Assessment of traffic noise level before and after freeway widening using traffic microsimulation and a refined classic noise prediction method

In this paper, a refined classic noise prediction method based on the VISSIM and FHWA noise prediction model is formulated to analyze the sound level contributed by traffic on the Nanjing Lukou airport connecting freeway before and after widening. The aim of this research is to (i) assess the traffic noise impact on the Nanjing University of Aeronautics and Astronautics (NUAA) campus before and after freeway widening, (ii) compare the prediction results with field data to test the accuracy of this method, (iii) analyze the relationship between traffic characteristics and sound level. The results indicate that the mean difference between model predictions and field measurements is acceptable. The traffic composition impact study indicates that buses (including mid-sizedtrucks) and heavy goods vehicles contribute a significant proportion of total noise power despite their low traffic volume. In addition, speed analysis offers an explanation for the minor differences in noise level across time periods. Future work will aim at reducing model error, by focusing on noise barrier analysis using the FEM/BEM method and modifying the vehicle noise emission equation by conducting field experimentation.

Dynamic load-sharing of longitudinal-connected air suspensions of a tri-axle semi-trailer

The effects of suspension parameters and driving conditions on dynamic load-sharing of longitudinal-connected air suspensions of a tri-axle semi-trailer are investigated in this study. A novel nonlinear model of a multi-axle semi-trailer with longitudinal-connected air suspensions is formulated based on fluid mechanics and thermodynamics and validated through test results. The effects of road surface conditions, driving speeds, air line inside diameter and connector inside diameter on dynamic load-sharing capability of the semi-trailer were analyzed in terms of load-sharing criteria. Simulation results indicate that, when larger air lines and connectors are employed, the DLSC (Dynamic Load-Sharing Coefficient) optimization ratio reaches its peak value when the road roughness is medium. The optimization ratio fluctuates in a complex manner as driving speed increases. The results also indicate that if the air line inside diameter is always assumed to be larger than the connector inside diameter, the influence of air line inside diameter on load-sharing is more significant than that of the connector inside diameter. The proposed approach can be used for further study of the influence of additional factors (such as vehicle load, static absolute air pressure and static height of air spring) on load-sharing and the control methods for multi-axle air suspensions with longitudinal air line.

Transit Capacity and Quality of Service Manual (TCQSM) applications for education

Relevant Education Contexts, Examples of TCQSM Applicability to Undergraduate Disciplines, Why Teach with the TCQSM?, TCQS Teaching Tools, Theory Curriculum Example: Examination Question, Problem Based Learning Example: Senior Year Semester Team Project, Honors Dissertation Example Topics, Where to From Here?

How transit route passenger load and distance can together influence quality of service

This paper investigates: - correlation between transit route passenger loading and travel distance - its implications on quality of service (QoS) and resource productivity. It uses Automatic Fare Collection (AFC) data across a weekday on a premium bus line in Brisbane, Australia. A composite load-distance factor is proposed as a new measure for profiling transit route on-board passenger comfort QoS. Understanding these measures and their correlation is important for planning, design, and operational activities.

Brisbane Macroscopic Fundamental Diagram : empirical findings on network partitioning and incident detection

The Macroscopic Fundamental Diagram (MFD) relates space-mean density and flow, and the existence with dynamic features was confirmed in congested urban network in downtown Yokohama with real data set. Since the MFD represents the area-wide network traffic performances, studies on perimeter control strategies and an area traffic state estimation utilizing the MFD concept has been reported. However, limited works have been reported on real world example from signalised arterial network. This paper fuses data from multiple sources (Bluetooth, Loops and Signals) and develops a framework for the development of the MFD for Brisbane, Australia. Existence of the MFD in Brisbane arterial network is confirmed. Different MFDs (from whole network and several sub regions) are evaluated to discover the spatial partitioning in network performance representation. The findings confirmed the usefulness of appropriate network partitioning for traffic monitoring and incident detections. The discussion addressed future research directions

Establishing definitions and modeling public transport travel time variability

Public transport travel time variability (PTTV) is essential for understanding deteriorations in the reliability of travel time, optimizing transit schedules and route choices. This paper establishes key definitions of PTTV in which firstly include all buses, and secondly include only a single service from a bus route. The paper then analyses the day-to-day distribution of public transport travel time by using Transit Signal Priority data. A comprehensive approach using both parametric bootstrapping Kolmogorov-Smirnov test and Bayesian Information Creation technique is developed, recommends Lognormal distribution as the best descriptor of bus travel time on urban corridors. The probability density function of Lognormal distribution is finally used for calculating probability indicators of PTTV. The findings of this study are useful for both traffic managers and statisticians for planning and researching the transit systems.

Transit passenger segmentation using travel regularity mined from Smart Card transactions data

Transit passenger market segmentation enables transit operators to target different classes of transit users to provide customized information and services. The Smart Card (SC) data, from Automated Fare Collection system, facilitates the understanding of multiday travel regularity of transit passengers, and can be used to segment them into identifiable classes of similar behaviors and needs. However, the use of SC data for market segmentation has attracted very limited attention in the literature. This paper proposes a novel methodology for mining spatial and temporal travel regularity from each individual passenger’s historical SC transactions and segments them into four segments of transit users. After reconstructing the travel itineraries from historical SC transactions, the paper adopts the Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm to mine travel regularity of each SC user. The travel regularity is then used to segment SC users by an a priori market segmentation approach. The methodology proposed in this paper assists transit operators to understand their passengers and provide them oriented information and services.

Effectiveness of pilot car operations in reducing speeds in a long-term rural highway work zone

Pilot cars are used in one-lane two-way work zones to guide traffic and keep their speeds within posted limits. While many studies have examined the effectiveness of measures to reduce vehicle speeds in work zones, little is known about the reductions achievable through the use of pilot cars. This paper examines the effectiveness of a pilot car in reducing travel speeds in a rural highway work zone in Queensland, Australia. Analysis of speed data covering a period of five days showed that a pilot car reduced average speeds at the treatment location, but not downstream. The proportion of vehicles speeding through the activity area was also reduced, particularly those traveling at 10 km/h or more above the posted limit. Motorists were more likely to speed during the day, under a 40 kh/h limit, when traffic volumes were higher and when there were fewer vehicles in the traffic stream. Medium vehicles were less likely to speed in the presence of a pilot car than light vehicles. To maximize these benefits, it is necessary to ensure that the pilot car itself is not speeding.

Bike share's impact on car use : evidence from the United States, Great Britain, and Australia

There are currently more than 400 cities operating bike share programs. Purported benefits of bike share programs include flexible mobility, physical activity, reduced congestion, emissions and fuel use. Implicit or explicit in the calculation of program benefits are assumptions regarding the modes of travel replaced by bike share journeys. This paper examines the degree to which car trips are replaced by bike share, through an examination of survey and trip data from bike share programs in Melbourne, Brisbane, Washing, D.C., London, and Minneapolis/St. Paul. A secondary and unique component of this analysis examines motor vehicle support services required for bike share fleet rebalancing and maintenance. These two components are then combined to estimate bike share’s overall contribution to changes in vehicle kilometres traveled. The results indicate that the estimated mean reduction in car use due to bike share is at least twice the distance covered by operator support vehicles, with the exception of London, in which the relationship is reversed, largely due to a low car mode substitution rate. As bike share programs mature, evaluation of their effectiveness in reducing car use may become increasingly important. This paper reveals that by increasing the convenience of bike share relative to car use and by improving perceptions of safety, the capacity of bike share programs to reduce vehicle trips and yield overall net benefits will be enhanced. Researchers can adapt the analytical approach proposed in this paper to assist in the evaluation of current and future bike share programs.

Decision fusion from parts and samples for robust iris recognition

Fusion techniques can be used in biometrics to achieve higher accuracy. When biometric systems are in operation and the threat level changes, controlling the trade-off between detection error rates can reduce the impact of an attack. In a fused system, varying a single threshold does not allow this to be achieved, but systematic adjustment of a set of parameters does. In this paper, fused decisions from a multi-part, multi-sample sequential architecture are investigated for that purpose in an iris recognition system. A specific implementation of the multi-part architecture is proposed and the effect of the number of parts and samples in the resultant detection error rate is analysed. The effectiveness of the proposed architecture is then evaluated under two specific cases of obfuscation attack: miosis and mydriasis. Results show that robustness to such obfuscation attacks is achieved, since lower error rates than in the case of the non-fused base system are obtained.

Bike share's impact on car use : evidence from the United States, Great Britain, and Australia

There are currently more than 700 cities operating bike share programs. Purported benefits of bike share include flexible mobility, physical activity, reduced congestion, emissions and fuel use. Implicit or explicit in the calculation of program benefits are assumptions regarding the modes of travel replaced by bike share journeys. This paper examines the degree to which car trips are replaced by bike share, through an examination of survey and trip data from bike share programs in Melbourne, Brisbane, Washington, D.C., London, and Minneapolis/St. Paul. A secondary and unique component of this analysis examines motor vehicle support services required for bike share fleet rebalancing and maintenance. These two components are then combined to estimate bike share’s overall contribution to changes in vehicle kilometers traveled. The results indicate an estimated reduction in motor vehicle use due to bike share of approx. 90,000 km per annum in Melbourne and Minneapolis/St. Paul and 243,291 km for Washington, D.C. London’s bike share program however recorded an additional 766,341 km in motor vehicle use. This was largely due to a low car mode substitution rate and substantial truck use for rebalancing of bicycles. As bike share programs mature, evaluation of their effectiveness in reducing car use may become increasingly important. Researchers can adapt the analytical approach proposed in this paper to assist in the evaluation of current and future bike share programs.