling and capacity constraint #965

          Description

          @dhensle

          Is your feature request related to a problem? Please describe.
          Park-and-ride is currently onerous to model. For most ActivitySim implementations, the selection of the actual PnR lot used for park-and-ride trips is handled through hyper-pathing in the commerical assignment software packages. These packages will generate probabilities across multiple paths including potentially different PnR lots and distributes the PnR demand coming out of ActivitySim along those paths.

          Skims are then generated for PnR based on these paths. The skims are very expensive -- need to generate them for both directions (since the auto portion vs tansit portion changes based on inbound vs outbound) and all the normal transit variables like in vehicle time, cost, wait time, etc. Additionally, ActivitySim does not have any mechanism to implement capacity constraints on the PnR lots.

          Proposed PnR methodology
          We want to implement an explicit park-and-ride lot choice model in ActivitySim. This would run before tour mode choice. The choosers for this model are all tours that have walk-transit access at their destination end. The alternatives are all lots with non-zero PnR capacity.

          Utilities used to make the choice are broken down into two components - auto from tour origin to PnR lot and walk-transit from PnR lot to destination. The number of parking spaces would act as the size term.

          The PnR lot choice model output is the zone_id of the PnR lot the tour would use if that tour were to choose park-and-ride in the tour mode choice model. PnR utilities in tour mode choice would be built similarly as the lot choice model -- auto costs to lot + transit costs to destination.

          Capacities at each lot can then be calculated after tour mode choice. Tours that arrive after the lot is full (or sampled randomly) can be re-simulated with a new PnR lot choice option with full lots removed and updated tour mode choice utilities. PnR lot choice and tour mode choice would iterate until all PnR lots are under capacity. This is very similar to how the simulation-based constraint mechanism in workplace location works.

          Some minor updates to the write trip matrices is needed to split the PnR trips into auto and transit portions for the output demand matrices.

          Implications

          • Allows the removal of costly PnR skims
          • Allows the ability to build utilities directly to PnR lots and eventually estimate the coefficients for PnR lot choice
          • Allows the ability to track the PnR lot capacity and have tour mode choice respond
          • PnR lot choice also needs to be run when calculating logsums in upstream models (there is an option to skip this but then the logsum would not include PnR availability)

          Limitations / Future Enhancements

          • Iterating only with tour mode choice does not allow people to change other aspects of their tour.
          • Downstream stop attributes should be built from the PnR lot. (We are currently not allowing stops on drive-transit trips)
          • Increase in runtime because we are adding another model, particularly in the logsum calculations.
          • Getting PnR lot choices out of survey data is often not a trivial exercise for estimation. The first implementation of the model will have to rely on coefficients from tour mode choice before the model can be estimated.
          • It makes tour mode choice calibration slightly more complicated.

          Status
          Development is underway according to the above design. An initial implementation is expected to be completed by the end of August 2025.

          Metadata

          Metadata

          Assignees

          Labels

          FeatureNew feature or request

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          No type

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          No projects

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            No milestone

            Relationships

            None yet

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            No branches or pull requests

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            , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
            Skip to content

            Explicit Park-and-Ride modeling and capacity constraint #965

            Description

            @dhensle

            Is your feature request related to a problem? Please describe.
            Park-and-ride is currently onerous to model. For most ActivitySim implementations, the selection of the actual PnR lot used for park-and-ride trips is handled through hyper-pathing in the commerical assignment software packages. These packages will generate probabilities across multiple paths including potentially different PnR lots and distributes the PnR demand coming out of ActivitySim along those paths.

            Skims are then generated for PnR based on these paths. The skims are very expensive -- need to generate them for both directions (since the auto portion vs tansit portion changes based on inbound vs outbound) and all the normal transit variables like in vehicle time, cost, wait time, etc. Additionally, ActivitySim does not have any mechanism to implement capacity constraints on the PnR lots.

            Proposed PnR methodology
            We want to implement an explicit park-and-ride lot choice model in ActivitySim. This would run before tour mode choice. The choosers for this model are all tours that have walk-transit access at their destination end. The alternatives are all lots with non-zero PnR capacity.

            Utilities used to make the choice are broken down into two components - auto from tour origin to PnR lot and walk-transit from PnR lot to destination. The number of parking spaces would act as the size term.

            The PnR lot choice model output is the zone_id of the PnR lot the tour would use if that tour were to choose park-and-ride in the tour mode choice model. PnR utilities in tour mode choice would be built similarly as the lot choice model -- auto costs to lot + transit costs to destination.

            Capacities at each lot can then be calculated after tour mode choice. Tours that arrive after the lot is full (or sampled randomly) can be re-simulated with a new PnR lot choice option with full lots removed and updated tour mode choice utilities. PnR lot choice and tour mode choice would iterate until all PnR lots are under capacity. This is very similar to how the simulation-based constraint mechanism in workplace location works.

            Some minor updates to the write trip matrices is needed to split the PnR trips into auto and transit portions for the output demand matrices.

            Implications

            • Allows the removal of costly PnR skims
            • Allows the ability to build utilities directly to PnR lots and eventually estimate the coefficients for PnR lot choice
            • Allows the ability to track the PnR lot capacity and have tour mode choice respond
            • PnR lot choice also needs to be run when calculating logsums in upstream models (there is an option to skip this but then the logsum would not include PnR availability)

            Limitations / Future Enhancements

            • Iterating only with tour mode choice does not allow people to change other aspects of their tour.
            • Downstream stop attributes should be built from the PnR lot. (We are currently not allowing stops on drive-transit trips)
            • Increase in runtime because we are adding another model, particularly in the logsum calculations.
            • Getting PnR lot choices out of survey data is often not a trivial exercise for estimation. The first implementation of the model will have to rely on coefficients from tour mode choice before the model can be estimated.
            • It makes tour mode choice calibration slightly more complicated.

            Status
            Development is underway according to the above design. An initial implementation is expected to be completed by the end of August 2025.

            Metadata

            Metadata

            Assignees

            Labels

            FeatureNew feature or request

            Type

            No type

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              No milestone

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              None yet

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              , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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              Explicit Park-and-Ride modeling and capacity constraint #965

              Description

              @dhensle

              Is your feature request related to a problem? Please describe.
              Park-and-ride is currently onerous to model. For most ActivitySim implementations, the selection of the actual PnR lot used for park-and-ride trips is handled through hyper-pathing in the commerical assignment software packages. These packages will generate probabilities across multiple paths including potentially different PnR lots and distributes the PnR demand coming out of ActivitySim along those paths.

              Skims are then generated for PnR based on these paths. The skims are very expensive -- need to generate them for both directions (since the auto portion vs tansit portion changes based on inbound vs outbound) and all the normal transit variables like in vehicle time, cost, wait time, etc. Additionally, ActivitySim does not have any mechanism to implement capacity constraints on the PnR lots.

              Proposed PnR methodology
              We want to implement an explicit park-and-ride lot choice model in ActivitySim. This would run before tour mode choice. The choosers for this model are all tours that have walk-transit access at their destination end. The alternatives are all lots with non-zero PnR capacity.

              Utilities used to make the choice are broken down into two components - auto from tour origin to PnR lot and walk-transit from PnR lot to destination. The number of parking spaces would act as the size term.

              The PnR lot choice model output is the zone_id of the PnR lot the tour would use if that tour were to choose park-and-ride in the tour mode choice model. PnR utilities in tour mode choice would be built similarly as the lot choice model -- auto costs to lot + transit costs to destination.

              Capacities at each lot can then be calculated after tour mode choice. Tours that arrive after the lot is full (or sampled randomly) can be re-simulated with a new PnR lot choice option with full lots removed and updated tour mode choice utilities. PnR lot choice and tour mode choice would iterate until all PnR lots are under capacity. This is very similar to how the simulation-based constraint mechanism in workplace location works.

              Some minor updates to the write trip matrices is needed to split the PnR trips into auto and transit portions for the output demand matrices.

              Implications

              • Allows the removal of costly PnR skims
              • Allows the ability to build utilities directly to PnR lots and eventually estimate the coefficients for PnR lot choice
              • Allows the ability to track the PnR lot capacity and have tour mode choice respond
              • PnR lot choice also needs to be run when calculating logsums in upstream models (there is an option to skip this but then the logsum would not include PnR availability)

              Limitations / Future Enhancements

              • Iterating only with tour mode choice does not allow people to change other aspects of their tour.
              • Downstream stop attributes should be built from the PnR lot. (We are currently not allowing stops on drive-transit trips)
              • Increase in runtime because we are adding another model, particularly in the logsum calculations.
              • Getting PnR lot choices out of survey data is often not a trivial exercise for estimation. The first implementation of the model will have to rely on coefficients from tour mode choice before the model can be estimated.
              • It makes tour mode choice calibration slightly more complicated.

              Status
              Development is underway according to the above design. An initial implementation is expected to be completed by the end of August 2025.

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                , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
                Skip to content

                Explicit Park-and-Ride modeling and capacity constraint #965

                Description

                @dhensle

                Is your feature request related to a problem? Please describe.
                Park-and-ride is currently onerous to model. For most ActivitySim implementations, the selection of the actual PnR lot used for park-and-ride trips is handled through hyper-pathing in the commerical assignment software packages. These packages will generate probabilities across multiple paths including potentially different PnR lots and distributes the PnR demand coming out of ActivitySim along those paths.

                Skims are then generated for PnR based on these paths. The skims are very expensive -- need to generate them for both directions (since the auto portion vs tansit portion changes based on inbound vs outbound) and all the normal transit variables like in vehicle time, cost, wait time, etc. Additionally, ActivitySim does not have any mechanism to implement capacity constraints on the PnR lots.

                Proposed PnR methodology
                We want to implement an explicit park-and-ride lot choice model in ActivitySim. This would run before tour mode choice. The choosers for this model are all tours that have walk-transit access at their destination end. The alternatives are all lots with non-zero PnR capacity.

                Utilities used to make the choice are broken down into two components - auto from tour origin to PnR lot and walk-transit from PnR lot to destination. The number of parking spaces would act as the size term.

                The PnR lot choice model output is the zone_id of the PnR lot the tour would use if that tour were to choose park-and-ride in the tour mode choice model. PnR utilities in tour mode choice would be built similarly as the lot choice model -- auto costs to lot + transit costs to destination.

                Capacities at each lot can then be calculated after tour mode choice. Tours that arrive after the lot is full (or sampled randomly) can be re-simulated with a new PnR lot choice option with full lots removed and updated tour mode choice utilities. PnR lot choice and tour mode choice would iterate until all PnR lots are under capacity. This is very similar to how the simulation-based constraint mechanism in workplace location works.

                Some minor updates to the write trip matrices is needed to split the PnR trips into auto and transit portions for the output demand matrices.

                Implications

                • Allows the removal of costly PnR skims
                • Allows the ability to build utilities directly to PnR lots and eventually estimate the coefficients for PnR lot choice
                • Allows the ability to track the PnR lot capacity and have tour mode choice respond
                • PnR lot choice also needs to be run when calculating logsums in upstream models (there is an option to skip this but then the logsum would not include PnR availability)

                Limitations / Future Enhancements

                • Iterating only with tour mode choice does not allow people to change other aspects of their tour.
                • Downstream stop attributes should be built from the PnR lot. (We are currently not allowing stops on drive-transit trips)
                • Increase in runtime because we are adding another model, particularly in the logsum calculations.
                • Getting PnR lot choices out of survey data is often not a trivial exercise for estimation. The first implementation of the model will have to rely on coefficients from tour mode choice before the model can be estimated.
                • It makes tour mode choice calibration slightly more complicated.

                Status
                Development is underway according to the above design. An initial implementation is expected to be completed by the end of August 2025.

                Metadata

                Metadata

                Assignees

                Labels

                FeatureNew feature or request

                Type

                No type

                Projects

                No projects

                  Milestone

                  No milestone

                  Relationships

                  None yet

                  Development

                  No branches or pull requests

                  Issue actions