Young, inexperienced and on the road: Do novice drivers comply with road rules?

Young novice drivers are at considerable risk of injury and fatality, particularly when they first drive independently. Graduated Driver Licensing (GDL) has been introduced in numerous jurisdictions to allow more driving experience in conditions of reduced risk and increasing driving privileges over a longer duration. Queensland, Australia, enhanced GDL July 2007. Learners must record 100 hours in a logbook (10 hours at night) over 1 year, no mobile handsfree/loudspeaker by driver or any passenger. Provisional 1 (P1) drivers must not carry 2 or more peer passengers 11pm - 5am, no mobile handsfree/loudspeaker by any passenger. Self-reported compliance with new GDL and general road rules has not been examined.

On the relationships between self-reported bicycling injuries and perceived risk among cyclists in Queensland, Australia

The focus of governments on increasing active travel has motivated renewed interest in cycling safety. Bicyclists are up to 20 times more likely to be involved in serious injury crashes than drivers so understanding the relationship among factors in bicyclist crash risk is critically important for identifying effective policy tools, for informing bicycle infrastructure investments, and for identifying high risk bicycling contexts. This study aims to better understand the complex relationships between bicyclist self reported injuries resulting from crashes (e.g. hitting a car) and non-crashes (e.g. spraining an ankle) and perceived risk of cycling as a function of cyclist exposure, rider conspicuity, riding environment, rider risk aversion, and rider ability. Self reported data from 2,500 Queensland cyclists are used to estimate a series of seemingly unrelated regressions to examine the relationships among factors. The major findings suggest that perceived risk does not appear to influence injury rates, nor do injury rates influence perceived risks of cycling. Riders who perceive cycling as risky tend not to be commuters, do not engage in group riding, tend to always wear mandatory helmets and front lights, and lower their perception of risk by increasing days per week of riding and by increasing riding proportion on bicycle paths. Riders who always wear helmets have lower crash injury risk. Increasing the number of days per week riding tends to decrease both crash injury and non crash injury risk (e.g. a sprain). Further work is needed to replicate some of the findings in this study.

Transit line passenger transmission and productiveness under high load conditions

Deterministic transit capacity analysis applies to planning, design and operational management of urban transit systems. The Transit Capacity and Quality of Service Manual (1) and Vuchic (2, 3) enable transit performance to be quantified and assessed using transit capacity and productive capacity. This paper further defines important productive performance measures of an individual transit service and transit line. Transit work (p-km) captures the transit task performed over distance. Passenger transmission (p-km/h) captures the passenger task delivered by service at speed. Transit productiveness (p-km/h) captures transit work performed over time. These measures are useful to operators in understanding their services’ or systems’ capabilities and passenger quality of service. This paper accounts for variability in utilized demand by passengers along a line and high passenger load conditions where passenger pass-up delay occurs. A hypothetical case study of an individual bus service’s operation demonstrates the usefulness of passenger transmission in comparing existing and growth scenarios. A hypothetical case study of a bus line’s operation during a peak hour window demonstrates the theory’s usefulness in examining the contribution of individual services to line productive performance. Scenarios may be assessed using this theory to benchmark or compare lines and segments, conditions, or consider improvements.

Transit line passenger transmission and productiveness under high load conditions : presentation

Transit Capacity Analysis critical to urban system Planning Design, Operation Productive Performance Analysis not so well detailed This study extends TRB’s & Vuchic’s work in this area

Airport ground transportation policies and the future of rail connections at US airports

Airports are currently being pressured to operate in a more environmentally-sensitive manner; as a response, airports have integrated environmental policies into their operations. However, environmental concerns regarding automobile traffic and related emissions have yet to be addressed. While the automobile is the dominant air passenger ground transportation mode at US airports, services facilitating automobile usage including public parking and car rentals are a major airport revenue source. Less than 20 US hub airports have direct access to rail-based transportation modes. New rail transportation projects serving additional airports are either being consideration or under construction. Regardless of whether an airport has direct access to rail-based transportation modes, the air passenger ground transportation modal split at US airports remain low in comparison to those in Asia and Europe. The high cost of providing additional US airports with direct rail connections in an era of severe governmental budgetary cutbacks is making the “build it and they will come” mindset untenable. Governmental policies are but one factor determining whether programs increasing transit usage results in automobile traffic reductions and related emissions. This study reveals that a significant percentage of the busiest US airports do not have policies fostering increases in the air passenger ground transportation modal split. A case study of one US airport is presented that has successfully adopted a transit first policy to achieve a high air passenger ground transportation modal split and facilitate the availability of rail-based transportation services.

Intraurban rail access : Policy implications of five revealed perspectives from a Q-sorting exercise in three Australian cities

This project advances current understanding of intra-urban rail passengers and their travel experiences in order to help rail industry leaders tailor policy approaches to fit specific, relevant segments of their target population. Using a Q sorting technique and cluster analysis, our preliminary research identified five perspectives occurring in a small sample of rail passengers, who varied in their frequency and location of rail travel as well as certain socio-demographic characteristics. Revealed perspectives (named to capture the gist of their content) included: ‘Rail Travel is About the Destination, Not the Journey’; ‘Despite Challenges, Public Transport is Still the Best Option’; ‘Rail Travel is Fine’; ‘Rail Travel? So Far, So Good’; and ‘Bad Taste for Rail Travel’. This paper discusses each of the perspectives in detail, and considers them in terms of tailored policy implications. An overarching finding from this study is that improving railway travel ‘access’ requires attention to physical, psychological, financial, and social facets of accessibility. For example, designing waiting areas to be more socially functional and comfortable has the potential to increase ridership by addressing social forms of access, decreasing perceived wait times, and making time at the station feel like time well spent. Even at this preliminary stage, the Q sorting technique promises to provide a valuable, holistic albeit fine-grained analysis of passenger attitudes and experiences that will assist industry efforts to increase ridership.

High load transit line passenger transmission and productiveness efficiencies

Performance of urban transit systems may be quantified and assessed using transit capacity and productive capacity in planning, design and operational management activities. Bunker (4) defines important productive performance measures of an individual transit service and transit line, which are extended in this paper to quantify efficiency and operating fashion of transit services and lines. Comparison of a hypothetical bus line’s operation during a morning peak hour and daytime hour demonstrates the usefulness of productiveness efficiency and passenger transmission efficiency, passenger churn and average proportion line length traveled to the operator in understanding their services’ and lines’ productive performance, operating characteristics, and quality of service. Productiveness efficiency can flag potential pass-up activity under high load conditions, as well as ineffective resource deployment. Proportion line length traveled can directly measure operating fashion. These measures can be used to compare between lines/routes and, within a given line, various operating scenarios and time horizons to target improvements. The next research stage is investigating within-line variation using smart card passenger data and field observation of pass-ups. Insights will be used to further develop practical guidance to operators.

High load transit line passenger transmission and productiveness efficiencies

Performance of urban transit systems may be quantified and assessed using transit capacity and productive capacity in planning, design and operational management activities. Bunker (4) defines important productive performance measures of an individual transit service and transit line, which are extended in this paper to quantify efficiency and operating fashion of transit services and lines. Comparison of a hypothetical bus line’s operation during a morning peak hour and daytime hour demonstrates the usefulness of productiveness efficiency and passenger transmission efficiency, passenger churn and average proportion line length traveled to the operator in understanding their services’ and lines’ productive performance, operating characteristics, and quality of service. Productiveness efficiency can flag potential pass-up activity under high load conditions, as well as ineffective resource deployment. Proportion line length traveled can directly measure operating fashion. These measures can be used to compare between lines/routes and, within a given line, various operating scenarios and time horizons to target improvements. The next research stage is investigating within-line variation using smart card passenger data and field observation of pass-ups. Insights will be used to further develop practical guidance to operators.

Planning for transit system reliability using productive performance and risk assessment

Urban transit system performance may be quantified and assessed using transit capacity and productive capacity for planning, design and operational management. Bunker (4) defines important productive performance measures of an individual transit service and transit line. Transit work (p-km) captures transit task performed over distance. Transit productiveness (p-km/h) captures transit work performed over time. This paper applies productive performance with risk assessment to quantify transit system reliability. Theory is developed to monetize transit segment reliability risk on the basis of demonstration Annual Reliability Event rates by transit facility type, segment productiveness, and unit-event severity. A comparative example of peak hour performance of a transit sub-system containing bus-on-street, busway, and rail components in Brisbane, Australia demonstrates through practical application the importance of valuing reliability. Comparison reveals the highest risk segments to be long, highly productive on street bus segments followed by busway (BRT) segments and then rail segments. A transit reliability risk reduction treatment example demonstrates that benefits can be significant and should be incorporated into project evaluation in addition to those of regular travel time savings, reduced emissions and safety improvements. Reliability can be used to identify high risk components of the transit system and draw comparisons between modes both in planning and operations settings, and value improvement scenarios in a project evaluation setting. The methodology can also be applied to inform daily transit system operational management.