Application of traffic microsimulation for evaluating safety performance of urban signalized intersections

Shahdah, Usama Elrawy; Saccomanno, Frank; Persaud, Bhagwant

doi:10.1016/j.trc.2015.06.010

Cited by 58 publications

(37 citation statements)

References 11 publications

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“…The results showed a quantitative relationship between the number of conflicts and observed crash data. The work of Shahdah (Shahdah, Saccomanno, & Persaud, 2015), Wang (Wang & Stamatiadis, 2014), Gettman(Gettman & Head, 2003) also provided strong evidence to support the validity of microsimulation models in safety assessment (for motor vehicles).…”

Section: Microsimulation For Safety Analysismentioning

confidence: 93%

Contextual Guidance at Intersectionsfor Protected Bicycle Lanes

Monsere¹,

McNeil²,

Wang³

et al. 2019

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Section: Microsimulation For Safety Analysismentioning

confidence: 93%

Contextual Guidance at Intersectionsfor Protected Bicycle Lanes

Monsere¹,

McNeil²,

Wang³

et al. 2019

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“…From previous studies, it has been shown that there is strong correlation between the surrogate measures of safety and accident data. Shahdah, Saccomanno, & Persaud (2015) evaluated the safety levels of signalized intersections using microsimulation with TTC as the surrogate measure of safety. To predict crash risk, Li, Xiang, Ma, Gu, & Li (2016) used the conflict framework in a microsimulation setting.…”

Section: Conflict Analysismentioning

confidence: 99%

Strategic and Tactical Guidance for the Connected and Autonomous Vehicle Future

Ukkusuri¹,

Sagir²,

Mahajan³

et al. 2019

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JOINT TRANSPORTATION RESEARCH PROGRAMThe Joint Transportation Research Program serves as a vehicle for INDOT collaboration with higher education institutions and industry in Indiana to facilitate innovation that results in continuous improvement in the planning, design, construction, operation, management and economic efficiency of the Indiana transportation infrastructure. Abstract Autonomous vehicle (AV) and connected vehicle (CV) technologies are rapidly maturing and the timeline for their wider deployment is currently uncertain. These technologies are expected to have a number of significant societal benefits: traffic safety, improved mobility, improved road efficiency, reduced cost of congestion, reduced energy use, and reduced fuel emissions. State and local transportation agencies need to understand what this means for them and what they need to do now and in the next few years to prepare for the AV/CV future. In this context, the objectives of this research are as follows:1. Synthesize the existing state of practice and how other state agencies are addressing the pending transition to AV/CV environment 2. Estimate the impacts of AV/CV environment within the context of (a) traffic operations-impact of headway distribution and traffic signal coordination; (b) traffic control devices; (c) roadway safety in terms of intersection crashes 3. Provide a strategic roadmap for INDOT in preparing for and responding to potential issues This research is divided into two parts. The first part is a synthesis study of existing state of practice in the AV/CV context by conducting an extensive literature review and interviews with other transportation agencies. Based on this, we develop a roadmap for INDOT and similar agencies clearly delineating how they should invest in AV/CV technologies in the short, medium, and long term. The second part assesses the impacts of AV/CVs on mobility and safety via modeling in microsimulation software Vissim. 17.

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“…However, a thorough examination of papers attempting to link conflicts with collisions (e.g. [8], [9], [25]) reveals that the primary aim of these papers is the before-and-after evaluation of new technologies or infrastructure modifications with regards to safety. More specifically, these approaches seek to estimate if alterations to the current state of (a part of) the traffic environment will increase or reduce the number of collisions on specific spots.…”

Section: A Safety Assessment Using Simulated Conflictsmentioning

confidence: 99%

“…Recent research on traffic micro-simulation and road safety (e.g. [8], [9]) showed that it is now possible to estimate surrogate measures of safety performance based on dangerous vehicle interactions. If these risky vehicle interactions are filtered with established risk indicating thresholds, they are termed as "traffic conflicts".…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, studying conflicts can enhance the understanding of the specific characteristics that lead road users to drive unsafely and cause collisions [8]. Approaches that use traffic conflicts are however criticised in the literature because the correlation between traffic conflicts and traffic collisions on a segment may be low [9]. Nevertheless, it is admitted that the mechanism that triggers collisions and conflicts is analogous [8], [9].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Simulation Study of Predicting Real-Time Conflict-Prone Traffic Conditions

Katrakazas

Quddus

Chen

2018

IEEE Trans. Intell. Transport. Syst.

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Current approaches to estimate the probability of a traffic collision occurring in real-time primarily depend on comparing traffic conditions just prior to collisions with normal traffic conditions. Most studies acquire pre-collision traffic conditions by matching the collision time in the national crash database with the time in the traffic database. Since the reported collision time sometimes differs from the actual time, the matching method may result in traffic conditions not representative of pre-collision traffic dynamics. In this paper, this is overcome through the use of highly disaggregated vehicle-based traffic data from a traffic micro-simulation (i.e., VISSIM) and the corresponding traffic conflicts data generated by the surrogate safety assessment model (SSAM). In particular, the idea is to use traffic conflicts as surrogate measures of traffic safety so that traffic collisions data are not needed. Three classifiers (i.e., support vector machines, k-nearest neighbours, and random forests) are then employed to examine the proposed idea. Substantial efforts are devoted to making the traffic simulation as representative of the real-world as possible by employing data from a motorway section in England. Four temporally aggregated traffic datasets (i.e., 30 s, 1 min, 3 min, and 5 min) are examined. The main results demonstrate the viability of using traffic micro-simulation along with the SSAM for real-time conflicts prediction and the superiority of random forests with 5-min temporal aggregation in the classification results. However, attention should be given to the calibration and validation of the simulation software so as to acquire more realistic traffic data, resulting in more effective prediction of conflicts.

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Application of traffic microsimulation for evaluating safety performance of urban signalized intersections

Cited by 58 publications

References 11 publications

Contextual Guidance at Intersectionsfor Protected Bicycle Lanes

Contextual Guidance at Intersectionsfor Protected Bicycle Lanes

Strategic and Tactical Guidance for the Connected and Autonomous Vehicle Future

A Simulation Study of Predicting Real-Time Conflict-Prone Traffic Conditions

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