The paradox of driving speed: two adverse effects on highway accident rate

Safety effects of automated section speed control on the Italian motorway network

INTRODUCTION

Automated Section Speed Control (ASSC) has been identified as an effective countermeasure to reduce speeds and improve speed limit compliance.

METHOD

An Empirical Bayes (EB) before-and-after study was performed in this research in order to evaluate the impact of the ASSC system on the expected crash frequency. The study was carried out on a sample of 125 ASSC sites of the Italian motorway network covering 1252 km, where a total of 21,721 crashes were recorded during a 10-year analysis period from 2004 to 2013.

RESULTS

Overall, the EB analysis estimated a significant 22% reduction in the expected crash frequency due to the implementation of the ASSC system. The analysis indicated that the effect is slightly larger on property damage only (PDO) crashes (-23%) than on fatal injury (FI) crashes (-18%) and that the highest reductions in crash frequency are expected for multi-vehicle FI crashes (-25%) and multi-vehicle PDO crashes (-31%). Furthermore, the results indicated that the ASSC system is more effective in reducing crash rates when traffic volume increases and it is therefore strongly recommended as a countermeasure to improve safety on high-traffic-volume motorway sections.

Preventing Emergency Vehicle Crashes: Status and Challenges of Human Factors Issues

OBJECTIVE

This study reports current status of knowledge and challenges associated with the emergency vehicle (police car, fire truck, and ambulance) crashes, with respect to the major contributing risk factors.

BACKGROUND

Emergency vehicle crashes are a serious nationwide problem, causing injury and death to emergency responders and citizens. Understanding the underlying causes of these crashes is critical for establishing effective strategies for reducing the occurrence of similar incidents.

METHOD

We reviewed the broader literature associated with the contributing factors for emergency vehicle crashes: peer-reviewed journal papers; and reports, policies, and manuals published by government agencies, universities, and research institutes.

RESULTS

Major risk factors for emergency vehicle crashes identified in this study were organized into four categories: driver, task, vehicle, and environmental factors. Also, current countermeasures and interventions to mitigate the hazards of emergency vehicle crashes were discussed, and new ideas for future studies were suggested.

CONCLUSION

Risk factors, control measures, and knowledge gaps relevant to emergency vehicle crashes were presented. Six research concepts are offered for the human factors community to address. Among the topics are emergency vehicle driver risky behavior carryover between emergency response and return from a call, distraction in emergency vehicle driving, in-vehicle driver assistance technologies, vehicle red light running, and pedestrian crash control.

APPLICATION

This information is helpful for emergency vehicle drivers, safety practitioners, public safety agencies, and research communities to mitigate crash risks. It also offers ideas for researchers to advance technologies and strategies to further emergency vehicle safety on the road.

Road Safety Impact of Increased Rural Highway Speed Limits in British Columbia, Canada

Control of vehicle speed is a central tenet of the safe systems approach to road safety. Most research shows that raising speed limits results in more injuries. Advocates of higher speed limits argue that this conclusion is based on older research, that traffic fatalities are decreasing despite higher speed limits, and that modern vehicles are able to safely travel at higher speeds. These arguments were used to justify raising speed limits on rural highways in British Columbia, Canada (July 2014). We used an interrupted time series approach to evaluate the impact of these speed limit increases on fatal crashes, auto-insurance claims, and ambulance dispatches for road trauma. Events were mapped to affected road segments (with increased speed limits) and to nearby road segments (within 5 km of an affected segment). Separate linear regression models were fitted for each outcome and road segment group. Models included gasoline sales to account for changes in vehicle travel. Our main findings were significant increases in (i) total insurance claims (43.0%; 95% Confidence Interval [CI] = 16.0–76.4%), (ii) injury claims (30.0%; 95% CI = 9.5–54.2%), and (iii) fatal crashes (118.0; 95% CI = 10.9–225.1%) on affected road segments. Nearby segments had a 25.7% increase in insurance claims (95% CI = 16.1–36.1%).

Self-monitoring of driving speed

In-vehicle data recorders (IVDR) have been found to facilitate safe driving and are highly valuable in accident analysis. Nevertheless, it is not easy to convince drivers to use them. Part of the difficulty is related to the "Big Brother" concern: installing IVDR impairs the drivers' privacy. The "Big Brother" concern can be mitigated by adding a turn-off switch to the IVDR. However, this addition comes at the expense of increasing speed variability between drivers, which is known to impair safety. The current experimental study examines the significance of this negative effect of a turn-off switch under two experimental settings representing different incentive structures: small and large fines for speeding. 199 students were asked to participate in a computerized speeding dilemma task, where they could control the speed of their "car" using "brake" and "speed" buttons, corresponding to automatic car foot pedals. The participants in two experimental conditions had IVDR installed in their "cars", and were told that they could turn it off at any time. Driving with active IVDR implied some probability of "fines" for speeding, and the two experimental groups differed with respect to the fine's magnitude, small or large. The results indicate that the option to use IVDR reduced speeding and speed variance. In addition, the results indicate that the reduction of speed variability was maximal in the small fine group. These results suggest that using IVDR with gentle fines and with a turn-off option maintains the positive effect of IVDR, addresses the "Big Brother" concern, and does not increase speed variance.

Re-visiting crash-speed relationships: A new perspective in crash modelling

Although speed is considered to be one of the main crash contributory factors, research findings are inconsistent. Independent of the robustness of their statistical approaches, crash frequency models typically employ crash data that are aggregated using spatial criteria (e.g., crash counts by link termed as a link-based approach). In this approach, the variability in crashes between links is explained by highly aggregated average measures that may be inappropriate, especially for time-varying variables such as speed and volume. This paper re-examines crash-speed relationships by creating a new crash data aggregation approach that enables improved representation of the road conditions just before crash occurrences. Crashes are aggregated according to the similarity of their pre-crash traffic and geometric conditions, forming an alternative crash count dataset termed as a condition-based approach. Crash-speed relationships are separately developed and compared for both approaches by employing the annual crashes that occurred on the Strategic Road Network of England in 2012. The datasets are modelled by injury severity using multivariate Poisson lognormal regression, with multivariate spatial effects for the link-based model, using a full Bayesian inference approach. The results of the condition-based approach show that high speeds trigger crash frequency. The outcome of the link-based model is the opposite; suggesting that the speed-crash relationship is negative regardless of crash severity. The differences between the results imply that data aggregation is a crucial, yet so far overlooked, methodological element of crash data analyses that may have direct impact on the modelling outcomes.

Modelling crash propensity of carshare members

Carshare systems are considered a promising solution for sustainable development of cities. To promote carsharing it is imperative to make them cost effective, which includes reduction in costs associated to crashes and insurance. To achieve this goal, it is important to characterize carshare users involved in crashes and understand factors that can explain at-fault and not-at fault drivers. This study utilizes data from GoGet carshare users in Sydney, Australia. Based on this study it was found that carshare users who utilize cars less frequently, own one or more cars, have less number of accidents in the past ten years, have chosen a higher insurance excess and have had a license for a longer period of time are less likely to be involved in a crash. However, if a crash occurs, carshare users not needing a car on the weekend, driving less than 1000km in the last year, rarely using a car and having an Australian license increases the likelihood to be at-fault. Since the dataset contained information about all members as well as not-at-fault drivers, it provided a unique opportunity to explore some aspects of quasi-induced exposure. The results indicate systematic differences in the distribution between the not-at-fault drivers and the carshare members based on the kilometres driven last year, main mode of travel, car ownership status and how often the car is needed. Finally, based on this study it is recommended that creating an incentive structure based on training and experience (based on kilometres driven), possibly tagged to the insurance excess could improve safety, and reduce costs associated to crashes for carshare systems.

The influence of economic incentives linked to road safety indicators on accidents: the case of toll concessions in Spain

The goal of this paper is to evaluate whether the incentives incorporated in toll highway concession contracts in order to encourage private operators to adopt measures to reduce accidents are actually effective at improving safety. To this end, we implemented negative binomial regression models using information about highway characteristics and accident data from toll highway concessions in Spain from 2007 to 2009. Our results show that even though road safety is highly influenced by variables that are not managed by the contractor, such as the annual average daily traffic (AADT), the percentage of heavy vehicles on the highway, number of lanes, number of intersections and average speed; the implementation of these incentives has a positive influence on the reduction of accidents and injuries. Consequently, this measure seems to be an effective way of improving safety performance in road networks.

Quasi-induced exposure: the choice of exposure metrics

The quasi-induced exposure method is widely used to estimate exposure and risks of different groups of drivers and vehicles. Essentially, this method assumes that non-at-fault or passive parties in two-vehicle collisions represent a random sample of the populations on the road. Most previous works have used the whole sample of collisions to estimate exposure. There has been some concern about possible biases in quasi-induced estimates. In this paper, we argue that (1) biases are mainly due to differences in accident avoidance abilities, speeds and injury risks, and (2) because the influence of these three factors on the probability of being non-at-fault is not the same for every crash type, differences may arise among non-at-fault populations, in which case some crash types would provide a more accurate estimate of exposure than others. We explore the direction of biases due to speed, accident avoidance ability and injury risk in four accident types: accidents between vehicles travelling on different lanes in two-way, two-lane undivided roads; accidents between vehicles travelling on different lanes on multilane roads; intersection accidents; and accidents between vehicles travelling on the same lane. Our analysis shows that more research would be needed concerning the effect of speed on head-on crashes on undivided roads, and crashes on multilane roads.

Motor vehicle driver death and high state maximum speed limits: 1991-1993

OBJECTIVE

To measure the association between motor vehicle crash (MVC) driver death and high state maximum speed limits.

METHODS

This study used a case-control design and assessed driver deaths from three major types of MVCs: non-collision; collision with motor vehicles in transit; and collision with stationary objects. The study period was 1991-1993. For each type of crash, case subject populations of fatally injured drivers were obtained from the U.S. Department of Transportation Fatality Analysis Reporting System. Four control subject populations, each associated with a different cause of death, were obtained from a U.S. national death certificate database (the causes of death were unintentional poisoning, non-Hodgkin lymphoma, drowning, and diabetes mellitus). Subjects were considered exposed if the state in which they crashed (for cases) or died (for controls) had a maximum speed limit greater than 55 mph. Each of the three case subject populations was compared against each of the four control subject populations. Odds ratios (ORs) were adjusted for age and gender.

RESULTS

For non-collision driver death, ORs ranged from 3.06 to 6.56, depending on the year and control group; all the ORs were significant. For collision with motor vehicles in transit driver death, ORs ranged from 1.12 to 2.22; all the ORs were significant. For collision with stationary objects driver death, ORs ranged from 0.87 to 1.83.

CONCLUSIONS

There was a moderately strong and significant association between non-collision driver death and high state maximum speed limits. For collision with motor vehicles in transit driver death, the association was somewhat milder but still consistent. For collision with stationary objects driver death, the presence of an association was unclear. During 1991-1993, the effects of high state maximum speed limits may have been different for different types of MVCs.

Association of intersection approach speed with driver characteristics, vehicle type and traffic conditions comparing urban and suburban areas

A mobile recording system, with integrated laser speed gun, video from CCD-cameras and auxiliary battery system, was used to observe driving behavior at an urban intersection and a suburban analog. After removal of instances of interference, 1538 driving behaviors were recorded. Multiple regression was then utilized to examine the factors affecting approaching speed. Speed limit violation was considered a dichotomous variable with two categories, violation and compliance. Binary logistic regression was also used to examine the risk of speeding as a function of covariates and interaction terms. The results of analysis revealed that the major contributing factors for approaching speed were site, rush-hour-status, traffic light condition, vehicle type and driver gender. In particular, light status was the highest contributor to speed. In addition, the results of logistic regression showed significant sites and rush-hour effects on speeding, with the risk of limit violation in the suburbs nearly six-fold that in urban areas. The relative risk of speeding for travelling in non-rush hours is three times higher than that for rush-hour. In terms of driver characteristics, male drivers under 55 years of age had the greatest speeding propensity in our sample. The results of the present study may provide meaningful information applicable to the design and operation of signalized intersections.