scholarly journals On the Effects of Various Measures of Performance Selections on Simulation Model Calibration Performance

2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Chen Wang ◽  
Chengcheng Xu

Objective. This paper examines the effects of various measures of performance (MOP) selections on simulation model calibration performance, in terms of reflecting actual traffic conditions and vehicle interactions. Method. Two intersections in Shanghai were selected for simulation model calibration, one for testing and another for validation. Three effective MOPs were utilized, including average travel time (i.e., time passing the intersection), average queue length, and vehicle headway distribution. The counts of three types of traffic conflicts (i.e., crossing, rear-end, and lane change) were used as safety MOPs. Those MOPs, as calibration objectives, were examined and compared. Results. The results of the testing site showed that different effective MOPs had their own advantages: average travel time appeared to be the best in reflecting lane change and rear-end conflicts while headway distribution performed the best consistency between simulated and actual crossing conflicts. Compared to the safety MOPs, average travel time and headway distribution still performed better, in terms of resulting in more similar simulated conflict metrics (e.g., TTC, PET) to actual ones. A multicriteria calibration strategy based on average travel time and headway distribution generally had better performances in reflecting actual traffic conditions and vehicle interactions than using any single effective or safety MOP. Similar results were found for the validation site. Conclusion. To simulate actual traffic conditions and vehicle interactions, multiple effective MOPs could be simultaneously considered for model calibration, instead of using safety MOPs.

2016 ◽  
Vol 40 (4) ◽  
pp. 7-14 ◽  
Author(s):  
Dodappaneni Abhigna ◽  
Sindhu Kondreddy ◽  
K. V. R. Ravi Shankar

Roundabouts are replacing conventional unsignalized intersections in many parts of the world (Polus and Shmueli, 1997). Capacity estimation is necessary for designing a new roundabout, to analyze and improve the existing roundabout facilities. There are several methods to estimate the capacity of the roundabout, but most of them are for homogeneous lane based traffic conditions and not applicable for mixed traffic conditions. This study tries to find out the applicability of the existing methods to mixed traffic conditions, identify the effect of vehicle composition, travel time and delay on capacity. In this study, data was collected from two roundabouts located in Mysore, Karnataka and Rajahmundry, Andhra Pradesh in India. Capacities for both the roundabouts are calculated using the existing methods and compared. VISSIM simulation model has been developed and analyzed for different vehicle compositions scenarios. It was observed that vehicle composition of the traffic influences the roundabout capacity. Since the entry capacity of a roundabout varies significantly with the vehicle composition of the traffic at the roundabout, it is necessary to incorporate this factor into the existing capacity estimation models.


2021 ◽  
Vol 13 (3) ◽  
pp. 1302
Author(s):  
Mateusz Szarata ◽  
Piotr Olszewski ◽  
Lesław Bichajło

Not many publications are available on using microsimulation models to analyze the feasibility of implementing the dynamic bus lane (DBL) concept. The paper presents the methodology and calibration process used for DBL modeling. For the selected four sites in Rzeszów (Poland), three options were analyzed: no bus lane, standard exclusive bus lane (XBL), and dynamic bus lane. The analyses were carried out using PTV Vissim software with an additional logic script to control the DBL activation. Simulation model parameters were calibrated using a genetic algorithm. The final assessment of individual options was based on the weighted average travel time for all transport modes. The results show that the dynamic bus lane could bring the same benefits to public transport and cause only a slight increase in travel times in private transport compared to XBL. The XBL solution, depending on the site, led to increasing the average travel time in private transport by 12% to 25%, while the dynamic bus lane increased by 1% to 12%. Weighted average travel time per person is proposed as the overall indicator of efficiency. Preliminary analyses show that the bus volume, bus occupancy, routing, and traffic conditions will affect the efficiency of the new solution.


Author(s):  
Alberto Portera ◽  
Marco Bassani

Current design manuals provide guidance on how to design exit ramps to facilitate driving operations and minimize the incidence of crashes. They also suggest that interchanges should be built along straight roadway sections. These criteria may prove ineffective in situations where there is no alternative to terminals being located along curved motorway segments. The paper investigates driving behavior along parallel deceleration curved terminals, with attention paid to the difference in impact between terminals having a curvature which is the same sign as the motorway segment (i.e., continue design), and those having an opposite curvature (i.e., reverse design). A driving simulation study was set up to collect longitudinal and transversal driver behavioral data in response to experimental factor variations. Forty-eight drivers were stratified on the basis of age and gender, and asked to drive along three randomly assigned circuits with off-ramps obtained by combining experimental factors such as motorway mainline curve radius (2 values), terminal length (3), curve direction (2), and traffic conditions (2). The motorway radius was found to be significant for drivers’ preferred speed when approaching the terminal. Terminal length and traffic volume do not have a significant impact on either longitudinal or transversal driver outputs. However, the effect of curve direction was found to be significant, notably for reverse terminals which do not compel drivers to select appropriate speeds and lane change positions. This terminal type can give rise to critical driving situations that should be considered at the design stage to facilitate the adoption of appropriate safety countermeasures.


2021 ◽  
pp. 1-12
Author(s):  
Zhe Li

 In order to improve the simulation effect of complex traffic conditions, based on machine learning algorithms, this paper builds a simulation model. Starting from the macroscopic traffic flow LWR theory, this paper introduces the process of establishing the original CTM mathematical model, and combines it with machine learning algorithms to improve it, and establishes the variable cell transmission model VCTM ordinary transmission, split transmission, and combined transmission mathematical expressions. Moreover, this paper establishes a road network simulation model to calibrate related simulation parameters. In addition, this paper combines the actual needs of complex traffic conditions analysis to construct a complex traffic simulation control model based on machine learning, and designs a hybrid microscopic traffic simulation system architecture to simulate all relevant factors of complex road conditions. Finally, this paper designs experiments to verify the performance of the simulation model. The research results show that the simulation control model of complex traffic conditions constructed in this paper has certain practical effects.


2021 ◽  
Vol 64 (11) ◽  
pp. 121-129
Author(s):  
Alexandru Cristian ◽  
Luke Marshall ◽  
Mihai Negrea ◽  
Flavius Stoichescu ◽  
Peiwei Cao ◽  
...  

In this paper, we describe multi-itinerary optimization (MIO)---a novel Bing Maps service that automates the process of building itineraries for multiple agents while optimizing their routes to minimize travel time or distance. MIO can be used by organizations with a fleet of vehicles and drivers, mobile salesforce, or a team of personnel in the field, to maximize workforce efficiency. It supports a variety of constraints, such as service time windows, duration, priority, pickup and delivery dependencies, and vehicle capacity. MIO also considers traffic conditions between locations, resulting in algorithmic challenges at multiple levels (e.g., calculating time-dependent travel-time distance matrices at scale and scheduling services for multiple agents). To support an end-to-end cloud service with turnaround times of a few seconds, our algorithm design targets a sweet spot between accuracy and performance. Toward that end, we build a scalable approach based on the ALNS metaheuristic. Our experiments show that accounting for traffic significantly improves solution quality: MIO finds efficient routes that avoid late arrivals, whereas traffic-agnostic approaches result in a 15% increase in the combined travel time and the lateness of an arrival. Furthermore, our approach generates itineraries with substantially higher quality than a cutting-edge heuristic (LKH), with faster running times for large instances.


2019 ◽  
Author(s):  
Nate Wessel ◽  
Steven Farber

Estimates of travel time by public transit often rely on the calculation of a shortest-path between two points for a given departure time. Such shortest-paths are time-dependent and not always stable from one moment to the next. Given that actual transit passengers necessarily have imperfect information about the system, their route selection strategies are heuristic and cannot be expected to achieve optimal travel times for all possible departures. Thus an algorithm that returns optimal travel times at all moments will tend to underestimate real travel times all else being equal. While several researchers have noted this issue none have yet measured the extent of the problem. This study observes and measures this effect by contrasting two alternative heuristic routing strategies to a standard shortest-path calculation. The Toronto Transit Commission is used as a case study and we model actual transit operations for the agency over the course of a normal week with archived AVL data transformed into a retrospective GTFS dataset. Travel times are estimated using two alternative route-choice assumptions: 1) habitual selection of the itinerary with the best average travel time and 2) dynamic choice of the next-departing route in a predefined choice set. It is shown that most trips present passengers with a complex choice among competing itineraries and that the choice of itinerary at any given moment of departure may entail substantial travel time risk relative to the optimal outcome. In the context of accessibility modelling, where travel times are typically considered as a distribution, the optimal path method is observed in aggregate to underestimate travel time by about 3-4 minutes at the median and 6-7 minutes at the \nth{90} percentile for a typical trip.


2021 ◽  
Author(s):  
Swapneel R. Kodupuganti ◽  
Sonu Mathew ◽  
Srinivas S. Pulugurtha

The rapid growth in population and related demand for travel during the past few decades has had a catalytic effect on traffic congestion, air quality, and safety in many urban areas. Transportation managers and planners have planned for new facilities to cater to the needs of users of alternative modes of transportation (e.g., public transportation, walking, and bicycling) over the next decade. However, there are no widely accepted methods, nor there is enough evidence to justify whether such plans are instrumental in improving mobility of the transportation system. Therefore, this project researches the operational performance of urban roads with heterogeneous traffic conditions to improve the mobility and reliability of people and goods. A 4-mile stretch of the Blue Line light rail transit (LRT) extension, which connects Old Concord Rd and the University of North Carolina at Charlotte’s main campus on N Tryon St in Charlotte, North Carolina, was considered for travel time reliability analysis. The influence of crosswalks, sidewalks, trails, greenways, on-street bicycle lanes, bus/LRT routes and stops/stations, and street network characteristics on travel time reliability were comprehensively considered from a multimodal perspective. Likewise, a 2.5-mile-long section of the Blue Line LRT extension, which connects University City Blvd and Mallard Creek Church Rd on N Tryon St in Charlotte, North Carolina, was considered for simulation-based operational analysis. Vissim traffic simulation software was used to compute and compare delay, queue length, and maximum queue length at nine intersections to evaluate the influence of vehicles, LRT, pedestrians, and bicyclists, individually and/or combined. The statistical significance of variations in travel time reliability were particularly less in the case of links on N Tryon St with the Blue Line LRT extension. However, a decrease in travel time reliability on some links was observed on the parallel route (I-85) and cross-streets. While a decrease in vehicle delay on northbound and southbound approaches of N Tryon St was observed in most cases after the LRT is in operation, the cross-streets of N Tryon St incurred a relatively higher increase in delay after the LRT is in operation. The current pedestrian and bicycling activity levels seemed insignificant to have an influence on vehicle delay at intersections. The methodological approaches from this research can be used to assess the performance of a transportation facility and identify remedial solutions from a multimodal perspective.


2014 ◽  
Vol 8 (1) ◽  
pp. 130-135
Author(s):  
S. Nithya ◽  
D. Senthurkumar ◽  
K. .Gunasekaran

The travel time studies are one of the most important measures used for evaluating the performance of road networks. The Global Positioning System (GPS) is a space-based system that provides position and time information in all weather conditions. GPS data could be used to obtain the values of traffic control delay, vehicle queue, average travel time and vehicle acceleration and deceleration at intersections.The task of estimation of delay becomes complex if it is performed for intersections carrying heterogeneous traffic and that to for over saturated conditions. Most of the urban signalized intersections are manually controlled during peak hours. GPS device fitted in a vehicle was run repeatedly during morning peak period and the period during which vehicles were allowed to cross the intersection was recorded with video graphic camera. The attempt to identify the control delay with the GPS data from the test vehicle while crossing manually operated major intersection is presented in this paper.


2015 ◽  
Vol 6 (2) ◽  
pp. 87-109 ◽  
Author(s):  
Renato Redondi ◽  
Paolo Malighetti ◽  
Stefano Paleari

The objective of this work is to evaluate the accessibility of European municipalities by air transport. We focus on travels that typically require the use of air transport by computing the quickest paths between any pair of municipalities separated by more than 500 km. The total travel time includes three components: i) travel by car or High Speed Train to reach the origin airport, ii) travel by air from the origin airport to the destination airport, including waiting times when no direct flight is available and iii) travel by car or High Speed Train from the destination airport to the municipality of destination. For each territorial unit, we calculate the population-weighted average travel time to reach any other municipality in Europe.


Author(s):  
Abhishek Jha ◽  

This study covers the freight vehicle, which clears the custom clearance process for Kathmandu and transports the same goods to Kathmandu from Birgunj. In this study average travel time for freight vehicles from Birgunj to Nagdhunga has been studied, along with the factors affecting the travel time from Birgunj to Nagdhunga. License plate monitoring method of the freight vehicles was done to find the average travel time and a questionnaire survey was done to identify the factors affecting travel time of the freight vehicle. The travel time from Birgunj to Nagdhunga is different for different types of, vehicle and good. The fastest average travel time is of fixed container of 40 feet size with 23.2 hours and longest average time is for fixed container of 20 feet size with 28.95 hours. The average travel time for non-degradable goods is 26.5 hours and for degradable goods is 22.38 hours. Major factors affecting the travel time are traffic congestion along the route, bad road condition along the route and hilly road with sharp bends, turns and grade.


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