Modeling the Frequency of Opposing Left-Turn Conflicts at Signalized Intersections Using Generalized Linear Regression Models

Zhang, Xin; Liu, Pan; Chen, Yuguang; Bai, Lu

doi:10.1080/15389588.2013.860526

Cited by 29 publications

(15 citation statements)

References 16 publications

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“…These studies have provided an insightful understanding on crash modeling and analysis, providing evidence that they could also be beneficial for conflict analysis, as traffic conflict data share similar traits with crash data, as highlighted by Zhang et al (13). Recent research has attempted to transfer crash frequency methodologies to conflict-based analysis.…”

Section: Background Reviewmentioning

confidence: 98%

Analysis of Rear-End Conflicts in Urban Networks using Bayesian Networks

Stylianou

Dimitriou

2018

Transportation Research Record: Journal of the Transportation R

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Crash analysis and modeling studies have provided insightful information on crash-contributing factors and the methodologies utilized provide evidence that they could also be beneficial for conflict analysis, as traffic conflict data share similar traits with crash data. In this study, a Bayesian network (BN) is estimated to comprehensively analyze rear-end conflict likelihood in an urban network, using disaggregate vehicle-by-vehicle data and the time-to-collision indicator to identify conflicts. The variables imported in the BN include (i) individual driver characteristics (e.g., speed); (ii) traffic operational characteristics (e.g., volume); and (iii) general characteristics (e.g., weather conditions). The inference analyses of the BN conducted to quantify the contributions of the variables affecting rear-end conflict likelihood in the urban network showed that rear-end conflict likelihood could be increased when the involved vehicles are of a different type, when the speed of the following vehicle is higher than the speed of the leading vehicle, when the individual speed is high when the individual headway is small, with a higher coefficient of variation of speed values, when the type of intersection nearest to the measuring point was a priority intersection, when the carriageway was of dual design, and when it was rainy. It was also shown that rear-end conflict likelihood increases during congestion and free-flow traffic. The findings of this study could be further developed to provide a good understanding of contributing factors to possible crashes in the urban network.

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Section: Background Reviewmentioning

confidence: 98%

Analysis of Rear-End Conflicts in Urban Networks using Bayesian Networks

Stylianou

Dimitriou

2018

Transportation Research Record: Journal of the Transportation R

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“…Only the traffic incidents with a TTC less than 2 s were considered traffic conflicts and used for safety assessment. More details with regard to the collection of traffic conflicts data are available from previous studies (35)(36)(37)(38)(39). This study considered only the conflicts between vehicle and pedestrian, since rear-end conflicts between vehicles are very rare.…”

Section: Collection Of Field Datamentioning

confidence: 99%

“…In total, 1,723 traffic conflicts between through vehicles and pedestrians were observed and identified at the selected sites. The procedure proposed by the previous study was followed for developing the conflict predictive model for the selected crosswalks (35,36). The conflict frequency counted in 15-min intervals was selected as the dependent variable in a conflict-predictive model.…”

Section: Impacts On Traffic Safetymentioning

confidence: 99%

Multiobjective Evaluation of Midblock Crosswalks on Urban Streets Based on TOPSIS and Entropy Methods

Yang

Liu

et al. 2016

Transportation Research Record: Journal of the Transportation R

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This study presents a multiobjective evaluation method to estimate the performance of various midblock crosswalk treatments on urban streets. The considered objectives included traffic operation, traffic safety, environmental impacts, and costs. Data were collected at 16 midblock crosswalks in the Nanjing area in China. Vissim simulation models were developed and calibrated with field data to evaluate the operational and environmental impacts of various midblock crosswalk treatments. For the impact of various treatments on traffic operation, the total control delay to vehicles on the major streets and pedestrians were estimated. For the impact on traffic safety, the frequency of traffic conflicts was calculated. For the impact on the environment, vehicle emissions and fuel consumption were quantified. The TOPSIS entropy evaluation method was then used to rank the performance of various treatments of crosswalks considering multiple performance measures. Compared with the life-cycle cost analysis method that quantifies the benefits and costs using monetized expressions to establish a common unit, the TOPSIS method presented does not require the well-developed economic theories of valuation. It was found that by combining multiple objectives in decision making, one may obtain different results with regard to the optimum treatments of crosswalks. The research results can be directly used by traffic engineers to select crosswalk treatments given traffic flow conditions and geometric design characteristics. The framework implemented in the study can also be used to estimate the impacts of other traffic projects considering multiobjective evaluation.

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“…The traffic conflicts technique was used to evaluate the safety impacts of left-turn waiting areas at signalized intersections. A traffic conflict is defined as an event involving two or more vehicles in which the action of one causes the other to make an evasive maneuver (9). Even though controversy remains with regard to the relationship between conflicts and crashes, the traffic conflicts technique has been widely used in countries like China, where reliable crash data are often not available.…”

Section: Impacts On Traffic Safetymentioning

confidence: 99%

“…Use of the expected conflict frequency as a safety measure also took into consideration the stochastic nature of conflict occurrences. The procedure proposed in a previous study was followed for developing the conflict predictive model for the selected intersections (9). Different types of models were tested and compared.…”

Section: Impacts On Traffic Safetymentioning

confidence: 99%

Multiobjective Evaluation of Left-Turn Waiting Areas at Signalized Intersections in China

Dong

Yang

et al. 2016

Transportation Research Record: Journal of the Transportation R

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This study presents a procedure for evaluating the impacts of left-turn waiting areas at signalized intersections considering multiple performance measures, including traffic operations, safety, environmental impacts, and fuel consumption. Data were collected at 33 sites in Nanjing, China. Vissim simulation models were developed for both isolated intersections and a roadway segment to evaluate the operational and environmental impacts of left-turn waiting areas at signalized intersections. The frequency of traffic conflicts associated with the left-turning traffic was considered the safety performance measure. The life-cycle cost method was used to combine different components in the total benefit for an isolated intersection. It was found that first, for an isolated signalized intersection, the implementation of left-turn waiting areas is overall economically beneficial when the storage capacity of the left-turn waiting area is more than one vehicle. Second, when signal coordination at arterials is considered, a set of factors may determine the overall benefits of using left-turn waiting areas, including the distance between adjacent intersections, the signal timing strategy, the size of left-turn waiting areas, and other factors. The overall benefits of using left-turn waiting areas should be determined case by case. For more than 70% of the randomly generated network cases, the lead-lag phase yields greater maximized progression bandwidth than the dual lagging phase. In this situation, it is generally recommended to implement a left-turn waiting area on one approach with a lead-lag left-turn phase. For only a few network cases in which the maximized progression bandwidth of the lag-lag phase is larger than that of the lead-lag phase, the implementation of left-turn waiting areas on both approaches with a dual-lagging left-turn phase is recommended.

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Modeling the Frequency of Opposing Left-Turn Conflicts at Signalized Intersections Using Generalized Linear Regression Models

Abstract: The occurrences of traffic conflicts at signalized intersections can be modeled using generalized linear regression models. The use of conflict predictive models has potential to expand the uses of surrogate safety measures in safety estimation and evaluation.

Cited by 29 publications

References 16 publications

Analysis of Rear-End Conflicts in Urban Networks using Bayesian Networks

Analysis of Rear-End Conflicts in Urban Networks using Bayesian Networks

Multiobjective Evaluation of Midblock Crosswalks on Urban Streets Based on TOPSIS and Entropy Methods

Multiobjective Evaluation of Left-Turn Waiting Areas at Signalized Intersections in China

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