Inclement Weather Impacts on Freeway Traffic Stream Behavior

Rakha, Hesham; Farzaneh, Mohamadreza; Arafeh, Mazen; Sterzin, Emily

doi:10.3141/2071-02

Cited by 104 publications

(90 citation statements)

References 4 publications

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“…As the rain or snow intensity increases, maximum flow rate, speed intercept, and free-flow speed are reduced. The literature shows similar findings (5,10). Increasing snow intensity has also been found to reduce breakpoint density; however, the effect of rain on breakpoint intensity is not as clear as that for snow, as in some networks it decreases with rain intensity (e.g., Irvine), while in other cases it increases (e.g., Baltimore).…”

Section: Calibration Resultssupporting

confidence: 63%

Calibration of Traffic Flow Models under Adverse Weather and Application in Mesoscopic Network Simulation

Hou

Mahmassani

Alfelor

et al. 2013

Transportation Research Record

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Saint Paul, Minnesota, metropolitan area and showed that adverse weather causes clear reductions in traffic speed: up to 6% for rain, 13% for snow, and 12% for reduced visibility (1). Ibrahim and Hall (5) analyzed the effects of adverse weather on the speed-flow and flow-occupancy relationships for Canadian travelers and found the effects of snow to be much larger than those of rain and to cause a reduction in free-flow speed of 38 to 50 km/h. The effects of weather on traffic volume are also evident from empirical data. The research conducted by Datla and Sharma indicates that the impact of cold and snow on traffic volume varies with the type of trip and hour of the day (6). From traffic data collected in Canada, they observed that commute trips experience the lowest reductions in volume because of snowy weather, of up to 14%, while recreational trips experience the highest reductions, of up to 31%. They also found that reductions in commute trips during off-peak hours (−10% to −15%) were generally greater than those during peak hours (−6% to −10%); however, an opposite pattern was observed for recreational trips. All these studies show that inclement weather may have a significant and comprehensive impact on the transportation system that cannot be ignored by planners and decision makers.To mitigate the impacts of adverse weather on highway travel, the FHWA Road Weather Management Program has been involved in research, development, and deployment of strategies and tools for weather-responsive traffic management. In a project completed in 2006, the Road Weather Management Program used data from Seattle, Washington; Minneapolis, Minnesota; and Baltimore, Maryland; to develop statistical models and adjustment factors to quantify the impacts of weather on traffic flow (7). One of the challenges remaining is to integrate those models into decision support systems to help improve the performance of the transportation system during inclement weather conditions. The traffic estimation and prediction system (TrEPS) is a tool currently available for traffic planners and operators to assist with evaluating and implementing weatherresponsive traffic management strategies. Weather-sensitive TrEPS capabilities aim for accurate estimation and prediction of the traffic states under inclement weather conditions. Mahmassani et al. identified several key components within the TrEPS framework for which the impact of weather must be incorporated on both the supply and demand sides (8). One such element on the supply side consists of well-calibrated weather-integrated traffic flow models. Successful application of weather-sensitive TrEPS requires detailed calibration of weather effects on the underlying traffic flow models.The main objectives of this paper are (a) to develop systematic procedures for calibrating traffic flow models under inclement Calibration of Traffic Flow Models Under Adverse Weather and Application in Mesoscopic Network SimulationTian Hou, Hani S. Mahmassani, Roemer M. Alfelor, Jiwon Kim, and Meead SaberiThe we...

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Section: Calibration Resultssupporting

confidence: 63%

Calibration of Traffic Flow Models under Adverse Weather and Application in Mesoscopic Network Simulation

Hou

Mahmassani

Alfelor

et al. 2013

Transportation Research Record

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“…Equation 5.60 yields values that are consistent with those reported by Perrin et al (2001) (based on some assumed snowfall rates for each weather condition) and Rakha et al (2008). It is used in Step 7 to estimate the additional running time during weather events.…”

Section: If Equationsupporting

confidence: 64%

“…Speed was observed to decline with each weather condition, in the order cited (i.e., speed was reduced for wet, it was further reduced for wet and snowing, and so forth). Research indicates that precipitation rate has an influence on speed that is functionally similar to that shown in Equation 5.59 (Rakha et al 2008). …”

Section: If Equationmentioning

confidence: 54%

“…The weather categories in Table G Rakha et al (2008), who produced one of the few papers to isolate free-flow speed effects from capacity speed effects, were the primary source for the free-flow speed adjustments in Table G.11. The higher end of the range of percentage adjustments was assumed to apply to the freeways with the highest free-flow speeds under clear weather, dry pavement conditions.…”

Section: Weather Free-flow Speed Adjustmentsmentioning

confidence: 99%

See 1 more Smart Citation

Incorporating Travel Time Reliability into the Highway Capacity Manual

Zegeer¹,

Bonneson²,

Dowling³

et al. 2014

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“…If the traffic conditions are not homogeneous, the normal distribution is not well suitable anymore. [48].…”

Section: Figure 2 Investigated Distributionsmentioning

confidence: 99%

Assessing the Need for Applying Multimodal Speed Distribution in Road Transport Macro Emission Estimation

Török¹,

Zefreh²

2016

Acta Tech Jaur

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Vehicles speed distribution is an important input parameter in lots of issues, such as kinematical traffic simulation model, road design, speed limit evaluation, road traffic noise prediction or vehicles emission estimation. In this paper, a new approach has been presented in which the speed is randomly generated according to different speed distributions. Later on, these distributions were used as the basis of emission estimation. These different distributions were chosen according to the contextual traffic situation (free flow, pulsed accelerated flow, intersection, congestion, etc.) and were assigned to the fundamental diagram. The study of the effect of different speed distributions on the resulting emission level has been performed. The considerable difference in the emission models related to Log-normal distribution as well as exponential, chi-square and equal distribution to normal Gaussian distribution implies that these different traffic conditions will have a considerable effect on emission and will show the need for applying multimodal speed distribution in macro emission estimation rather than unimodal distribution. It should also be mentioned that this result may lead to the chance of revising the simulation software in further studies.

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Inclement Weather Impacts on Freeway Traffic Stream Behavior

Cited by 104 publications

References 4 publications

Calibration of Traffic Flow Models under Adverse Weather and Application in Mesoscopic Network Simulation

Calibration of Traffic Flow Models under Adverse Weather and Application in Mesoscopic Network Simulation

Incorporating Travel Time Reliability into the Highway Capacity Manual

Assessing the Need for Applying Multimodal Speed Distribution in Road Transport Macro Emission Estimation

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