1,720,997 research outputs found
Estimation of Annual Average Daily Traffic from one-week traffic counts. A combined ANN-Fuzzy approach
No full textThis paper presents an approach to estimation of the Annual Average Daily Traffic (AADT) from a one-week seasonal traffic count (STC) of a road section. The proposed method uses fuzzy set theory to represent the fuzzy boundaries of road groups and neural networks to assign a road segment to one or more predefined road groups. The approach was tested with data obtained in the Province of Venice, Italy, for the period of the year in which STCs are taken. The method produced accurate results, which may be of interest for proper planning of monitoring and minimizing traffic count costs
Comparison of Clustering Methods for Road Group Identification in FHWA Traffic Monitoring Approach: Effects on AADT Estimates
No full textDefining road groups is the first step in the FHWA factor approach procedure for Annual Average Daily Traffic (AADT) estimation and is one of the main sources of errors in AADT estimates. This paper focuses on a comparative analysis of cluster analysis methods to identify road groups with similar traffic patterns according to different combinations of seasonal adjustment factors calculated for passenger vehicles and trucks. The aim is to highlight the differences among methods and input variables in the AADT estimation process, optimizing information commonly available to analysts. The analysis made use of traffic data from fifty Automatic Traffic Recorder (ATR) sites in the Province of Venice, Italy. The estimation accuracy of the clustering methods was assessed and compared by considering the values of Mean Absolute Percent Error in AADT estimates. The performance of clustering methods was found to differ, depending on datasets and traffic patterns. Particularly significant for the accuracy of AADT estimates was the choice to use seasonal adjustment factors disaggregated by vehicle type as input variables
Effects of Driver Task-related Fatigue on Driving Performance
No full textIn this study, passive task-related fatigue effects on highway driving were analyzed by means of driving simulator experiments. Ten drivers were asked to drive in various environments in the morning (9:00-11:00 a.m.) and early afternoon (1:00-3:00 p.m.). Mean of Absolute Steering Error and Standard Deviation of Lateral Position, calculated on sub-intervals of 4 minutes, were analysed as response variables. The results confirmed the negative influence of the duration of driving tasks and circadian effects on driving performance, increasing the likelihood of “near misses” and accidents
Analysis of drivers’ behavior in different environments: experiments with a driving simulator
No full textDriver fatigue is a multidimensional and complex subject, addressed in past years by many researchers but not completely defined and clarified: terms like drowsiness, sleepiness and fatigue are often used like synonymous. The importance of studying fatigue is related to the fact that it represents a contributing factor in many crashes every year.
Following a sub categorization of fatigue concept recently proposed by May and Baldwin (2009) this paper focuses on the analysis of passive task-related (TR) effects of highway driving in monotonous environments. The analysis proposed in this paper was based on results obtained using a driving simulator approach, which has been widely adopted in recent years for this kind of studies, given the opportunity to analyze risky driving conditions in a safe and controlled environment.
Differently from previous studies, this paper analyzes the effects of monotonous environment separating its effects from other causal factors of fatigued state, aiming at a better evaluation of their relative importance and of the onset of driving fatigue phenomenon.
Mixed-effects models were chosen as suitable analysis tool to deal with the objectives of this study
Comparing Direct Transferability of Logit and Fuzzy Logic Models of Gap Acceptance at Unsignalized Intersections
No full textThis paper presents a comparative analysis of the performance of Logit models vs. Fuzzy logic models of gap-acceptance behavior in terms of their direct transferability. This refers to situations in which a model estimated in a given experimental context is directly applied in a different context without any updating. Data collected at four priority intersections having different characteristics in terms of geometry, location and type of control (stop vs. yield sign) were used to test the quality of the results obtained when transferring each type of model from an original to an alternative situation. The comparison was carried out based on metrics commonly used in the so-called ROC (Receiver Operating Characteristic) curve analysis. The results show that both models have essentially the same capability in terms of direct transferability, and that their performance in contexts different from those of original development could be more than adequate for application purposes
Network-level analysis of the effects of drivers’ preferences toward driving behavior of Automated Vehicles: a microsimulation study on a highway segment
No full textWith the increasing prevalence of Level 2 and Level 3 Automated Vehicles (AVs) equipped with advanced technological features like Adaptive Cruise Control (ACC), the need to investigate their impact on traffic efficiency when sharing roads with Human-Driven Vehicles (HDVs) becomes crucial. The performance of these AVs (Level 2 and Level 3) primarily depends on the behaviour of users, as they prefer a similar or more defensive driving style when riding in AVs compared to their normal driving behaviour. Neglecting this diversity in the driving styles of AVs undermines the accuracy of the results of studies investigating their impact on traffic efficiency. Therefore, this study aimed to assess the impact of AVs on travel time, delay, and flow rate, considering the typical driving styles of drivers. We investigated a gradual increase in the penetration rate of AVs from 0% to 100% in 25% increments within a simulated mixed traffic environment of AVs and HDVs on a highway segment in the Veneto region, Italy, using the VISSIM microsimulation software. The results show that an increase in the penetration rates of AVs with different driving styles increases travel time (1.08% - 4.09%) and delay (13.22% - 99.28%) while exhibiting a negligible improvement in flow rate (0.09% - 0.26%)
Freeway rear-end collision risk estimation with extreme value theory approach. A case study
No full textThe current practice in crash-based safety analysis is hindered by some weaknesses: rarity of crashes, lack of timeliness, mistakes in crash reporting. Researchers are testing alternative approaches to safety estimation without the need of crash data. This paper presents an application of Extreme Value Theory in road safety analysis, using Time-To-Collision as a surrogate safety measure to estimate the risk to be involved in a freeway rear-end collision. The method was tested using data from an Italian toll-road with good results
Fuzzy Logic-based Incident Detection System using Loop Detectors Data
No full textVehicle loop detectors or other equipment installed on cross-sections are commonly used for monitoring traffic flow conditions on road network. For operational analysis it is crucial to distinguish between low level of service related to oversaturated conditions and generated by extraordinary events as incidents. In case of incident it is fundamental to have a prompt response in order to activate any requested countermeasure, such as rescue activation and traffic detour. This paper introduces a control system which recognizes incidents from vehicle loop detectors data (system control), and identifies the optimal position of loop detectors (system design).The system was developed using fuzzy logic concepts and calibrated using data from micro simulation experiments. Micro simulation approach is justified from the impossibility to get the requested data from on-field observations. The analysis has been focused on a two-way four-lane freeway basic segment; traffic flow variables (Density, Space Mean Speed and Flow Rate) were estimated with reference to the set of consecutive time intervals (one-minute long) belonging to the whole observation time period (3 hours). Simulated data were obtained running the model several times (10 runs) for each traffic volume class adopted in the analysis (1,000, 2,000, 3,000, 3,500 vehicles/hour), with different random number seeds. Calibration dataset was used to determine the knowledge base of each FIS using the open-source software FisPro, and the remaining data (validation dataset) to evaluate the performance of the system. The main finding of the study is that the detection system, despite its simplicity, shows excellent False Alarm Rate and satisfactory Mean Time To Detection
Driver gap-acceptance at roundabouts: a fuzzy logic approach
No full textGap-acceptance behaviour at unsignalized intersections has been extensively
studied in the field of traffic theory and engineering using
various methods. An interesting application of gap-acceptance theory
regards roundabouts. This paper describes the development of a model
of gap acceptance based on fuzzy system theory and specifically applicable
to traffic entering a roundabout. The study is based on data
derived from on site observations carried out at a roundabouts near
Padova, Italy
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