Farhana Naznin

An empirical bayes safety evaluation of tram/streetcar signal and lane priority measures in Melbourne

ABSTRACT Objective: Streetcars/tram systems are growing worldwide, and many are given priority to increase speed and reliability performance in mixed traffic conditions. Research related to the road safety impact of tram priority is limited. This study explores the road safety impacts of tram priority measures including lane and intersection/signal priority measures. Method: A before–after crash study was conducted using the empirical Bayes (EB) method to provide more accurate crash impact estimates by accounting for wider crash trends and regression to the mean effects. Before–after crash data for 29 intersections with tram signal priority and 23 arterials with tram lane priority in Melbourne, Australia, were analyzed to evaluate the road safety impact of tram priority. Results: The EB before–after analysis results indicated a statistically significant adjusted crash reduction rate of 16.4% after implementation of tram priority measures. Signal priority measures were found to reduce crashes by 13.9% and lane priority by 19.4%. A disaggregate level simple before–after analysis indicated reductions in total and serious crashes as well as vehicle-, pedestrian-, and motorcycle-involved crashes. In addition, reductions in on-path crashes, pedestrian-involved crashes, and collisions among vehicles moving in the same and opposite directions and all other specific crash types were found after tram priority implementation. Conclusions: Results suggest that streetcar/tram priority measures result in safety benefits for all road users, including vehicles, pedestrians, and cyclists. Policy implications and areas for future research are discussed.

Safety impacts of platform tram stops on pedestrians in mixed traffic operation: A comparison group before-after crash study.

Tram stops in mixed traffic environments present a variety of safety, accessibility and transport efficiency challenges. In Melbourne, Australia the hundred year-old electric tram system is progressively being modernized to improve passenger accessibility. Platform stops, incorporating raised platforms for level entry into low floor trams, are being retro-fitted system-wide to replace older design stops. The aim of this study was to investigate the safety impacts of platform stops over older design stops (i.e. Melbourne safety zone tram stops) on pedestrians in the context of mixed traffic tram operation in Melbourne, using an advanced before-after crash analysis approach, the comparison group (CG) method. The CG method evaluates safety impacts by taking into account the general trends in safety and the unobserved factors at treatment and comparison sites that can alter the outcomes of a simple before-after analysis. The results showed that pedestrian-involved all injury crashes reduced by 43% after platform stop installation. This paper also explores a concern that the conventional CG method might underestimate safety impacts as a result of large differences in passenger stop use between treatment and comparison sites, suggesting differences in crash risk exposure. To adjust for this, a modified analysis explored crash rates (crash counts per 10,000 stop passengers) for each site. The adjusted results suggested greater reductions in pedestrian-involved crashes after platform stop installation: an 81% reduction in pedestrian-involved all injury crashes and 86% reduction in pedestrian-involved FSI crashes, both are significant at the 95% level. Overall, the results suggest that platform stops have considerable safety benefits for pedestrians. Implications for policy and areas for future research are explored.

Application of a random effects negative binomial model to examine tram-involved crash frequency on route sections in Melbourne, Australia

Safety is a key concern in the design, operation and development of light rail systems including trams or streetcars as they impose crash risks on road users in terms of crash frequency and severity. The aim of this study is to identify key traffic, transit and route factors that influence tram-involved crash frequencies along tram route sections in Melbourne. A random effects negative binomial (RENB) regression model was developed to analyze crash frequency data obtained from Yarra Trams, the tram operator in Melbourne. The RENB modelling approach can account for spatial and temporal variations within observation groups in panel count data structures by assuming that group specific effects are randomly distributed across locations. The results identify many significant factors effecting tram-involved crash frequency including tram service frequency (2.71), tram stop spacing (-0.42), tram route section length (0.31), tram signal priority (-0.25), general traffic volume (0.18), tram lane priority (-0.15) and ratio of platform tram stops (-0.09). Findings provide useful insights on route section level tram-involved crashes in an urban tram or streetcar operating environment. The method described represents a useful planning tool for transit agencies hoping to improve safety performance.

Exploring the impacts of factors contributing to tram-involved serious injury crashes on Melbourne tram routes

Previous research is limited regarding factors influencing tram-involved serious injury crashes. The aim of this study is to identify key vehicle, road, environment and driver related factors associated with tram-involved serious injury crashes. Using a binary logistic regression modelling approach, the following factors were identified to be significant in influencing tram-involved fatal crashes in Melbourne: tram floor height, tram age, season, traffic volume, tram lane priority and tram travel speed. Low floor trams, older trams, tram priority lanes and higher tram travelling speeds are more likely to increase tram-involved fatal crashes. Higher traffic volume decreases the likelihood of serious crashes. Fatal crashes are more likely to occur during spring and summer. Findings from this study may offer ideas for future research in the area of tram safety and help to develop countermeasures to prevent specific fatality types from occurring.

A meta-analysis and synthesis of public transport customer amenity valuation research

ABSTRACT This paper synthesises published research concerned with the valuation of public transport customer amenities. It includes normalisation of published values to equivalent terms, a meta-analysis of factors influencing these values, a review of valuation methods and issues faced in applying these methods, and an identification of gaps in knowledge. Some 57 separate research publications in this area were identified. Valuation methods adopted included stated preference, revealed preference, customer ratings, priority evaluator, maximum difference scaling and benefit/value transfer. Of these, stated preference was the most common published approach, however in practice benefit/value transfer is the most common method to apply values in project appraisal. Key issues associated with valuation include substantial variation in values (which are often context dependant) and the adoption of different units for expressing values, thereby limiting their transferability. Some 556 separate customer amenity values were identified relating to 97 separate amenity types. Almost all valuations were below 2 minutes of equivalent in-vehicle travel time value. Meta-analysis identified five types of significant predictors of values (R2 = 0.23): study location (Scandinavia), valuation method (stated preference), mode (train/metro), amenity group (access) and journey stage (boarding/alighting). Future research needs to disaggregate valuations by market segment.