Area-interlinking Design Analysis

The goal of the Area-Interlinking Design Analysis (AIDA) is to push the boundaries of what mobility simulation can do, develop and analyse innovative intelligent transport system solutions, and bring together the real and simulated world to form a symbiotic simulation environment.

Our research revolves around our established simulator CityMoS. It is a high-performance, parallel, microscopic, agent-based traffic simulator which can simulate days of traffic in megacities.

Its interactive user interface enables researchers as well as non-domain experts to meaningfully interact with the simulation environment and effortlessly identify regions of interest.

CityMoS provides open interfaces to connect it to other simulators and real-world data. This turns CityMoS into a citybrain — a platform to monitor, predict, and evaluate control strategies for smooth traffic in future smart cities.

• Enabling simulators to be able to carry out city-scale experiments
• Developing beyond the state-of-the-art parallelisation and performance-improving techniques
• Efficiently exploring large design and parameter spaces
• Using heterogeneous hardware environments and novel execution schemes

• Holistically evaluating smart city applications
• Conducting simulation studies from component all the way to the system level
• Developing novel Intelligent Transport System solutions
• Tackling new challenges such as mixed traffic of autonomous and conventional vehicles

• Creating open interfaces to bidirectionally couple with other simulators
• Incorporating both recorded and live real-world data to increase explanatory power and create a digital twin
• Immersing the human in the simulation to improve, validate and calibrate simulation models

1. [56] M. Xie, S. Ramanathan, A. Rau, D. Eckhoff, and F. Busch, “Design and evaluation of v2x-based dynamic bus lanes,” IEEE Access, vol. 9, pp. 136094–136104, Oct. 2021, DOI: 10.1109/ACCESS.2021.3117024
2. [55] J. Xiao, P. Andelfinger, W. Cai, D. Eckhoff, and A. Knoll, “OptCL: A middleware to optimise performance for high performance domain-specific languages on heterogeneous platforms,” in Proceedings of the 21st International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP), Virtual Event, Xiamen, China, Springer, Dec. 2021, accepted
3. [54] W. J. Tan, P. Andelfinger, D. Eckhoff, W. Cai, and A. Knoll, “Causality and consistency of state update schemes in synchronous agent-based simulations,” in Proceedings of the 2021 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (PADS), Virtual Event, USA, ACM, May 2021, DOI: 10.1145/3437959.3459262
4. [53] J. Ivanchev, C. Deboeser, T. Braud, A. Knoll, D. Eckhoff, and A. Sangiovanni-Vincentelli, “A hierarchical state-machine-based framework for platoon manoeuvre descriptions,” IEEE Access, vol. 9, pp. 128393–128406, Aug. 2021, DOI: 10.1109/ACCESS.2021.3106455
5. [52] T. Braud, J. Ivanchev, C. Deboeser, A. Knoll, D. Eckhoff, and A. Sangiovanni-Vincentelli, “AVDM: A hierarchical command-and-control system architecture for cooperative autonomous vehicles in highways scenario using microscopic simulations,” Autonomous Agents and Multi-Agent Systems, vol. 35, Springer, Apr. 2021, DOI: 10.1007/s10458-021-09499-6
6. [51] I. Bojic, C. Luo, X. Li, D. Zehe, D. Eckhoff, and C. Ratti, “Optimal railway disruption bridging using heterogeneous bus fleets,” IEEE Access, vol. 9, pp. 90656–90668, Jun. 2021, DOI: 10.1109/ACCESS.2021.3091576
7. [50] B. S. Bhati, J. Ivanchev, I. Bojic, A. Datta, and D. Eckhoff, “Utility-Driven k-anonymization of public transport user data,” IEEE Access, vol. 9, pp. 23608–23623, Jan. 2021, DOI: 10.1109/ACCESS.2021.3055505
8. [49] J. Xiao, K. G\”orkem, P. Andelfinger, D. Eckhoff, W. Cai, and A. Knoll, “Pedal to the bare metal: Road traffic simulation on FPGAs using high-level synthesis,” in Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (PADS), Miami, FL, USA, ACM, Jun. 2020, pp. 117–121, DOI: 10.1145/3384441.3395979
9. [48] J. Xiao, P. Andelfinger, W. Cai, P. Richmond, A. Knoll, and D. Eckhoff, “OpenABLext: An automatic code generation framework for agent-based simulations on CPU-GPU-FPGA heterogeneous platforms,” Concurrency and Computation: Practice and Experience, Wiley, pp. 1–15, Jun. 2020, ISSN: 1532-0634, DOI: 10.1002/CPE.5807
10. [47] M. Wagner, H. Cornet, D. Eckhoff, P. Andelfinger, W. Cai, and A. Knoll, “Evaluation of guidance systems at dynamic public transport hubs using crowd simulation,” in Proceedings of the 2020 Winter Simulation Conference (WSC), Orlando, FL, USA, IEEE, Dec. 2020, pp. 123–134, DOI: 10.1109/WSC48552.2020.9383949
11. [46] W. J. Tan, P. Andelfinger, W. Cai, Y. Xu, A. Knoll, and D. Eckhoff, “Multi-thread state update schemes for microscopic traffic simulation,” in Proceedings of the 2020 Winter Simulation Conference (WSC), Orlando, FL, USA, IEEE, Dec. 2020, pp. 182–193, DOI: 10.1109/WSC48552.2020.9383962
12. [45] B. Su, P. Andelfinger, D. Eckhoff, H. Cornet, G. Marinkovic, W. Cai, and A. Knoll, “A passenger model for simulating boarding and alighting in spatially confined transportation scenarios,” Journal of Computational Science, vol. 45, Elsevier, p. 101173, 2020, ISSN: 1877-7503, DOI: 10.1016/j.jocs.2020.101173
13. [44] M. Pruckner and D. Eckhoff, “Shared autonomous electric vehicles and the power grid: Applications and research challenges,” in Proceedings of the IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), The Hague, Netherlands, IEEE, Oct. 2020, pp. 1151–1155, DOI: 10.1109/ISGT-Europe47291.2020.9248844
14. [43] Q. A. P. Nguyen, P. Andelfinger, W. J. Tan, W. Cai, and A. Knoll, “Transitioning spiking neural network simulators to heterogeneous hardware,” ACM Transactions on Modeling and Computer Simulation (TOMACS), ACM, 2020, DOI: 10.1145/3422389
15. [42] A. Bhatia, J. Ivanchev, D. Eckhoff, and A. Knoll, “Autonomous vehicles as local traffic optimizers,” in Proceedings of the 20th International Conference on Computational Science (ICCS), Amsterdam, Netherlands, Springer, Jun. 2020, pp. 499–512, DOI: 10.1007/978-3-030-50371-0_37
16. [41] P. Andelfinger, Y. Xu, D. Eckhoff, W. Cai, and A. Knoll, “Fidelity and performance of state fast-forwarding in microscopic traffic simulations,” ACM Transactions on Modeling and Computer Simulation (TOMACS), vol. 30, no. 2, ACM, pp. 10:1-10:16, Apr. 2020, DOI: 10.1145/3366019
17. [40] P. Andelfinger, D. Eckhoff, W. Cai, and A. Knoll, “Fast-Forwarding of vehicle clusters in microscopic traffic simulations,” in Proceedings of the 20th ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (PADS), Miami, FL, USA, ACM, Jun. 2020, pp. 63–66, DOI: 10.1145/3384441.3395975
18. [39] J. Xiao, P. Andelfinger, D. Eckhoff, W. Cai, and A. Knoll, “A survey on agent-based simulation using hardware accelerators,” ACM Computing Surveys (CSUR), vol. 51, no. 6, ACM, Feb. 2019, DOI: 10.1145/3291048
19. [38] J. Xiao, P. Andelfinger, W. Cai, P. Richmond, A. Knoll, and D. Eckhoff, “Advancing automatic code generation for agent-based simulations on heterogeneous hardware,” in Proceedings of the International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms (HeteroPar), Goettingen, Germany, Springer, Aug. 2019, DOI: 10.1007/978-3-030-48340-1_24
20. [37] E. Tamayo, J. Ivanchev, D. Eckhoff, A. Sangiovanni-Vincentelli, and A. Knoll, “Multi-objective calibration of microscopic traffic simulation for highway traffic safety,” in Proceedings of the 22nd Intelligent Transportation Systems Conference (ITSC), Auckland, New Zealand, IEEE, Oct. 2019, DOI: 10.1109/ITSC.2019.8917044
21. [36] B. Su, P. Andelfinger, D. Eckhoff, H. Cornet, G. Marinkovic, W. Cai, and A. Knoll, “An agent-based model for evaluating the boarding and alighting efficiency of autonmous public transport vehicles,” in International Conference on Computational Science (ICCS 2019), Faro, Portugal, Springer, Jun. 2019, pp. 534–547, DOI: 10.1007/978-3-030-22734-0_39
22. [35] C. Sommer, D. Eckhoff, A. Brummer, D. S. Buse, F. Hagenauer, S. Joerer, and M. Segata, “Veins – the open-source vehicular network simulation framework,” in Recent Advances in Network Simulation, A. Virdis and M. Kirsche, Eds., Springer, May 2019, DOI: 10.1007/978-3-030-12842-5_6
23. [34] Q. A. P. Nguyen, P. Andelfinger, W. Cai, and A. Knoll, “Transitioning spiking neural network simulators to heterogeneous hardware,” in Proceedings of the 2019 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (PADS), Chicago, IL, USA, ACM, Jun. 2019, pp. 115–126, DOI: 10.1145/3316480.3322893
24. [33] C. Luo, X. Li, Y. Zhou, A. M. Caunhye, U. Alibrandi, N. Y. Aydin, C. Ratti, D. Eckhoff, and I. Bojic, “Data-driven disruption response planning for a mass rapid transit system,” in Proceedings of the KES International Symposium on Smart Transportation Systems 2019 (KES-STS-19), St Julians, Malta, Springer, Jun. 2019, DOI: 10.1007/978-981-13-8683-1_21
25. [32] J. Ivanchev, A. Knoll, D. Zehe, S. Nair, and D. Eckhoff, “A macroscopic study on dedicated highway lanes for autonomous vehicles,” in International Conference on Computational Science (ICCS 2019), Faro, Portugal, Springer, Jun. 2019, pp. 520–533, DOI: 10.1007/978-3-030-22734-0_38
26. [31] J. Ivanchev, D. Eckhoff, and A. Knoll, “System-level optimization of longitudinal acceleration control of autonomous vehicles in mixed traffic,” in Proceedings of the 22nd Intelligent Transportation Systems Conference (ITSC), Auckland, New Zealand, IEEE, Oct. 2019, DOI: 10.1109/ITSC.2019.8917281
27. [30] M. Gallet, T. Massier, and D. Zehe, “Developing a large-scale microscopic model of electric public bus operation and charging,” in Proceedings of the 2019 IEEE Vehicle Power and Propulsion Conference (VPPC), Hanoi, Vietnam, IEEE, Oct. 2019, pp. 1–5, DOI: 10.1109/VPPC46532.2019.8952361
28. [29] P. Andelfinger, J. Ivanchev, D. Eckhoff, W. Cai, and A. Knoll, “From effects to causes: reversible simulation and reverse exploration of microscopic traffic models,” in Proceedings of the 2019 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (PADS), Chicago, IL, USA, ACM, Jun. 2019, pp. 173–184, DOI: 10.1145/3316480.3322891
29. [28] M. Yang, P. Andelfinger, W. Cai, and A. Knoll, “Evaluation of conflict resolution methods for agent-based simulations on the GPU,” in Proceedings of the 2018 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (PADS), Rome, Italy, ACM, May 2018, pp. 129–132, DOI: 10.1145/3200921.3200940
30. [27] J. Xiao, P. Andelfinger, D. Eckhoff, W. Cai, and A. Knoll, “Exploring execution schemes for agent-based traffic simulation on heterogeneous hardware,” in Proceedings of the 22nd International Symposium on Distributed Simulation and Real Time Applications (DS-RT), Madrid, Spain, IEEE, Oct. 2018, pp. 243–252, DOI: 10.1109/DISTRA.2018.8601016
31. [26] I. Wagner and D. Eckhoff, “Technical privacy metrics: a systematic survey,” ACM Computing Surveys (CSUR), vol. 51, no. 3, ACM, Jun. 2018, DOI: 10.1145/3168389
32. [25] D. Krauß, P. Andelfinger, F. Paus, N. Vahrenkamp, and T. Asfour, “Evaluating and optimizing component-based robot architectures using network simulation,” in Proceedings of the 2018 Winter Simulation Conference (WSC), Gothenburg, Sweden, Dec. 2018, pp. 1061–1072, DOI: 10.1109/WSC.2018.8632243
33. [24] J. Ivanchev, S. Litescu, D. Zehe, M. Lees, H. Aydt, and A. Knoll, “Hard and soft closing of roads towards socially optimal routing,” in Proceedings of the 21st International Conference on Intelligent Transportation Systems (ITSC 2018), Maui, HI, USA, Nov. 2018, pp. 3499–3504, DOI: 10.1109/ITSC.2018.8569694
34. [23] D. Eckhoff and I. Wagner, “Privacy in the smart city – applications, technologies challenges and solutions,” IEEE Communications Surveys and Tutorials, vol. 20, no. 1, IEEE, pp. 489–516, 2018, DOI: 10.1109/COMST.2017.2748998
35. [22] P. Andelfinger, D. Zehe, Y. Chen, B. Su, D. Eckhoff, W. Cai, and A. Knoll, “Incremental calibration of seat selection preferences in agent-based simulations of public transport scenarios,” in Proceedings of the 2018 Winter Simulation Conference (WSC), Gothenburg, Sweden, Dec. 2018, pp. 833–844, DOI: 10.1109/WSC.2018.8632292
36. [21] P. Andelfinger, Y. Xu, W. Cai, D. Eckhoff, and A. Knoll, “Fast-forwarding agent states to accelerate microscopic traffic simulations,” in Proceedings of the 2018 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (PADS), Rome, Italy, ACM, May 2018, pp. 113–124, DOI: 10.1145/3200921.3200923
37. [20] P. Andelfinger, S. Udayakumar, D. Eckhoff, W. Cai, and A. Knoll, “Model preemption based on dynamic analysis of simulation data to accelerate traffic light timing optimisation,” in Proceedings of the 2018 Winter Simulation Conference (WSC), Gothenburg, Sweden, Dec. 2018, pp. 652–663, DOI: 10.1109/WSC.2018.8632411
38. [19] D. Zehe, S. Nair, A. Knoll, and D. Eckhoff, “Towards CityMoS: a coupled city-scale mobility simulation framework,” in Proceedings of the 5th GI/ITG KuVS Fachgespräch Inter-vehicle Communication (FG-IVC 2017), Erlangen, Germany, FAU Erlangen-Nuremberg, Apr. 2017, ISSN: 2191-5008
39. [18] Y. Xu, V. Viswanathan, and W. Cai, “Reducing synchronization overhead with computation replication in parallel agent-based road traffic simulation,” IEEE Transactions on Parallel and Distributed Systems, vol. 28, no. 11, pp. 3286–3297, Nov. 2017, ISSN: 1045-9219, DOI: 10.1109/TPDS.2017.2714165
40. [17] Y. Xu, W. Cai, D. Eckhoff, S. Nair, and A. Knoll, “A graph partitioning algorithm for parallel agent-based road traffic simulation,” in Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (PADS), Singapore, May 2017, pp. 209–219, DOI: 10.1145/3064911.3064914
41. [16] Y. Xu, W. Cai, H. Aydt, M. Lees, and D. Zehe, “Relaxing synchronization in parallel agent-based road traffic simulation,” ACM Transactions on Modeling and Computer Simulation (TOMACS) – Special Issue on PADS 2015, vol. 27, no. 2, pp. 14:1–24, May 2017, DOI: 10.1145/2994143
42. [15] S. Nair, N. Somani, A. Grunau, E. Dean-Leon, and A. Knoll, “Image processing units on ultra-low-cost embedded hardware: algorithmic optimizations for real-time performance,” Journal of Signal Processing Systems, vol. 90, no. 6, pp. 913–929, Aug. 2017, ISSN: 1939-8018, DOI: 10.1007/s11265-017-1267-1
43. [14] J. Ivanchev, D. Zehe, S. Nair, and A. Knoll, “Fast identification of critical roads by neural networks using system optimum assignment information,” in Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems (ITSC), Yokohama, Japan, Oct. 2017, DOI: 10.1109/ITSC.2017.8317626
44. [13] D. Eckhoff, D. Zehe, J. Ivanchev, and A. Knoll, “Smart city-to-vehicle – measuring, prediction influencing,” ATZelektronik worldwide, vol. 12, no. 2, Springer, pp. 60–63, Apr. 2017, ISSN: 2192-9092, DOI: 10.1007/s38314-017-0018-1, [Online] Available: https://link.springer.com/article/10.1007%2Fs38314-017-0018-1
45. [12] D. Eckhoff, D. Zehe, J. Ivanchev, and A. Knoll, “Smart city-to-vehicle – Messen, Vorhersagen Beeinflussen,” ATZelektronik, vol. 12, no. 2, Springer, pp. 68–73, Apr. 2017, ISSN: 2192-8878, DOI: 10.1007/s35658-017-0019-0
46. [11] R. Bi, J. Xiao, V. Viswanathan, and A. Knoll, “Influence of charging behaviour given charging infrastructure specification: a case study of singapore,” Journal of Computational Science, vol. 20, Elsevier, pp. 118–128, May 2017, DOI: 10.1016/j.jocs.2017.03.013
47. [10] R. Bi, J. Xiao, D. Pelzer, D. Ciechanowicz, D. Eckhoff, and A. Knoll, “A simulation-based heuristic for city-scale electric vehicle charging station placement,” in Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems (ITSC), Yokohama, Japan, IEEE, Oct. 2017, DOI: 10.1109/ITSC.2017.8317680
48. [9] D. Zehe, V. Viswanathan, W. Cai, and A. Knoll, “Online data extraction for large-scale agent-based simulations,” in Proceedings of the 2016 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (PADS), Banff, Canada, ACM, May 2016, pp. 69–78, DOI: 10.1145/2901378.2901384
49. [8] R. Yaadhav, S. Nair, and A. Knoll, “Precise measurement of cargo boxes for gantry robot palletization in large scale workspaces using low-cost RGB-D sensors,” in Proceedings of the 13th Asian Conference on Computer Vision (ACCV 2016), Taipei, Taiwan, Springer, Nov. 2016, DOI: 10.1007/978-3-319-54190-7_29
50. [7] M. Wagner and V. Viswanathan, “Analyzing the impact of driving behavior at traffic lights on urban heat,” in Proceedings of the Fourth International Conference on Countermeasure to Urban Heat Islands (IC2UHI), Singapore, Elsevier, Jun. 2016, pp. 303–307, DOI: 10.1016/j.proeng.2016.10.037
51. [6] A. Sunderrajan, V. Viswanathan, W. Cai, and A. Knoll, “Traffic state estimation using floating car data,” in Proceedings of the 2016 International Conference on Computational Science (ICCS), vol. 80, San Diego, CA, USA, Elsevier, Jun. 2016, pp. 2008–2018, DOI: 10.1016/j.procs.2016.05.521
52. [5] A. Sunderrajan, V. Viswanathan, W. Cai, and A. Knoll, “Data driven adaptive traffic simulation of an expressway,” in Proceedings of the 2016 Winter Simulation Conference (WSC), Washington, D.C., USA, Dec. 2016, pp. 1194–1205, DOI: 10.1109/WSC.2016.7822176
53. [4] N. Somani, M. Rickert, A. Gaschler, C. Cai, A. Perzylo, and A. Knoll, “Task level robot programming using prioritized non-linear inequality constraints,” in Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, South Korea, IEEE, Oct. 2016, pp. 430–437, DOI: 10.1109/IROS.2016.7759090
54. [3] J. Ivanchev, D. Zehe, V. Viswanathan, S. Nair, and A. Knoll, “BISOS: backwards incremental system optimum search algorithm for fast socially optimal traffic assignment,” in Proceedings of the IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Rio de Janeiro, Brazil, IEEE, Nov. 2016, pp. 2137–2142, DOI: 10.1109/ITSC.2016.7795902
55. [2] L. Goel, R. Khandelwal, E. Retamino, S. Nair, and A. Knoll, “Application of a hybrid relation extraction framework for intelligent natural language processing,” in Proceedings of the 2016 Intelligent Systems Technologies and Applications (ISTA’16), Jaipur, India, Springer, Oct. 2016, pp. 803–813, DOI: 10.1007/978-3-319-47952-1_64
56. [1] R. Bi, J. Xiao, V. Viswanathan, and A. Knoll, “Influence of charging behaviour given charging station placement at existing petrol stations and residential car park locations in singapore,” in Proceedings of the 2016 International Conference on Computational Science (ICCS), San Diego, CA, USA, Jun. 2016, pp. 335–344, DOI: 10.1016/j.procs.2016.05.347
57. [2] J. Ivanchev, J. A. Fonseca, and A. Knoll, “Anthropogenic heat due to road transport: A mesoscopic assessment and mitigation potential of electric vehicles and autonomous vehicles in Singapore,” in Proceedings of the 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), Rhodes, Greece, IEEE, Oct. 2020, pp. 1–8
58. [1] J. Ivanchev, T. Braud, D. Eckhoff, D. Zehe, A. Sangiovanni-Vincentelli, and A. Knoll, “On the need for novel tools and models for mixed traffic analysis,” in 26th ITS World Congress, Singapore, Oct. 2019