subject:( Motorway congestion)

Massey University

1. Yu, Xuefeng. Dynamic programming based coordinated ramp metering algorithms.

Degree: PhD, Mechatronics, 2014, Massey University

► Motorway congestion can be classified into two types, recurrent congestion and non-recurrent congestion. Recurrent congestion happens during peak hours. Non-recurrent congestion occurs due to car… (more)

▼ Motorway congestion can be classified into two types, recurrent congestion and non-recurrent congestion. Recurrent congestion happens during peak hours. Non-recurrent congestion occurs due to car accidents, weather conditions or public events. Negative impacts of traffic congestion include wasted fuel, pollution, travel delay and spillover effects caused by slow traffic. Ramp metering, as an only way to regulate traffic amount accessing to the motorway, is considered as the most cost-effective way to prevent the recurrent congestion. Coordinated ramp metering was developed to control a number of on-ramps simultaneously to improve traffic conditions on busy motorways. The existing coordinated ramp metering algorithms were normally established on macroscopic traffic flow models based on Payne’s wok, the performances of which were measured by the employed macroscopic model themselves, and the released metering rates of which tended to be continuous. Implementations in microscopic traffic simulators were few. This thesis presents DP (Dynamic Programming) based online control approaches for the optimal coordination of ramp metering and evaluates its performances in both macroscopic and microscopic traffic simulation environment. DP decision networks were proposed, where a traffic system can be modeled as a number of discrete traffic states and separated by time stages, and the control problem of coordinated ramp metering was treated as the minimization problem to search the optimal trajectory of discrete decision variables (ramp metering rates) that minimized a cost criterion in terms of TTS (total time spent) along the time horizon. Experiments conducted in the macroscopic simulation environment demonstrated the full potential of proposed algorithms with precise queue constrains in an ideal deterministic environment, and experiments conducted in the microscopic simulation environment indicated the performances of the proposed algorithms in a stochastic environment and revealed the feasibility in the real world. The implementation of DP ramp metering was proposed under the framework of receding horizon control. A 6.7km stretch of motorway in Auckland, New Zealand, was chosen as a study location and constructed by a microscopic simulator as a simulation scenario and by a macroscopic traffic model as a prediction model. The simulation results indicated that the proposed algorithms were able to eliminate motorway queues under high traffic demands and manage queue lengths at metered on-ramps when queue constrains were not overstrict. The simulation results also revealed that 9 discrete metering rates for each ramp meter were adequate to prevent motorway queues. Such feature not only proved that the optimal trajectory converged very fast in the proposed DP decision networks, but also made on-line control system possible due to less computational load.

Subjects/Keywords: Traffic congestion; Motorway congestion; Motorway ramps; Ramp metering; Traffic flow; On-ramps; Traffic simulation

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APA (6^th Edition):

Yu, X. (2014). Dynamic programming based coordinated ramp metering algorithms. (Doctoral Dissertation). Massey University. Retrieved from http://hdl.handle.net/10179/5927

Chicago Manual of Style (16^th Edition):

Yu, Xuefeng. “Dynamic programming based coordinated ramp metering algorithms.” 2014. Doctoral Dissertation, Massey University. Accessed April 18, 2021. http://hdl.handle.net/10179/5927.

MLA Handbook (7^th Edition):

Yu, Xuefeng. “Dynamic programming based coordinated ramp metering algorithms.” 2014. Web. 18 Apr 2021.

Vancouver:

Yu X. Dynamic programming based coordinated ramp metering algorithms. [Internet] [Doctoral dissertation]. Massey University; 2014. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/10179/5927.

Council of Science Editors:

Yu X. Dynamic programming based coordinated ramp metering algorithms. [Doctoral Dissertation]. Massey University; 2014. Available from: http://hdl.handle.net/10179/5927

Queensland University of Technology

2. Jiang, Rui. Strategies for rapid congestion recovery using ramp metering.

Degree: 2014, Queensland University of Technology

URL: https://eprints.qut.edu.au/68096/

► This research investigated strategies for motorway congestion management from a different angle: that is, how to quickly recover motorway from congestion at the end of… (more)

Subjects/Keywords: motorway congestion; rapid congestion recovery; ramp metering; cell transmission model; on-ramp queue estimation; queue management; ramp coordination; micro-simulation

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

APA (6^th Edition):

Jiang, R. (2014). Strategies for rapid congestion recovery using ramp metering. (Thesis). Queensland University of Technology. Retrieved from https://eprints.qut.edu.au/68096/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Jiang, Rui. “Strategies for rapid congestion recovery using ramp metering.” 2014. Thesis, Queensland University of Technology. Accessed April 18, 2021. https://eprints.qut.edu.au/68096/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Jiang, Rui. “Strategies for rapid congestion recovery using ramp metering.” 2014. Web. 18 Apr 2021.

Vancouver:

Jiang R. Strategies for rapid congestion recovery using ramp metering. [Internet] [Thesis]. Queensland University of Technology; 2014. [cited 2021 Apr 18]. Available from: https://eprints.qut.edu.au/68096/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Jiang R. Strategies for rapid congestion recovery using ramp metering. [Thesis]. Queensland University of Technology; 2014. Available from: https://eprints.qut.edu.au/68096/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

3. Miete, O.M. (author). Gaining new insights regarding traffic congestion, by explicitly considering the variability in traffic.

Degree: 2011, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:2673e7dd-af22-4d35-b3f7-e051d665bd80

► In hydraulic engineering it is known that for the evaluation of the performance of a system, a probabilistic approach is preferable to a deterministic one.… (more)

▼ In hydraulic engineering it is known that for the evaluation of the performance of a system, a probabilistic approach is preferable to a deterministic one. The essence of such a probabilistic approach is that random variability/uncertainty is explicitly taken into account. In this graduation project, this probabilistic way of looking at a system is applied to the traffic system, in the context of analyzing (ways to alleviate) traffic congestion. Basically, the mechanism behind traffic congestion can be described as a process of interaction between the traffic demand and supply on a road network. Both this traffic demand and supply show a significant level of temporal variability, which makes the resulting traffic conditions variable as well. Traditionally, in evaluations of the effectiveness of proposed congestion relief measures this variability is taken into account only in a limited or simplified way, or even not at all. Often simply a kind of ‘representative’ situation is calculated. The main objective of this research project was to reveal what kind of new insights can be obtained if we actually do explicitly/systematically take into account the variable nature of daily motorway congestion. After a comprehensive study into the sources of the variability in the traffic conditions, and the selection of appropriate performance indicators, a quantification model was developed. The main principle of this model is that a large number of traffic simulations are performed for varying traffic demand and supply values. Subsequently, the desired performance indicators are computed from the combined set of simulation results. In order to explore the (potential) new insights obtained by explicitly considering the variability, the developed model was applied to a reasonably sized real-life motorway network. From the results it is clear that a ‘representative’ calculation (in which all demand and supply variables are taken at their ‘representative’ level, which for example could be the mean or median value) does not give a good impression of the performance of the traffic system. It underestimates the congestion in certain respects, and – obviously – does not provide information on the uncertainty in travel times (which is an important factor in the societal costs of traffic congestion). The research has shown that if the variability in traffic is explicitly considered, new insights can be obtained into the relative importance of different (variable) influence factors. This was demonstrated by ‘deactivating’ these influence factors in the model (one at a time). The results of this demonstration indicate that the capacity variations due to the intrinsic randomness in human driving behavior play a central role in (peak period-related) congestion. Such information yields important insights into how traffic congestion can be remedied most effectively. By considering the example of a rush-hour lane, the research has shown that new insights can also be obtained into the effectiveness of specific measures that are proposed to… Advisors/Committee Members: Hoogendoorn, S.P. (mentor), Vrijling, J.K. (mentor), Van Gelder, P.H.A.J.M. (mentor), Van Lint, J.W.C. (mentor), Taale, H. (mentor), Wiggenraad, P.B.L. (mentor).

Subjects/Keywords: traffic congestion; variability; probabilistic; measures; evaluation; performance; traffic demand; traffic supply; variable; representative; randomness; stochasticity; stochastic; effectiveness; alleviate; traffic conditions; motorway; variation; variations; evaluations; simulation

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

APA (6^th Edition):

Miete, O. M. (. (2011). Gaining new insights regarding traffic congestion, by explicitly considering the variability in traffic. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:2673e7dd-af22-4d35-b3f7-e051d665bd80

Chicago Manual of Style (16^th Edition):

Miete, O M (author). “Gaining new insights regarding traffic congestion, by explicitly considering the variability in traffic.” 2011. Masters Thesis, Delft University of Technology. Accessed April 18, 2021. http://resolver.tudelft.nl/uuid:2673e7dd-af22-4d35-b3f7-e051d665bd80.

MLA Handbook (7^th Edition):

Miete, O M (author). “Gaining new insights regarding traffic congestion, by explicitly considering the variability in traffic.” 2011. Web. 18 Apr 2021.

Vancouver:

Miete OM(. Gaining new insights regarding traffic congestion, by explicitly considering the variability in traffic. [Internet] [Masters thesis]. Delft University of Technology; 2011. [cited 2021 Apr 18]. Available from: http://resolver.tudelft.nl/uuid:2673e7dd-af22-4d35-b3f7-e051d665bd80.

Council of Science Editors:

Miete OM(. Gaining new insights regarding traffic congestion, by explicitly considering the variability in traffic. [Masters Thesis]. Delft University of Technology; 2011. Available from: http://resolver.tudelft.nl/uuid:2673e7dd-af22-4d35-b3f7-e051d665bd80

Loughborough University

4. Wang, Chao. The relationship between traffic congestion and road accidents : an econometric approach using GIS.

Degree: PhD, 2010, Loughborough University

URL: http://hdl.handle.net/2134/6207

► Both traffic congestion and road accidents impose a burden on society, and it is therefore important for transport policy makers to reduce their impact. An… (more)

▼ Both traffic congestion and road accidents impose a burden on society, and it is therefore important for transport policy makers to reduce their impact. An ideal scenario would be that traffic congestion and accidents are reduced simultaneously, however, this may not be possible since it has been speculated that increased traffic congestion may be beneficial in terms of road safety. This is based on the premise that there would be fewer fatal accidents and the accidents that occurred would tend to be less severe due to the low average speed when congestion is present. If this is confirmed then it poses a potential dilemma for transport policy makers: the benefit of reducing congestion might be off-set by more severe accidents. It is therefore important to fully understand the relationship between traffic congestion and road accidents while controlling for other factors affecting road traffic accidents. The relationship between traffic congestion and road accidents appears to be an under researched area. Previous studies often lack a suitable congestion measurement and an appropriate econometric model using real-world data. This thesis aims to explore the relationship between traffic congestion and road accidents by using an econometric and GIS approach. The analysis is based on the data from the M25 motorway and its surrounding major roads for the period 2003-2007. A series of econometric models have been employed to investigate the effect of traffic congestion on both accident frequency (such as classical Negative Binomial and Bayesian spatial models) and accident severity (such as ordered logit and mixed logit models). The Bayesian spatial model and the mixed logit model are the best models estimated for accident frequency and accident severity analyses respectively. The model estimation results suggest that traffic congestion is positively associated with the frequency of fatal and serious injury accidents and negatively (i.e. inversely) associated with the severity of accidents that have occurred. Traffic congestion is found to have little impact on the frequency of slight injury accidents. Other contributing factors have also been controlled for and produced results consistent with previous studies. It is concluded that traffic congestion overall has a negative impact on road safety. This may be partially due to higher speed variance among vehicles within and between lanes and erratic driving behaviour in the presence of congestion. The results indicate that mobility and safety can be improved simultaneously, and therefore there is significant additional benefit of reducing traffic congestion in terms of road safety. Several policy implications have been identified in order to optimise the traffic flow and improve driving behaviour, which would be beneficial to both congestion and accident reduction. This includes: reinforcing electronic warning signs and the Active Traffic Management, enforcing average speed on a stretch of a roadway and introducing minimum speed limits in the UK. This thesis contributes to…

Subjects/Keywords: 526; Traffic congestion; Road accidents; GIS; M25 motorway; Site ranking; Accident hotspots; Spatial econometrics; Full Bayesian hierarchical models; Ordered and nominal response models; Two-stage mixed multivariate models

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

APA (6^th Edition):

Wang, C. (2010). The relationship between traffic congestion and road accidents : an econometric approach using GIS. (Doctoral Dissertation). Loughborough University. Retrieved from http://hdl.handle.net/2134/6207

Chicago Manual of Style (16^th Edition):

Wang, Chao. “The relationship between traffic congestion and road accidents : an econometric approach using GIS.” 2010. Doctoral Dissertation, Loughborough University. Accessed April 18, 2021. http://hdl.handle.net/2134/6207.

MLA Handbook (7^th Edition):

Wang, Chao. “The relationship between traffic congestion and road accidents : an econometric approach using GIS.” 2010. Web. 18 Apr 2021.

Vancouver:

Wang C. The relationship between traffic congestion and road accidents : an econometric approach using GIS. [Internet] [Doctoral dissertation]. Loughborough University; 2010. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/2134/6207.

Council of Science Editors:

Wang C. The relationship between traffic congestion and road accidents : an econometric approach using GIS. [Doctoral Dissertation]. Loughborough University; 2010. Available from: http://hdl.handle.net/2134/6207

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