Macroscopic traffic model for large scale urban traffic network design

Thonhofer, Elvira; Palau, Toni; Kühn, Andrea A.; Jakubek, Stefan; Kozek, Martin

doi:10.1016/j.simpat.2017.09.007

Cited by 46 publications

(31 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Microscopic modeling considers the individual description of vehicles, mesoscopic modeling considers the packets of vehicles sharing the same behaviors and finally the macroscopic modeling in which the dynamic of traffic flow is described as that of a fluid [2]. By comparing these modeling approaches, the macroscopic modeling presents fewer parameters, low computation times and provides a good description of traffic flow [21]. This paper presents a macroscopic model for traffic flow modeling.…”

Section: Introductionmentioning

confidence: 99%

“…The PWSL is an extended and improved version of the switched mode model [22]. Specifically, it is a linearized and simplified version of the cell transmission model, which is commonly used in traffic modeling literature [21]. Of course, the PWSL model permits the description of several traffic phenomena which make it suitable for various applications of estimation, control, and monitoring [23].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Integrating Model-Based Observer and Kullback–Leibler Metric for Estimating and Detecting Road Traffic Congestion

et al. 2018

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integrating Model-Based Observer and Kullback–Leibler Metric for Estimating and Detecting Road Traffic Congestion

et al. 2018

View full text Add to dashboard Cite

“…They can be subsumed into two categories: the bottom-up approach of microscopic modeling, and the top-down variant of macroscopic modeling [10,12]. In between these categories, mesoscopic models have emerged as a means to devise detailed simulations without extensive computational cost [13][14][15].State-of-the-art models include commercial ones like VISSIM [16], and noncommercial ones like MATSIM [17] and SUMO [18]. A significant challenge for most of these is to find data about the origin and destination of travelers (OD data).…”

mentioning

confidence: 99%

“…Thus, this model is especially targeted toward the full-scale assessment of urban areas in the interest of comparing diverse scenarios with different parameters.Recently, hybrid-modeling advances have emerged. They combine macroscopic traffic with instantaneous emissions models [14,27]. In Reference [13], the method subsequently provided a framework to assess CO 2 emissions in an urban environment.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Mesoscopic Urban-Traffic Simulation Based on Mobility Behavior to Calculate NOx Emissions Caused by Private Motorized Transport

et al. 2019

View full text Add to dashboard Cite

Motorized transport is one of the main contributors to anthropogenic CO 2 emissions, which cause global warming. Other emissions, like nitrogen oxides or carbon monoxide, are detrimental to human health. A prominent way to understand and thus be able to minimize emissions is by using traffic simulations to evaluate different scenarios. In that way, one can find out which policies, technical innovations, or behavioral changes can lead to a decrease in emissions. Since the effect of CO 2 is on a global scale, a macroscopic model is often enough to find reasonable results. However, NO x emissions can also have a direct, local effect. Therefore, it is interesting to investigate these emissions on a mesoscopic scale, to gain insight into the local distribution of this pollutant. In this study, we used a traffic model that, contrary to most other state-of-the-art traffic simulations, does not require an origin-destination matrix as an input, but calculates it from mobility behavior extracted from a survey. We then generated agents with realistic mobility behavior that perform their daily trips and calculate key features like congestion and emissions for every edge of the road network. Our approach has the additional advantage of allowing to investigate technical, juridical, as well as behavioral changes, all within the same framework. It is then possible to identify strategies that minimize NO x emissions caused by private motorized transport. Evaluation showed good agreement with reality in terms of local and temporal resolution. Especially when looking at the sum of emissions, the main feature for evaluating policies, and deviations between our simulation and available statistics were negligible. We found that, from all scenarios we investigated, the ban of old diesel cars is the most promising policy: By replacing all diesel cars built in 2005 or earlier with petrol cars of the same age, NO x emissions could drop by roughly a third.the city of Lyon [6] found that traffic was the main contributor, responsible for over 50% of total NO x emissions. When considering citizen exposure to NO 2 in urban areas, the relative contribution of the road sector is even bigger [5]. This extent of emissions is not only caused by the higher population density of an urban environment, but also by high congestion. Congested roads lead to an increase in traffic emissions and thus health risks for people in these areas [4]. In order to quantify those health risks, emission inventories created by coupled traffic and emissions models are then fed into meteorological and atmospheric chemistry transport models to yield their effect on air quality [7]. Subsequently, human exposure models link the concentration of pollutants with human factors [8].There is not necessarily a linear relation of the concentration to health effects. Thus, together with data on other adverse substances, the health hazard can finally be modeled [9].In order to combat the negative effects of traffic-related emissions, infrastructural and policy changes in a city's ro...

show abstract

The Effect of Urban and Rural Mobility Behaviour on Congestion and Emissions Resulting from Private Motorized Traffic

Plakolb

Jäger

Hofer

et al. 2021

Springer Proceedings in Complexity

View full text Add to dashboard Cite

Macroscopic traffic model for large scale urban traffic network design

Cited by 46 publications

References 22 publications

Integrating Model-Based Observer and Kullback–Leibler Metric for Estimating and Detecting Road Traffic Congestion

Integrating Model-Based Observer and Kullback–Leibler Metric for Estimating and Detecting Road Traffic Congestion

Mesoscopic Urban-Traffic Simulation Based on Mobility Behavior to Calculate NOx Emissions Caused by Private Motorized Transport

The Effect of Urban and Rural Mobility Behaviour on Congestion and Emissions Resulting from Private Motorized Traffic

Contact Info

Product

Resources

About