matsim-org/matsim-libs
Nov 2024 – Feb 2026
15 Months active
Languages Used
Java
Technical Skills
Algorithm OptimizationBackend DevelopmentData AnalysisJava DevelopmentSimulationSimulation Analysis
Nico Kühnel
PROFILE
Nico Kühnel
Over 15 months, this developer advanced the matsim-org/matsim-libs repository by delivering 33 features and resolving 19 bugs, focusing on demand-responsive transport, routing, and simulation reliability. They engineered enhancements such as configurable zone systems, robust DRT scheduling, and AWS S3 integration for cloud-based workflows. Their technical approach emphasized modular Java backend development, algorithm optimization, and code refactoring to improve maintainability and scalability. By introducing abstractions for reservation management, refining pathfinding with link-based routing, and strengthening test coverage, they enabled more accurate simulations and operational flexibility. Their work consistently addressed edge-case failures and supported extensible, production-grade transit modeling solutions.
Overall Statistics
Feature vs Bugs
63%Features
Repository Contributions
99Total
Bugs
19
Commits
99
Features
33
Lines of code
25,449
Activity Months15
Your Network
32 peopleSame Organization
@moia.io1
Shared Repositories
31
aleksMember
anaueMember
Ricardo EwertMember
Friedrich VölkersMember
Gerry CaseyMember
paulhMember
u234825Member
Jakob RehmannMember
janekderersteMember
Work History
February 2026
4 Commits • 1 Features
Feb 1, 2026February 2026 — Matsim-libs: Focused reliability improvements and data enablement for DRT scheduling. Fixed critical bugs affecting scheduling correctness and prebooking operations and introduced an end-of-simulation data export to transit schedules for downstream analysis. These changes reduce operational risk and improve analytical capabilities for transit-enabled simulations and decision-making.
4 Commits • 1 Features
Feb 1, 2026February 2026 — Matsim-libs: Focused reliability improvements and data enablement for DRT scheduling. Fixed critical bugs affecting scheduling correctness and prebooking operations and introduced an end-of-simulation data export to transit schedules for downstream analysis. These changes reduce operational risk and improve analytical capabilities for transit-enabled simulations and decision-making.
February 2026
January 2026
2 Commits • 2 Features
Jan 1, 2026January 2026 productivity summary for matsim-libs focusing on business value and technical achievements. Delivered two feature efforts with a key bug-fix: Reservation Management improvements and GeoFileReader S3 access, driving scheduling reliability, data accessibility, and scalable workflows.
January 2026
2 Commits • 2 Features
Jan 1, 2026January 2026 productivity summary for matsim-libs focusing on business value and technical achievements. Delivered two feature efforts with a key bug-fix: Reservation Management improvements and GeoFileReader S3 access, driving scheduling reliability, data accessibility, and scalable workflows.
December 2025
5 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for matsim-libs focusing on key business value and technical excellence. In this period, the team delivered substantive DRT scheduling enhancements and improved robustness around DynAgent prebooking, with strong emphasis on correctness, test coverage, and future-proofing. Key features delivered and major fixes: - DRT System Scheduling Enhancements: refactors and behavioral improvements to include pickup duration in accepted DRT requests, introduce stable ID helpers for DRT/DVRP entities, enable stop merging by extending planned end times, and improve slack-time calculation propagation. Comprehensive tests accompany these changes to ensure reliability. - Prebooking Robustness for DynAgent Handling: fix adaptive prebooking logic by adding checks for DynAgent instances to ensure only appropriate agents are processed, boosting robustness and efficiency. Technologies/skills demonstrated: - Java-centric refactoring and service-oriented design adjustments in a complex routing library - Test-driven development with expanded unit and integration tests for new scheduling logic - Code quality improvements including helper methods and clearer separation of concerns - End-to-end thinking about system performance, scheduling accuracy, and scalability Business value and impact: - More accurate and stable DRT scheduling leading to reduced wait times and better resource utilization - Stronger robustness in prebooking flow reducing edge-case failures during deployment - Clear foundations for future enhancements in DRT planning, stop coordination, and slack-time propagation
5 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for matsim-libs focusing on key business value and technical excellence. In this period, the team delivered substantive DRT scheduling enhancements and improved robustness around DynAgent prebooking, with strong emphasis on correctness, test coverage, and future-proofing. Key features delivered and major fixes: - DRT System Scheduling Enhancements: refactors and behavioral improvements to include pickup duration in accepted DRT requests, introduce stable ID helpers for DRT/DVRP entities, enable stop merging by extending planned end times, and improve slack-time calculation propagation. Comprehensive tests accompany these changes to ensure reliability. - Prebooking Robustness for DynAgent Handling: fix adaptive prebooking logic by adding checks for DynAgent instances to ensure only appropriate agents are processed, boosting robustness and efficiency. Technologies/skills demonstrated: - Java-centric refactoring and service-oriented design adjustments in a complex routing library - Test-driven development with expanded unit and integration tests for new scheduling logic - Code quality improvements including helper methods and clearer separation of concerns - End-to-end thinking about system performance, scheduling accuracy, and scalability Business value and impact: - More accurate and stable DRT scheduling leading to reduced wait times and better resource utilization - Stronger robustness in prebooking flow reducing edge-case failures during deployment - Clear foundations for future enhancements in DRT planning, stop coordination, and slack-time propagation
December 2025
November 2025
3 Commits • 2 Features
Nov 1, 2025During November 2025, I delivered key DRT-related enhancements in matsim-libs focused on scheduling accuracy, reliability, and test coverage. The work improves how departures are scheduled and how insertions are generated, directly increasing operational efficiency for demand-responsive transport use cases. Core outcomes include: earlier departure time calculations for DRT stop tasks, a bug fix addressing an off-by-one error in the insertion scheduler, and improvements to insertion generation that account for remaining dropoff time loss. These changes were supported by corresponding test updates to validate correctness and ensure long-term stability. Overall, the work strengthens the DRT scheduling framework by providing more precise timing, reducing edge-case failures, and enabling more reliable dispatch decisions for real-world operations.
November 2025
3 Commits • 2 Features
Nov 1, 2025During November 2025, I delivered key DRT-related enhancements in matsim-libs focused on scheduling accuracy, reliability, and test coverage. The work improves how departures are scheduled and how insertions are generated, directly increasing operational efficiency for demand-responsive transport use cases. Core outcomes include: earlier departure time calculations for DRT stop tasks, a bug fix addressing an off-by-one error in the insertion scheduler, and improvements to insertion generation that account for remaining dropoff time loss. These changes were supported by corresponding test updates to validate correctness and ensure long-term stability. Overall, the work strengthens the DRT scheduling framework by providing more precise timing, reducing edge-case failures, and enabling more reliable dispatch decisions for real-world operations.
October 2025
3 Commits • 1 Features
Oct 1, 2025October 2025 (matsim-org/matsim-libs) summary: Delivered two targeted updates to DRT operations that drive business value in dynamic transit planning, plus resilience improvements to handle operational hiccups without disruption. Key features delivered include DRT Operations and Time Window Enhancements that make constraints relative to the earliest departure, enabling more flexible routing, improved offer acceptance, and capacity-aware scheduling; and Graceful Handling of Vehicle Checkout Failures that logs a warning instead of throwing to maintain operation continuity during temporary checkout issues. These changes were implemented via commits 10405b0018ca9ee89e93a1d7d64240d6994e6c70 (make drt constrains relative again), 55af20e995704136ac61ed10d866107d5f76ebb3 (feat(drt-extensions): operation facility with capacity management + condensed shift starts), and 61e093a2cd9c9c3f1424e577e3b98ecbcda940fa (relax operation facility checkout).
3 Commits • 1 Features
Oct 1, 2025October 2025 (matsim-org/matsim-libs) summary: Delivered two targeted updates to DRT operations that drive business value in dynamic transit planning, plus resilience improvements to handle operational hiccups without disruption. Key features delivered include DRT Operations and Time Window Enhancements that make constraints relative to the earliest departure, enabling more flexible routing, improved offer acceptance, and capacity-aware scheduling; and Graceful Handling of Vehicle Checkout Failures that logs a warning instead of throwing to maintain operation continuity during temporary checkout issues. These changes were implemented via commits 10405b0018ca9ee89e93a1d7d64240d6994e6c70 (make drt constrains relative again), 55af20e995704136ac61ed10d866107d5f76ebb3 (feat(drt-extensions): operation facility with capacity management + condensed shift starts), and 61e093a2cd9c9c3f1424e577e3b98ecbcda940fa (relax operation facility checkout).
October 2025
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025: Delivered a generic AbstractReservationManager in matsim-libs/common contrib, introduced as a centralized reservation core. Extended by ChargerReservationManager to consolidate charger reservation logic and prepare for additional scenarios. This refactor reduces duplication, improves maintainability, and enables future extension for reservation types across modules. The change is recorded in commit 9562cf96b96cf60b6cf1ed0e3efca15e8becde08 (#4260).
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025: Delivered a generic AbstractReservationManager in matsim-libs/common contrib, introduced as a centralized reservation core. Extended by ChargerReservationManager to consolidate charger reservation logic and prepare for additional scenarios. This refactor reduces duplication, improves maintainability, and enables future extension for reservation types across modules. The change is recorded in commit 9562cf96b96cf60b6cf1ed0e3efca15e8becde08 (#4260).
August 2025
11 Commits • 4 Features
Aug 1, 2025August 2025 (2025-08) — Delivered architecture-driven DRT enhancements and reliability fixes in matsim-libs, reducing cross-module coupling, enabling easier extension, and improving ride-assignment efficiency. Key outcomes include the DRT Schedule Inquiry abstraction, centralized DrtRouteConstraints with per-request rejection, enhanced StopWaypoint system with a factory for flexible stops, shift scheduling reliability fixes, and idle-time optimization for EmptyVehicleRelocator. These changes strengthen operational robustness, support future DRT extensions, and translate into more predictable scheduling and better resource utilization.
11 Commits • 4 Features
Aug 1, 2025August 2025 (2025-08) — Delivered architecture-driven DRT enhancements and reliability fixes in matsim-libs, reducing cross-module coupling, enabling easier extension, and improving ride-assignment efficiency. Key outcomes include the DRT Schedule Inquiry abstraction, centralized DrtRouteConstraints with per-request rejection, enhanced StopWaypoint system with a factory for flexible stops, shift scheduling reliability fixes, and idle-time optimization for EmptyVehicleRelocator. These changes strengthen operational robustness, support future DRT extensions, and translate into more predictable scheduling and better resource utilization.
August 2025
July 2025
7 Commits • 3 Features
Jul 1, 2025July 2025 (2025-07) — Matsim-libs delivered key reliability and cloud-readiness improvements for matsim-org/matsim-libs. This month focused on enforcing DRT ride duration maximums, strengthening IO robustness, integrating AWS S3 for inputs/outputs, and fixing a charging task removal edge case. The changes improve scheduling fidelity, reduce runtime errors at shift boundaries, enable cloud-based data flows, and enhance observability.
July 2025
7 Commits • 3 Features
Jul 1, 2025July 2025 (2025-07) — Matsim-libs delivered key reliability and cloud-readiness improvements for matsim-org/matsim-libs. This month focused on enforcing DRT ride duration maximums, strengthening IO robustness, integrating AWS S3 for inputs/outputs, and fixing a charging task removal edge case. The changes improve scheduling fidelity, reduce runtime errors at shift boundaries, enable cloud-based data flows, and enhance observability.
May 2025
10 Commits • 2 Features
May 1, 2025February-May monthly summary for matsim-libs (2025-05). Focused on delivering routing accuracy improvements, DRT analytics enhancements, and improved operational diagnostics with an emphasis on business value and cross-scenario robustness.
10 Commits • 2 Features
May 1, 2025February-May monthly summary for matsim-libs (2025-05). Focused on delivering routing accuracy improvements, DRT analytics enhancements, and improved operational diagnostics with an emphasis on business value and cross-scenario robustness.
May 2025
April 2025
8 Commits • 2 Features
Apr 1, 2025April 2025 (2025-04) — Delivered key configurability, routing accuracy, and code-quality improvements in matsim-libs that strengthen production reliability and multi-market applicability for DRT/DVRP workloads. Business value centers on flexible zone definitions, precise travel-time calculations, and robust scheduling of unscheduled requests, underpinned by maintainable code. Key features delivered: - Configurable Zone Systems and Travel Time Matrix: Introduced independent zone systems for analysis, rebalancing, and the DVRP travel-time matrix; enabled a configurable zone system for the adaptive travel time matrix. Commits include 26b7d14ae33927df6cd24657146d793a0625e5e2 and 00b43850b637b212b17f2ccc1f9b5b1acfd7521f. - Routing System Refactor: Link-based Path Calculations: Refactored routing to operate on links rather than nodes to improve accuracy with turn restrictions and network connectivity. Commit: c1b7546b1548e5bfb7ac6d93d29fb86621ecb13d. Major bugs fixed: - Unscheduled Request Handling Improvement: ComplexRequestUnscheduler now uses the vehicle's schedule directly, enhancing how unscheduled requests are located and replaced. Commit: 9bcea91820f047bbb36a9f25aaf47090f2df212c. - Deprecation Warning for zoneTargetLinkSelection: Added a user warning to inform that the configuration is deprecated and will be ignored, guiding migration to rebalancing parameters. Commit: 1c1fa658e902b31cce6706ca502d06ca9faad00b. - Code Quality and Encapsulation Improvements (DRT and FISS): Refactored DRT config accessors to getters/setters and encapsulated FISS config fields; included minor typo fixes. Commits: 18893098f7452af89bbe4d6c677d5dc8b5c866ee, 2f1049ed0bee0f4f1f26cfbfd7c07dbd3fcce370, 743fa700af243a1e6c805ace3d14bdc9880dcc83. Overall impact and accomplishments: - Increased configurability and routing accuracy enable flexible deployments across markets and more reliable travel-time calculations. - Improved unscheduled-request handling reduces operational risk and downtime when requests cannot be immediately scheduled. - Clear deprecation warnings and encapsulated configurations boost maintainability, test reliability, and onboarding speed for future features. Technologies/skills demonstrated: - Advanced configuration management, link-based routing algorithms, and domain-specific refactoring in a Java/Kotlin ecosystem; emphasis on DRT, DVRP, and FISS modules; commitment hygiene and typo fixes to improve code quality and test stability.
April 2025
8 Commits • 2 Features
Apr 1, 2025April 2025 (2025-04) — Delivered key configurability, routing accuracy, and code-quality improvements in matsim-libs that strengthen production reliability and multi-market applicability for DRT/DVRP workloads. Business value centers on flexible zone definitions, precise travel-time calculations, and robust scheduling of unscheduled requests, underpinned by maintainable code. Key features delivered: - Configurable Zone Systems and Travel Time Matrix: Introduced independent zone systems for analysis, rebalancing, and the DVRP travel-time matrix; enabled a configurable zone system for the adaptive travel time matrix. Commits include 26b7d14ae33927df6cd24657146d793a0625e5e2 and 00b43850b637b212b17f2ccc1f9b5b1acfd7521f. - Routing System Refactor: Link-based Path Calculations: Refactored routing to operate on links rather than nodes to improve accuracy with turn restrictions and network connectivity. Commit: c1b7546b1548e5bfb7ac6d93d29fb86621ecb13d. Major bugs fixed: - Unscheduled Request Handling Improvement: ComplexRequestUnscheduler now uses the vehicle's schedule directly, enhancing how unscheduled requests are located and replaced. Commit: 9bcea91820f047bbb36a9f25aaf47090f2df212c. - Deprecation Warning for zoneTargetLinkSelection: Added a user warning to inform that the configuration is deprecated and will be ignored, guiding migration to rebalancing parameters. Commit: 1c1fa658e902b31cce6706ca502d06ca9faad00b. - Code Quality and Encapsulation Improvements (DRT and FISS): Refactored DRT config accessors to getters/setters and encapsulated FISS config fields; included minor typo fixes. Commits: 18893098f7452af89bbe4d6c677d5dc8b5c866ee, 2f1049ed0bee0f4f1f26cfbfd7c07dbd3fcce370, 743fa700af243a1e6c805ace3d14bdc9880dcc83. Overall impact and accomplishments: - Increased configurability and routing accuracy enable flexible deployments across markets and more reliable travel-time calculations. - Improved unscheduled-request handling reduces operational risk and downtime when requests cannot be immediately scheduled. - Clear deprecation warnings and encapsulated configurations boost maintainability, test reliability, and onboarding speed for future features. Technologies/skills demonstrated: - Advanced configuration management, link-based routing algorithms, and domain-specific refactoring in a Java/Kotlin ecosystem; emphasis on DRT, DVRP, and FISS modules; commitment hygiene and typo fixes to improve code quality and test stability.
March 2025
16 Commits • 4 Features
Mar 1, 2025March 2025 monthly summary for matsim-libs highlights reliability, modularity, and expanded DRT capabilities. Key outcomes include end-of-iteration demand consolidation, end-of-shift relocation options with pre-booked insertion heuristics, enhanced DRT shift scheduling and EV charging task management, and DI-based shift assignment to improve modularity and testability. Critical stability fixes for prebooked agent cleanup prevent processing of non-existent agents and avoid stuck iterations. Minor documentation fix and configuration/data management improvements further strengthened maintainability. These changes deliver tangible business value through more robust simulations, faster iteration cycles, and safer deployment of DRT features.
16 Commits • 4 Features
Mar 1, 2025March 2025 monthly summary for matsim-libs highlights reliability, modularity, and expanded DRT capabilities. Key outcomes include end-of-iteration demand consolidation, end-of-shift relocation options with pre-booked insertion heuristics, enhanced DRT shift scheduling and EV charging task management, and DI-based shift assignment to improve modularity and testability. Critical stability fixes for prebooked agent cleanup prevent processing of non-existent agents and avoid stuck iterations. Minor documentation fix and configuration/data management improvements further strengthened maintainability. These changes deliver tangible business value through more robust simulations, faster iteration cycles, and safer deployment of DRT features.
March 2025
February 2025
9 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for matsim-libs: Delivered two major features that enhance routing reliability and maintainability in turn-constrained networks and in core pathfinding. Turn Restrictions Robustness and Accuracy improved routing correctness by consolidating colored nodes, preserving attributes when cleaning turn restriction networks, and ensuring correct coming-from logic, enabling more trustworthy simulations in complex networks. Pathfinding Core Refactor and Robustness modernized the path calculation pipeline by using node/link iterators, removing the parallel-links verification step, and tidying naming/formatting to improve clarity, encapsulation, and robustness. Major bug fixes included addressing a turn restriction related bug in LeastCostPathTree and updating the turn restriction network cleaner, reducing edge-case failures in routing. These efforts have strengthened routing confidence, reduced maintenance burden, and improved overall simulation reliability. Technologies/skills demonstrated include Java refactoring, iterator-based design, encapsulation, code hygiene, and targeted debugging across a large codebase.
February 2025
9 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for matsim-libs: Delivered two major features that enhance routing reliability and maintainability in turn-constrained networks and in core pathfinding. Turn Restrictions Robustness and Accuracy improved routing correctness by consolidating colored nodes, preserving attributes when cleaning turn restriction networks, and ensuring correct coming-from logic, enabling more trustworthy simulations in complex networks. Pathfinding Core Refactor and Robustness modernized the path calculation pipeline by using node/link iterators, removing the parallel-links verification step, and tidying naming/formatting to improve clarity, encapsulation, and robustness. Major bug fixes included addressing a turn restriction related bug in LeastCostPathTree and updating the turn restriction network cleaner, reducing edge-case failures in routing. These efforts have strengthened routing confidence, reduced maintenance burden, and improved overall simulation reliability. Technologies/skills demonstrated include Java refactoring, iterator-based design, encapsulation, code hygiene, and targeted debugging across a large codebase.
January 2025
10 Commits • 2 Features
Jan 1, 2025Concise monthly summary for 2025-01 focusing on business value and technical achievements. Delivered targeted routing and data-structural improvements in matsim-libs, with performance optimizations and API correctness fixes.
10 Commits • 2 Features
Jan 1, 2025Concise monthly summary for 2025-01 focusing on business value and technical achievements. Delivered targeted routing and data-structural improvements in matsim-libs, with performance optimizations and API correctness fixes.
January 2025
December 2024
8 Commits • 4 Features
Dec 1, 2024December 2024 performance highlights for matsim-libs: DRT routing robustness improved with Detour Constraints including a minimum detour, removal of a misleading consistency check, and validation ensuring min detour < max detour. SpatialRequestFleetFilter added to optimize DRT/ride-sharing vehicle selection via spatial proximity filtering and integration into request handling and QSim. Noise simulation gained configurable flexibility with a dedicated flag to enable/disable reflection calculations independently of shielding. Network integrity strengthened through improved handling of disallowed links during merging and preservation of turn restrictions, with a Replacement tracking mechanism for traceability. These changes collectively improve reliability, scalability, and modeling fidelity, delivering tangible business value through better routing decisions, faster dispatch, and more accurate network state after merges.
December 2024
8 Commits • 4 Features
Dec 1, 2024December 2024 performance highlights for matsim-libs: DRT routing robustness improved with Detour Constraints including a minimum detour, removal of a misleading consistency check, and validation ensuring min detour < max detour. SpatialRequestFleetFilter added to optimize DRT/ride-sharing vehicle selection via spatial proximity filtering and integration into request handling and QSim. Noise simulation gained configurable flexibility with a dedicated flag to enable/disable reflection calculations independently of shielding. Network integrity strengthened through improved handling of disallowed links during merging and preservation of turn restrictions, with a Replacement tracking mechanism for traceability. These changes collectively improve reliability, scalability, and modeling fidelity, delivering tangible business value through better routing decisions, faster dispatch, and more accurate network state after merges.
November 2024
2 Commits • 2 Features
Nov 1, 2024Monthly summary for 2024-11 focused on delivering high-value features in matsim-libs with accompanying tests, improving configurability, observability, and software quality. The work aligns with product goals of configurable zone-level policies and enhanced DR wait-time analytics, driving better operational efficiency and service reliability.
2 Commits • 2 Features
Nov 1, 2024Monthly summary for 2024-11 focused on delivering high-value features in matsim-libs with accompanying tests, improving configurability, observability, and software quality. The work aligns with product goals of configurable zone-level policies and enhanced DR wait-time analytics, driving better operational efficiency and service reliability.
November 2024
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Quality Metrics
Correctness87.8%
Maintainability87.0%
Architecture83.8%
Performance78.6%
AI Usage20.4%
Skills & Technologies
Programming Languages
Java
Technical Skills
API DesignAPI DevelopmentAPI IntegrationAWSAgent-Based ModelingAlgorithm DesignAlgorithm OptimizationAlgorithm RefactoringBackend DevelopmentBug FixingCapacity ManagementCode CleanupCode GenericsCode OrganizationCode Refactoring
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