Improving Traffic Flow Characteristics by Suppressing Shared Taxis Maneuvers

The sudden maneuver of shared taxi through lanes in order to pick-up and drop-off passengers and asking their destinations -due to lack of designated stop locations- may lead to disorder in traffic flow. The main hypothesis in this research was that shared taxis sudden maneuvers and lane changings have negative effects on traffic flow characteristics and subsequently, suppressing these maneuvers will improve traffic flow characteristics. For this purpose, a study was done on a path in the city of Isfahan in Iran. First the investigated path simulated without shared taxi sudden maneuvers and then the outputs of this simulation were compared to the real measurement data. By this comparison, some differences were observed. The shared taxis maneuvers were added to simulation to see if the observed difference can be lowered. By comparing the outputs of these two simulations to the real situation parameters, the considerable negative effect of this maneuvers was recognized. After observing of the mentioned maneuvers negative effect, an innovative solution – allocating a line to shared taxis and High Occupancy Vehicles - was added to suppress shared taxi maneuvers in order to improve traffic flow characteristics. By applying this scenario on current situation delay of traffic flow and delay of shared taxis decreased from 458.48 sec. to 383.01 sec. and from 506 sec. to 450 sec. respectively. Besides, traffic flow and the number of shared taxis increased from 11986 to 12980 and 663 to 718 vehicle per hour respectively

Distribution of traffic speed in different traffic conditions: an empirical study in Budapest

Fundamental diagram, a graphical representation of the relationship among traffic flow, speed, and density, has been the foundation of traffic flow theory and transportation engineering for many years. Underlying a fundamental diagram is the relation between traffic speed and density, which serves as the basis to understand system dynamics. Empirical observations of the traffic speed versus traffic density show a wide-scattering of traffic speeds over a certain level of density, which would form a speed distribution over a certain level of density. The main aim of the current research is to study on the distribution of traffic speed in different traffic conditions in the urban roads since the distribution of traffic speed is necessary for many traffic engineering applications including generating traffic in micro-simulation systems. To do so, the traffic stream is videotaped at various locations in the city of Budapest (Hungary). The recorded videos were analysed by traffic engineering experts and different traffic conditions were extracted from these recorded videos based on the predefined scenarios. Then their relevant speeds in that time interval were estimated with the so-called “g-estimator method” using the outputs of the available loop detectors among the videotaped locations. Then different parametric candidate distributions have been fitted to the speeds by Maximum Likelihood Estimation (MLE) method. Having fitted different parametric distributions to speed data, they were compared by three goodness-of-fit tests along with two penalized criteria (Akaike Information Criterion – AIC and Bayesian Information Criterion – BIC) in order to overcome the over-fitting problems. The results showed that the speed of traffic flow follows exponential, normal, lognormal, gamma, beta and chisquare distribution in the condition that traffic flow followed over-saturated congestion, under saturated flow, free flow, congestion, accelerated flow and decelerated flow respectively

Average Vehicles Length in Two-lane Urban Roads: A Case Study in Budapest

The length of vehicles is one of the most important parameters in traffic flow modeling and traffic control in many aspects such as speed estimation using the outputs of single loop detectors, length based vehicle classification and density estimation. In the current study, the average length of vehicles in two-lane urban roads of Budapest, Hungary has been measured by the means of manual observation method. Having measured the average vehicles length, their relevant effective vehicles length is manually calibrated within the day that is applicable to the local operating agencies. The obtained results showed that the local operating agencies have to set different effective vehicles length during the day in order to avoid possible estimation errors. Moreover, the heterogeneity of the traffic stream in the investigation area was evident from the results

Economic Investigation of a Public Transport Support Policy: A Case Study at Budapest

This paper analyses the effect of supporting the public transport policy based on intersection controlling with the aim of tram priority in Budapest, as a case study. The hypothesis related to this study was that the support of public transport is only viable when the marginal benefit of public transport is higher than the marginal cost of individual transport. Therefore, the real costs of this support for the society were estimated. This study revealed that by applying this policy, the waiting time at intersections and CO2 emission-related costs have increased by about 13.7% and 14.2%, respectively. Besides, the estimated monetary gain of tram users would be 17,800 euro on a daily level total by applying the mentioned policy

Theoretical Comparison of the Effects of Different Traffic Conditions on Urban Road Traffic Noise

Road traffic noise is one of the most relevant sources in the environmental noise pollution of the urban areas where dynamics of the traffic flow are much more complicated than uninterrupted traffic flows. It is evident that different traffic conditions would play the role in the urban traffic flow considering the dynamic nature of the traffic flow on one hand and presence of traffic lights, roundabouts, etc. on the other hand. The main aim of the current paper is to investigate the effect of different traffic conditions on urban road traffic noise. To do so, different traffic conditions have been theoretically generated by the Monte Carlo Simulation technique following the distribution of traffic speed in the urban roads. The “ASJ RTN-Model” has been considered as a base road traffic noise prediction model which would deal with different traffic conditions including steady and nonsteady traffic flow that would cover the urban traffic flow conditions properly. Having generated the vehicles speeds in different traffic conditions, the emitted noise (LWA) and subsequently the noise level at receiver (LA) were estimated by “ASJ RTN-Model.” Having estimated LWA and LA for each and every vehicle in each traffic condition and taking the concept of transient noise into account, the single event sound exposure levels (SEL) in different traffic conditions are calculated and compared to each other. The results showed that decelerated traffic flow had the lowest contribution, compared to congestion, accelerated flow, free flow, oversaturated congestion, and undersaturated flow by 16%, 14%, 12%, 12%, and 10%, respectively. Moreover, the distribution of emitted noise and noise level at receiver were compared in different traffic conditions. The results showed that traffic congestion had considerably the maximum peak compared to other traffic conditions which would highlight the importance of the range of generated noise in different traffic conditions

Distribution of traffic speed in different traffic conditions: an empirical study in Budapest

Fundamental diagram, a graphical representation of the relationship among traffic flow, speed, and density, has been the foundation of traffic flow theory and transportation engineering for many years. Underlying a fundamental diagram is the relation between traffic speed and density, which serves as the basis to understand system dynamics. Empirical observations of the traffic speed versus traffic density show a wide-scattering of traffic speeds over a certain level of density, which would form a speed distribution over a certain level of density. The main aim of the current research is to study on the distribution of traffic speed in different traffic conditions in the urban roads since the distribution of traffic speed is necessary for many traffic engineering applications including generating traffic in micro-simulation systems. To do so, the traffic stream is videotaped at various locations in the city of Budapest (Hungary). The recorded videos were analysed by traffic engineering experts and different traffic conditions were extracted from these recorded videos based on the predefined scenarios. Then their relevant speeds in that time interval were estimated with the so-called “g-estimator method” using the outputs of the available loop detectors among the videotaped locations. Then different parametric candidate distributions have been fitted to the speeds by Maximum Likelihood Estimation (MLE) method. Having fitted different parametric distributions to speed data, they were compared by three goodness-of-fit tests along with two penalized criteria (Akaike Information Criterion – AIC and Bayesian Information Criterion – BIC) in order to overcome the over-fitting problems. The results showed that the speed of traffic flow follows exponential, normal, lognormal, gamma, beta and chisquare distribution in the condition that traffic flow followed over-saturated congestion, under saturated flow, free flow, congestion, accelerated flow and decelerated flow respectively

Assessing the Possibility of Presenting a Semi-Stochastic Speed-Density Function

Underlying a fundamental diagram is a relation between traffic speed and density which roughly corresponds to drivers’ speed choices under varying car-following distances. Stochastic and deterministic models are mainly two different categories of speed-density models. The advantages of deterministic models are their mathematical simplicity and analytical tractability though their results will show just the average parameters. Although the stochastic models may represent more accurate results taking uncertainty into account, they are often hard to use and analytically not tractable. The aim of this paper is to investigate the possibility of presenting a model which is neither completely deterministic nor completely stochastic but easy to use and understand which incorporates different traffic conditions and speed distributions. Monte Carlo Method has been used to generate different speed distributions based on different traffic conditions and consequently generating their relevant densities. Surveying the relation between the mentioned speed distributions and the obtained densities kept the chance of presenting a model which is neither completely deterministic nor completely stochastic but easy to use and understand which incorporates different traffic conditions and speed distributions

Public Transport Accessibility: A Literature Review

Accessibility is one of the most important outcomes of the transportation system. Public transport can be more attractive by providing "Door to door mobility" and development of transportation services is an important factor of social quality. Public transport accessibility has gained vital importance in designing and evaluating the transit system in terms of mobility and sustainability. Apart from the transport system itself, public transport accessibility has the considerable impact on life satisfaction in the form of perceived accessibility. Moreover, researchers have revealed several impact and correlation of provision of public transport accessibility to the environment and daily life which would have a noticeable impact on public health and other aspects of public daily life. Furthermore, the correlation between public transport accessibility and job opportunities has attracted the researchers' attention in the literature. Also, public participation in social activities has been investigated based on public transport accessibility and their close connection has been revealed under the topic of social exclusion. In this paper, the available literature on public transport accessibility has been reviewed. As a conclusion, it should be highlighted that not just the performance of public transportation but its impact on other social aspects should be considered while planning the public transport facilities

Potential Effects of Automated Vehicles on Road Transportation: A Literature Review

Automated vehicles (AVs) are one of the emerging technologies that can perform the driving task themselves. The market penetration of AVs is expected to get growth in the close future. Therefore, it is crucial to have an overall clue on how they play the role in the road transportation sector. Automation might be assumed to have a beneficial impact on many aspects related to road transportation. The current paper attempts to investigate this rough assumption by reviewing the literature on the potential effects of automated vehicles on road transportation. A comprehensive look at the overall potential effects of automated vehicles will show the entire picture, and not just a cropped portion of that, to the researchers, decision makers, and practitioners and helps them to identify the negative and positive effects as well as challenges and uncertainties towards this new technology. In this paper, literature findings on the potential effects of automated vehicles on traffic flow, pedestrians mobility, travel demand and travel pattern, safety and security, and energy consumption and emissions are reviewed and discussed. According to the literature, it is concluded that AVs, as their market penetration increases, promisingly improve the capacity of a road network, eliminates human driver errors, and provide better mobility for groups of people who are currently facing travel-restriction conditions. However, the long-term effects of AVs especially on energy consumption, emission, pedestrian interaction, safety and security has uncertainty due to the complexity of predicting the future mobility pattern

Assessing the Possibility of Presenting a Semi-Stochastic Speed-Density Function

Underlying a fundamental diagram is a relation between traffic speed and density which roughly corresponds to drivers’ speed choices under varying car-following distances. Stochastic and deterministic models are mainly two different categories of speed-density models. The advantages of deterministic models are their mathematical simplicity and analytical tractability though their results will show just the average parameters. Although the stochastic models may represent more accurate results taking uncertainty into account, they are often hard to use and analytically not tractable. The aim of this paper is to investigate the possibility of presenting a model which is neither completely deterministic nor completely stochastic but easy to use and understand which incorporates different traffic conditions and speed distributions. Monte Carlo Method has been used to generate different speed distributions based on different traffic conditions and consequently generating their relevant densities. Surveying the relation between the mentioned speed distributions and the obtained densities kept the chance of presenting a model which is neither completely deterministic nor completely stochastic but easy to use and understand which incorporates different traffic conditions and speed distributions