Evaluation of Raised Safety Platforms (RSP) On-Road Safety Performance

A Raised Safety Platform (RSP) is a relatively new physical road safety intervention at major intersections. They aim to enhance road user safety by reducing vehicle speeds at intersections using an acute vertical deflection to the vehicle path. This study measured the change in speed at selected high-volume intersections treated with an RSP. It was a 12-month study based on a controlled before-and-after-treatment design, with speed and other measures assessed at six treated and five control intersections. Statistically significant and meaningful reductions in speeds were observed given the treatment and adjusted for the control group. A 15.6% reduction in the central tendency of speed was found overall. The odds of a vehicle exceeding nominal Safe System speeds of 30 km/h, 40 km/h, and 50 km/h also reduced markedly, with greater reductions observed at the higher speed thresholds (46%, 69%, and 80%, respectively). The change in speed corresponded to an estimated aggregate-level injurious crash-reduction benefit of around 26% and a reduction in the likelihood of a serious injury given a crash of between 38% to 57% depending on the crash type. It was concluded that RSP is an effective Safe System treatment to reduce speeds at major intersections to levels similar that at roundabouts. The results suggest that well designed RSPs at signalised intersections are an effective and sustainable Safe System treatment.

Analysis of Crash Frequency and Crash Severity in Thailand: Hierarchical Structure Models Approach

Currently, research on the development of crash models in terms of crash frequency on road segments and crash severity applies the principles of spatial analysis and heterogeneity due to the methods’ suitability compared with traditional models. This study focuses on crash severity and frequency in Thailand. Moreover, this study aims to understand crash frequency and fatality. The result of the intra-class correlation coefficient found that the spatial approach should analyze the data. The crash frequency model’s best fit is a spatial zero-inflated negative binomial model (SZINB). The results of the random parameters of SZINB are insignificant, except for the intercept. The crash frequency model’s significant variables include the length of the segment and average annual traffic volume for the fixed parameters. Conversely, the study finds that the best fit model of crash severity is a logistic regression with spatial correlations. The variances of random effect are significant such as the intersection, sideswipe crash, and head-on crash. Meanwhile, the fixed-effect variables significant to fatality risk include motorcycles, gender, non-use of safety equipment, and nighttime collision. The paper proposes a policy applicable to agencies responsible for driver training, law enforcement, and those involved in crash-reduction campaigns.

Safety Evaluation of Median U-Turn Crossover-Based Intersections

Alternative innovative designs for intersections were defined to enhance traffic operation and safety. Median U-turn (MUT) and restricted crossing U-turn (RCUT) intersections are among the types of alternative intersections that enable drivers to make left-turn movements at median U-turn crossovers downstream of the main intersection. Recently, municipalities and transport agencies have tended to implement these types of intersections. However, their effectiveness in crash reduction has not been adequately determined in previous studies. This is because of the limited number of alternative intersections that were considered in these studies. In addition, there was no consideration for the unusual new geometric design of these intersections. In this study, a safety evaluation was conducted while considering the new intersection-related areas at MUT and RCUT intersections to clarify and quantify their effectiveness in crash reduction. This study considered 73 MUT and 12 RCUT intersections. Two types of MUT intersections were considered in this study. Crash modification factors for MUT and RCUT intersections were estimated by using before–after and cross-sectional methods. The results indicated that MUT and RCUT intersections are safer than conventional intersections. MUT intersections are effective in reducing total, property damage only (PDO), rear-end, and opposite-direction sideswipe crashes, although they significantly increase single-vehicle and non-motorized crashes. RCUT intersections are effective in reducing fatal-and-injury, injury, head-on, and angle crashes. Findings of this research provide clear evaluation for decision makers about the effectiveness of MUT and RCUT intersections in crash reduction.

Identification of Vehicle-Pedestrian Collision Hotspots at the Micro-Level Using Network Kernel Density Estimation and Random Forests: A Case Study in Shanghai, China

The improvement of pedestrian safety plays a crucial role in developing a safe and friendly walking environments, which can contribute to urban sustainability. A preliminary step in improving pedestrian safety is to identify hazardous road locations for pedestrians. This study proposes a framework for the identification of vehicle-pedestrian collision hot spots by integrating the information about both the likelihood of the occurrence of vehicle-pedestrian collisions and the potential for the reduction in vehicle-pedestrian crashes. First, a vehicle-pedestrian collision density surface was produced via network kernel density estimation. By assigning a threshold value, possible vehicle-pedestrian hot spots were identified. To obtain the potential for vehicle-pedestrian collision reduction, random forests was employed to model the density with a set of variables describing vehicle and pedestrian flows. The potential for crash reduction was then measured as the difference between the observed vehicle-pedestrian crash density and the prediction produced by the random forests models. The final hotspots were determined by excluding those with a crash reduction value of no more than zero. The method was applied to the identification of hazardous road locations for pedestrians in a district in Shanghai, China. The result indicates that the method is useful for decision-making support.

Safety Effects of Flashing Yellow Arrows Used in Protected Permitted Phasing: Comparison of Full Bayes and Empirical Bayes Results

Using the flashing yellow arrow (FYA) signal indication for the permissive portion of protected-permissive left-turn (PPLT) phasing has become an increasingly popular treatment for left-turn signals as drivers are believed to understand the FYA better than the traditional circular green indication. A before-and-after safety evaluation of deploying FYA at PPLT signals at 28 intersections in Virginia was conducted. Each of the study intersections had FYA for the permitted portion of the phase on at least one left-turn approach. The focus was on left-turns that operated in the protected-permissive mode (with circular green indication for the permissive portion) before being converted to PPLT operations with the FYA indication for the permissive portion (PPLT-FYA). Crash records from before and after the activation of FYA were compared using both the full Bayes and empirical Bayes approaches. The results indicate that using the FYA signal indication instead of the circular green indication had a statistically significant effect in reducing overall frequency and severity of crashes. For the intersections studied in this research, total crashes reduced by 12% following conversion from PPLT to PPLT–FYA. The results also indicated that the full Bayes approach to safety effectiveness evaluation can, at a minimum, provide similar results to the well-established empirical Bayes approach. The 95% credible intervals for the expected crash reduction rates estimated with the full Bayes method were generally narrow, suggesting a good degree of confidence in the estimates.

Driver Performance in a Cooperative Adaptive Cruise Control String

Cooperative Adaptive Cruise Control (CACC) has been proposed as a method to increase highway capacity and possibly enhance safety. Two experiments were conducted in a driving simulator to verify that drivers with CACC would effectively monitor the system’s longitudinal control and override the system in the event that greater braking authority was needed than the system was designed to provide. In the first experiment, the emergency response of drivers with the CACC was compared with that of drivers who manually controlled following distance within a string of vehicles. The CACC group experienced markedly fewer crashes and had longer mean time-to-collision. The second experiment examined whether the CACC safety benefit was the result of the CACC system’s limited automatic braking authority, an auditory alarm, or both. The results suggest that both auto-braking and an auditory alarm are necessary to achieve a crash reduction benefit, although the alarm alone may promote less severe collisions.