1. 2019
  2. ‘Computer says no’ is not enough: Using prototypical examples to diagnose artificial neural networks for discrete choice analysis

    Alwosheel, A., van Cranenburgh, S. & Chorus, C. G., 1 Dec 2019, In : Journal of Choice Modelling. 33, 100186.

    Research output: Contribution to journalArticleScientificpeer-review

  3. New software tools for creating stated choice experimental designs efficient for regret minimisation and utility maximisation decision rules

    van Cranenburgh, S. & Collins, A. T., 1 Jun 2019, In : Journal of Choice Modelling. 31, p. 104-123 20 p.

    Research output: Contribution to journalArticleScientificpeer-review

  4. A logistic regression based method to uncover the Value-of-Travel-Time distribution

    van Cranenburgh, S. & Kouwenhoven, M., 17 May 2019, (In preparation).

    Research output: Working paperScientific

  5. On the impact of vehicle automation on the value of travel time while performing work and leisure activities in a car: Theoretical insights and results from a stated preference survey

    Correia, G. H. D. A., de Looff, E., van Cranenburgh, S., Snelder, M. & van Arem, B., 1 Jan 2019, In : Transportation Research Part A: Policy and Practice. 119, p. 359-382 24 p.

    Research output: Contribution to journalArticleScientificpeer-review

  6. An artificial neural network based approach to investigate travellers’ decision rules

    van Cranenburgh, S. & Alwosheel, A., Jan 2019, In : Transportation Research. Part C: Emerging Technologies. 98, p. 152-166 15 p.

    Research output: Contribution to journalArticleScientificpeer-review

  7. Experimental design optimised for discriminating among different choice models

    Huang, B., van Cranenburgh, S. & Chorus, C., 2019.

    Research output: Contribution to conferenceAbstractScientific

  8. Substitutability as a spatial concept to evaluate travel alternatives

    van Wee, B., van Cranenburgh, S. & Maat, K., 2019, In : Journal of Transport Geography. 79, 12 p., 102469.

    Research output: Contribution to journalArticleScientificpeer-review

  9. Using Artificial Neural Networks for Recovering the Value-of-Travel-Time Distribution

    van Cranenburgh, S. & Kouwenhoven, M., 2019, Advances in Computational Intelligence - 15th International Work-Conference on Artificial Neural Networks, IWANN 2019, Proceedings. Joya, G., Rojas, I. & Catala, A. (eds.). Springer, p. 88-102 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11506 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  10. 2018
  11. How Will Automated Vehicles Shape Users’ Daily Activities? Insights from Focus Groups with Commuters in the Netherlands

    Pudane, B., Rataj, M., Molin, E., Mouter, N., van Cranenburgh, S. & Chorus, C., 1 Dec 2018, In : Transportation Research Part D: Transport and Environment. 14 p.

    Research output: Contribution to journalArticleScientificpeer-review

  12. The consumer-citizen duality: Ten reasons why citizens prefer safety and drivers desire speed

    Mouter, N., van Cranenburgh, S. & van Wee, B., Dec 2018, In : Accident Analysis and Prevention. 121, p. 53-63 11 p.

    Research output: Contribution to journalArticleScientificpeer-review

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