Freeway Safety Management: Case Studies in Italy (original) (raw)
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Modelling highway safety with data from chinese freeways
International Journal of Safety and Security Engineering, 2013
This paper presents a study on the development of safety performance function for freeways. Applying well-established statistical methods, we evaluated all variables that may affect freeway safety and selected the most signifi cant ones in the model. A variable analysis unit was utilized in this study to overcome the diffi culties in obtaining accurate crash and highway attribute data, as well as to improve the modelling quality. The results of this study provide much needed tools for freeway safety analysis.
Freeway safety as a function of traffic flow
Accident Analysis and Prevention, 2004
In this paper, we present evidence of strong relationships between traffic flow conditions and the likelihood of traffic accidents (crashes), by type of crash. Traffic flow variables are measured using standard monitoring devices such as single inductive loop detectors. The key traffic flow elements that affect safety are found to be mean volume and median speed, and temporal variations in volume and speed, where variations need to be distinguished by freeway lane. We demonstrate how these relationships can form the basis for a tool that monitors the real-time safety level of traffic flow on an urban freeway. Such a safety performance monitoring tool can also be used in cost-benefit evaluations of projects aimed at mitigating congestion, by comparing the levels of safety of traffic flows patterns before and after project implementation.
A Tool to Evaluate the Safety Effects of Changes in Freeway Traffic Flow
Journal of Transportation Engineering-asce, 2004
This research involves the development of a tool that can be used to assess the changes in traffic safety tendencies that result from changes in traffic flow. The tool uses data from single inductive loop detectors, converting 30-second observations of volume and occupancy for multiple freeway lanes into traffic flow regimes. Each regime has a specific pattern of crash types, which were determined through nonlinear multivariate analyses of over 1,000 crashes on freeways in Southern California. These analyses revealed ways in which differences in variances in speeds and volumes across lanes, as well as central tendencies of speeds and volumes, combine in complex ways to explain crash taxonomy. This research may provide the foundation to forecast the crash rates, in terms of vehicle miles of travel, for vehicles that are exposed to different traffic flow conditions.
Transportation Research Record: Journal of the Transportation Research Board, 2014
Safety performance functions (SPFs) are crash prediction models that quantitatively relate the expected number of crash counts with traffic volume and roadway and roadside geometries. SPFs help traffic safety officials identify unsafe locations and take appropriate counteractive measures. A study assembled crash and roadway geometry data of freeways (only Interstate highway data were used for this study) in Connecticut for development of SPFs. Models were estimated separately for single-vehicle and multivehicle crashes. Total and fatal and injury crashes were considered for model estimation for both single-vehicle and multivehicle crashes. For each crash category, three model estimations were performed with negative binomial distribution models with all geometric variables, with speed limit only, and with interaction between speed limit and roadway geometric variables. The best models were selected for each crash category through a comparison of goodness-of-fit measures (Akaike info...
Road Safety Analysis Using Operating Speeds: Case Studies in Southern Italy
Procedia - Social and Behavioral Sciences, 2012
Operating speeds, implemented by drivers, are noticeably higher than design speeds. Many authors demonstrated that these inconsistencies determine particular hazardous "black spots". In this study we propose a procedure (based on two models) to identify these "black spots". With this aim, four different road sections were selected in southern Italy (Salerno, Cosenza and Catanzaro). For each road section the accident data since 2004 to 2008 were collected. The good statistical fitting between the estimated parameters and those surveyed confirms the validity of the models and, at the same time, their reliability to define road safety improvements.
Probabilistic models of freeway safety performance using traffic flow data as predictors
Safety Science, 2008
In this paper we lay the groundwork for gauging the level of safety of any type of traffic flow on a freeway, based on data from single loop detectors; the procedure can be implemented wherever such data are monitored or simulated. Our analyses are based on loop detector data for each of the freeway lanes for a short period of time preceding teach of over 1700 accidents in our case study. This case study covers the six major freeways in Orange County, California, for a six-month period in 2001.Recognizing that loop detector data at a specific time and place cannot be converted to speed, because it is not possible to know effective vehicle length at such a detailed level (that is, the mix of long and short vehicles is unknown at a specific place for a short period of time), we avoid using any direct speed or density measures among the parameters. Rather, we employ explanatory parameters that include not only central tendencies (means and medians), but variations, and measures of systematic and synchronized traits that capture patterns in short period of loop detector data. Such patterns include breakdown from free flow to congested operations or recovery back to free flow, and differences in traffic conditions across lanes. In the analysis, we uncover an extensive set of statistical parameters that capture those aspects of traffic flow that are strongly related to accident potential. We demonstrate that the parameters can account for speed and density, even though these are not used directly. Moreover, the parameters account for important differences among the types of accidents that occur under different types of traffic flow.
Relating Safety and Capacity on Urban Freeways
Procedia - Social and Behavioral Sciences, 2011
This research sought to investigate the relationship between capacity and safety on freeway roadways in New Jersey. Using the State's roadway database, capacity was estimated for State roadways using the procedures in the Highway Capacity Manual. Crash prediction models were developed relating crashes and crash rates to the geometric variables used to estimate capacity as well as to capacity and v/c ratio. The research showed that as capacity increases the number of crashes and crash rate also increases. As v/c ratio increased the number of crashes and crash rate decreased indicating that congestion may result in reduced speeds and as a result a lower number of crashes and crash rates. The research points to the need to include operational parameters in performing road safety evaluations.
Comparison of Simulated Freeway Safety Performance with Observed Crashes
Transportation Research Record: Journal of the Transportation Research Board, 2009
This paper provides a link between simulated measures of safety performance and observed crash occurrence. Safety performance is expressed by using a crash potential index (CPI), established as a function of individual vehicle deceleration rates required to avoid a crash and of braking capabilities. Safety performance is compared with a sample of crashes observed on an instrumented segment of freeway. Three test results are reported: ( a) comparing safety performance in 1-min increments for a period 5 min before the precise crash time, ( b) comparing safety performance in 1-min increments over 5 min for matching crash and noncrash cases, and ( c) comparing average safety performance with observed crash rates for a 1-h period at the same site. The results of this study confirm that crashes tend to occur when measures of safety performance at a given site are higher than normal and that this measure increases with the approaching time to crash. The results provide basic evidence that ...
GJESRM, 2019
Attempts to apply more evidence-based methodologies to traffic safety have recently intensified. One such attempt is the Highway Safety Manual (HSM, 2010), which provides crash modification factors (CMFs) for a variety of roadway treatments. CMFs provide traffic practitioners with the resources to estimate the safety effects of various countermeasures. At the moment, the HSM does not provide CMFs for traffic flow parameters despite the significant differences in the number of crashes on segments with similar geometric parameters and average annual daily traffic (AADT). This study develops CMFs associated with change in hourly traffic flow conditions for 2008 through 2011 on three similar urban freeway segments in New Jersey using Empirical Bayes (EB) for before-after road safety studies. Specifically, this study focuses on traffic density expressed as level of service (LOS). Results show significantly that, as the LOS deteriorates from A to B, B to C, C to D, and D to E, the resultant CMFs are 0.673, 1.11, 0.865, and 1.452 respectively. This demonstrates that traffic flow parameters have some significant effect on roadway safety, therefore needs to be investigated further and eventually included in the future editions of the HSM.