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You searched for +publisher:"University of New South Wales" +contributor:("Waller, S Travis, Civil & Environmental Engineering, Faculty of Engineering, UNSW"). Showing records 1 – 5 of 5 total matches.

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University of New South Wales

1. Zhang, Xiang. Multi-objective network design: Road capacity expansion and multi-modal recharge facility location.

Degree: Civil & Environmental Engineering, 2017, University of New South Wales

 With the increase of urban population, travel demand has also significantly increased thus leading to traffic-related externalities. The prevalent traffic issues include, among others, road… (more)

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APA (6th Edition):

Zhang, X. (2017). Multi-objective network design: Road capacity expansion and multi-modal recharge facility location. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/59079 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:48417/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Zhang, Xiang. “Multi-objective network design: Road capacity expansion and multi-modal recharge facility location.” 2017. Doctoral Dissertation, University of New South Wales. Accessed May 08, 2021. http://handle.unsw.edu.au/1959.4/59079 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:48417/SOURCE02?view=true.

MLA Handbook (7th Edition):

Zhang, Xiang. “Multi-objective network design: Road capacity expansion and multi-modal recharge facility location.” 2017. Web. 08 May 2021.

Vancouver:

Zhang X. Multi-objective network design: Road capacity expansion and multi-modal recharge facility location. [Internet] [Doctoral dissertation]. University of New South Wales; 2017. [cited 2021 May 08]. Available from: http://handle.unsw.edu.au/1959.4/59079 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:48417/SOURCE02?view=true.

Council of Science Editors:

Zhang X. Multi-objective network design: Road capacity expansion and multi-modal recharge facility location. [Doctoral Dissertation]. University of New South Wales; 2017. Available from: http://handle.unsw.edu.au/1959.4/59079 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:48417/SOURCE02?view=true


University of New South Wales

2. Gu, Ziyuan. Dynamic Congestion Pricing in Urban Networks with the Network Fundamental Diagram and Simulation-Based Dynamic Traffic Assignment.

Degree: Civil & Environmental Engineering, 2019, University of New South Wales

 This thesis focuses on modeling and optimization of two-region urban pricing systems and analyzing and understanding the effects of pricing on the network traffic flow.… (more)

Subjects/Keywords: Simulation-based optimization; Congestion pricing; Network fundamental diagram; Dynamic traffic assignment

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APA (6th Edition):

Gu, Z. (2019). Dynamic Congestion Pricing in Urban Networks with the Network Fundamental Diagram and Simulation-Based Dynamic Traffic Assignment. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/61967 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:57871/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Gu, Ziyuan. “Dynamic Congestion Pricing in Urban Networks with the Network Fundamental Diagram and Simulation-Based Dynamic Traffic Assignment.” 2019. Doctoral Dissertation, University of New South Wales. Accessed May 08, 2021. http://handle.unsw.edu.au/1959.4/61967 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:57871/SOURCE02?view=true.

MLA Handbook (7th Edition):

Gu, Ziyuan. “Dynamic Congestion Pricing in Urban Networks with the Network Fundamental Diagram and Simulation-Based Dynamic Traffic Assignment.” 2019. Web. 08 May 2021.

Vancouver:

Gu Z. Dynamic Congestion Pricing in Urban Networks with the Network Fundamental Diagram and Simulation-Based Dynamic Traffic Assignment. [Internet] [Doctoral dissertation]. University of New South Wales; 2019. [cited 2021 May 08]. Available from: http://handle.unsw.edu.au/1959.4/61967 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:57871/SOURCE02?view=true.

Council of Science Editors:

Gu Z. Dynamic Congestion Pricing in Urban Networks with the Network Fundamental Diagram and Simulation-Based Dynamic Traffic Assignment. [Doctoral Dissertation]. University of New South Wales; 2019. Available from: http://handle.unsw.edu.au/1959.4/61967 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:57871/SOURCE02?view=true


University of New South Wales

3. Saxena, Neeraj. Modelling the Effect of the Number of Stop-&-gos on the Route Choice Behaviour of Car Drivers.

Degree: Civil & Environmental Engineering, 2017, University of New South Wales

 Driving in stop-&-go (S&G) traffic can be a frustrating experience and can lead to an increase in fuel emissions, driver distress and safety risks. Past… (more)

Subjects/Keywords: Stated Choice Experiment; Stop-&-go Traffic; Driving Simulator; Latent Class Choice Model (LCCM); Integrated Choice and Latent Variable Model (ICLV); Random Parameter Error Component Logit Model (RPECL); Driver Route Choice

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APA (6th Edition):

Saxena, N. (2017). Modelling the Effect of the Number of Stop-&-gos on the Route Choice Behaviour of Car Drivers. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/60191 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:50100/SOURCE2?view=true

Chicago Manual of Style (16th Edition):

Saxena, Neeraj. “Modelling the Effect of the Number of Stop-&-gos on the Route Choice Behaviour of Car Drivers.” 2017. Doctoral Dissertation, University of New South Wales. Accessed May 08, 2021. http://handle.unsw.edu.au/1959.4/60191 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:50100/SOURCE2?view=true.

MLA Handbook (7th Edition):

Saxena, Neeraj. “Modelling the Effect of the Number of Stop-&-gos on the Route Choice Behaviour of Car Drivers.” 2017. Web. 08 May 2021.

Vancouver:

Saxena N. Modelling the Effect of the Number of Stop-&-gos on the Route Choice Behaviour of Car Drivers. [Internet] [Doctoral dissertation]. University of New South Wales; 2017. [cited 2021 May 08]. Available from: http://handle.unsw.edu.au/1959.4/60191 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:50100/SOURCE2?view=true.

Council of Science Editors:

Saxena N. Modelling the Effect of the Number of Stop-&-gos on the Route Choice Behaviour of Car Drivers. [Doctoral Dissertation]. University of New South Wales; 2017. Available from: http://handle.unsw.edu.au/1959.4/60191 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:50100/SOURCE2?view=true


University of New South Wales

4. Li, Xun. Fairness in Transportation System.

Degree: Civil & Environmental Engineering, 2018, University of New South Wales

 Fairness is an important concept in transportation system because transport services are generally recognized as public goods and affect travellers’ access to basic needs. Moreover,… (more)

Subjects/Keywords: Transport Policy; Transportation System; Fairness; Transportation Modeling

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APA (6th Edition):

Li, X. (2018). Fairness in Transportation System. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/60407 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:52080/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Li, Xun. “Fairness in Transportation System.” 2018. Doctoral Dissertation, University of New South Wales. Accessed May 08, 2021. http://handle.unsw.edu.au/1959.4/60407 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:52080/SOURCE02?view=true.

MLA Handbook (7th Edition):

Li, Xun. “Fairness in Transportation System.” 2018. Web. 08 May 2021.

Vancouver:

Li X. Fairness in Transportation System. [Internet] [Doctoral dissertation]. University of New South Wales; 2018. [cited 2021 May 08]. Available from: http://handle.unsw.edu.au/1959.4/60407 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:52080/SOURCE02?view=true.

Council of Science Editors:

Li X. Fairness in Transportation System. [Doctoral Dissertation]. University of New South Wales; 2018. Available from: http://handle.unsw.edu.au/1959.4/60407 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:52080/SOURCE02?view=true


University of New South Wales

5. Maghrebi, Mojtaba. Using Machine Learning to Automatically Plan Concrete Delivery Dispatching.

Degree: Civil & Environmental Engineering, 2014, University of New South Wales

 Demand for concrete, regardless of the geographical location, is increasing globally. While the Ready Mixed Concrete (RMC) industry is facing an ever-increasing demand for concrete,… (more)

Subjects/Keywords: Large scale optimization; Concrete delivery; Machine learning; Experts’ decisions

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Maghrebi, M. (2014). Using Machine Learning to Automatically Plan Concrete Delivery Dispatching. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/54231 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:13522/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Maghrebi, Mojtaba. “Using Machine Learning to Automatically Plan Concrete Delivery Dispatching.” 2014. Doctoral Dissertation, University of New South Wales. Accessed May 08, 2021. http://handle.unsw.edu.au/1959.4/54231 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:13522/SOURCE02?view=true.

MLA Handbook (7th Edition):

Maghrebi, Mojtaba. “Using Machine Learning to Automatically Plan Concrete Delivery Dispatching.” 2014. Web. 08 May 2021.

Vancouver:

Maghrebi M. Using Machine Learning to Automatically Plan Concrete Delivery Dispatching. [Internet] [Doctoral dissertation]. University of New South Wales; 2014. [cited 2021 May 08]. Available from: http://handle.unsw.edu.au/1959.4/54231 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:13522/SOURCE02?view=true.

Council of Science Editors:

Maghrebi M. Using Machine Learning to Automatically Plan Concrete Delivery Dispatching. [Doctoral Dissertation]. University of New South Wales; 2014. Available from: http://handle.unsw.edu.au/1959.4/54231 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:13522/SOURCE02?view=true

.