Harry Lahrmann

Pay as You Speed, ISA with incentives for not speeding: A case of test driver recruitment

The Intelligent Speed Adaptation (ISA) project we describe in this article is based on Pay as You Drive principles. These principles assume that the ISA equipment informs a driver of the speed limit, warns the driver when speeding and calculates penalty points. Each penalty point entails the reduction of a 30% discount on the drivers car insurance premium, which therefore produced the name, Pay as You Speed. The ISA equipment consists of a GPS-based On Board Unit with a mobile phone connection to a web server. The project was planned for a three-year test period with 300 young car drivers, but it never succeeded in recruiting that number of drivers. After several design changes, the project eventually went forward with 153 test drivers of all ages. This number represents approximately one thousandth of all car owners in the proving ground of North Jutland in Denmark. Furthermore the project was terminated before its scheduled closing date. This article describes the project with an emphasis on recruitment efforts and the projects progress. We include a discussion of possible explanations for the failure to recruit volunteers for the project and reflect upon the general barriers to using ISA with ordinary drivers.

Safety effects of permanent running lights for bicycles: A controlled experiment

Making the use of daytime running lights mandatory for motor vehicles is generally documented to have had a positive impact upon traffic safety. Improving traffic safety for bicyclists is a focal point in the road traffic safety work in Denmark. In 2004 and 2005 a controlled experiment including 3845 cyclists was carried out in Odense, Denmark in order to examine, if permanent running lights mounted to bicycles would improve traffic safety for cyclists. The permanent running lights were mounted to 1845 bicycles and the accident rate was recorded through 12 months for this treatment group and 2000 other bicyclists, the latter serving as a control group without bicycle running lights. The safety effect of the running lights is analysed by comparing incidence rates - number of bicycle accidents recorded per man-month - for the treatment group and the control group. The incidence rate, including all recorded bicycle accidents with personal injury to the participating cyclist, is 19% lower for cyclists with permanent running lights mounted; indicating that the permanent bicycle running light significantly improves traffic safety for cyclists. The study shows that use of permanent bicycle running lights reduces the occurrence of multiparty accidents involving cyclists significantly. In the study the bicycle accidents were recorded trough self-reporting on the Internet. Possible shortcomings and problems related to this accident recording are discussed and analysed.

Intelligent speed adaptation in company vehicles

This paper describes an intelligent speed adaptation project for company vehicles. The intelligent speed adaptation function in the project is both information and incentive, which means that the intelligent speed adaptation equipment gives a warning as well as penalty points if the driver is speeding. Each month the driver with that monthpsilas fewest points wins an award. The paper presents results concerning speed attitude on the first three of a planned 12 months test period. In all 26 vehicles and 51 drivers from six companies participate in the project. The key result is that speeding is reduced from 18.7% to 7.4% on urban roads with a speed limit of 50 km/h while it is reduced from 18.9% to 4.7% on rural roads with a speed limit of 80 km/h.

Reliability of Bluetooth Technology for Travel Time Estimation

A unique Bluetooth-enabled device may be detected several times or not at all when it passes a sensor location. This depends mainly on the strength and speed of a transmitting device, discovery procedure, location of the device relative to the Bluetooth sensor, the Bluetooth sensors ping cycle (0.1 s), the size and shape of the sensors detection zone, and the time span for which the Bluetooth-enabled device is within the detection zone. The influences of size of Bluetooth sensor detection zones and Bluetooth discovery procedure on multiple detection events have been mentioned in previous research. However, their corresponding impacts on accuracy and reliability of estimated travel time have not been evaluated. In this study, a controlled field experiment is conducted to collect both Bluetooth and global positioning system (GPS) data for 1000 trips to be used as the basis for evaluation. Data obtained by GPS logger are used to calculate actual travel time, referred to as ground truth, and to geo-code the Bluetooth detection events. In this setting, reliability is defined as the percentage of devices captured per trip during the experiment. It is found that, on average, Bluetooth-enabled devices will be detected 80% of the time while passing a sensor location. The impact of location ambiguity caused by the size of the detection zone is evaluated using geo-coded Bluetooth data. Results show that more than 80% of the detection events are recorded within the range of 100 m from the sensor center line. It is also shown that short-range antennas detect Bluetooth-enabled devices in a location closer to the sensor, thus providing a more accurate travel time estimate. However, the smaller the size of the detection zone, the lower is the penetration rate, which could itself influence the accuracy of estimates. Therefore, there has to be a trade-off between acceptable level of location ambiguity and penetration rate for configuration and coverage of the antennas.

Accuracy of Travel Time Estimation Using Bluetooth Technology: Case Study Limfjord Tunnel Aalborg

AbstarctBluetooth Technology (BT) has been used as a relatively new cost-effective measurement tool for travel time. However, due to low sampling rate of BT compared to other sensor technologies, the presence of outliers may significantly affect the accuracy and reliability of travel time estimates obtained using BT. In this study, the concept of outliers and their impact on travel time accuracy are discussed. Four different estimators, namely Min-BT, Max-BT, Med-BT and Avg-BT, were used to estimate travel times using BT. By means of various estimation methods, it is tried to evaluate the impact of estimation method on the accuracy of estimated travel time using BT. Two sources of Floating Car Data (FCD) were used as the ground truth in order to quantify and evaluate the accuracy of travel time profiles obtained by BT. Three aggregation techniques including arithmetic mean, geometric mean and harmonic mean were used to construct the travel time profile using BT dataset. In order to quantify the impact of sample size on accuracy of travel time estimates, a series of sensitivity analyses are conducted. Results show that Min-BT and Med-BT are more robust in the presence of outliers in the dataset and can provide more accurate travel time estimates compared to Max-BT and Avg-BT. Moreover, implementing harmonic mean and geometric mean for travel time profile construction could significantly improve the accuracy of estimates obtained by BT.

Mode-Specific Travel Time Estimation Using Bluetooth Technology

The problem of mode-specific travel time estimation is mostly relevant to arterials with different travel modes, including cars, buses, cyclists, and pedestrians. Traditional travel time measurement systems such as automated number plate recognition (ANPR) cameras detect only motor vehicles and provide an estimate of their travel times. Bluetooth technology has been used as an alternative to more expensive ANPR for travel time measurements in the recent past. However, Bluetooth-sensors detect discoverable electronic devices used by all travel modes. Bluetooth-based systems currently use the time stamp of device detection events by two sensors to estimate the travel time, and there is no direct way to estimate mode-specific travel times using this approach. Hence, estimating travel time using Bluetooth technology on urban arterials without classifying the modes of detected devices could provide a biased estimate. A novel method to estimate mode-specific travel times using Bluetooth technology that is capable of estimating mode-specific travel times, specifically distinguishing between the travel time of motor vehicles and bicycles, is presented in this article. The proposed method uses information about type of detected device (class of device, CoD) and radio signal strength indication (RSSI). The proposed method also uses the travel time of the detected device and its detection pattern across the road network by multiple Bluetooth sensors to estimate the travel mode of each detected device. The accuracy of the proposed method was evaluated against the ground truth obtained by manual transcription of traffic video recordings, and was compared against travel times obtained from ANPR, a commercially deployed Bluetooth-based method, and a clustering method. The results show that the proposed method provides travel time estimates using Bluetooth with almost the same level of accuracy as ANPR under mixed traffic conditions.

Randomized trials and self-reported accidents as a method to study safety-enhancing measures for cyclists—two case studies

A large number of studies show that high visibility in traffic is important in the struggle of getting the attention from other road users and thus an important safety factor. Cyclists have a much higher risk of being killed or injured in a traffic accident than car drivers so for them high visibility is particularly important. A number of studies have examined the effect of high visibility, such as reflective clothing, but most studies have been primitive, the data limited and the results very uncertain. In this paper we describe the safety impact of increased visibility of cyclists through two randomised controlled trials: permanent running lights on bicycles and a yellow bicycle jacket, respectively. The effect of running lights was studied through a trial where the lights were mounted to 1,845 bicycles and 2,000 others comprised a control group. The bicycle accidents were recorded every two month in a year through self-reporting on the Internet. Participants were asked to report all cycling accidents independently of severity to avoid differences between participants as regards to which accidents were reported. They reported a total of 255 accidents i.e. 7 accidents per 100 cyclists. The results showed that the incidence rate for multiparty bicycle accidents with personal injury was 47% lower for cyclists with permanent running light. The difference is statistically significant at the 5% level. The effect of a yellow bicycle jacket was examined through a trial with 6,800 volunteer cyclists. The half of the group received a bicycle jacket and the other half comprised a control group. Both groups reported every month all their bicycle accidents independently of severity on the Internet. They reported a total of 694 accidents i.e. 10 accidents per 100 cyclists. The treatment group was asked each month if they carried the jacket on their last cycling trip. The results showed that on a random day the treatment group carried the jacket or other fluorescent cycling garment on 77% of their cycle trips. The incidence rate for multiparty accidents with personal injury was 38% lower than the control group. The difference is statistically significant at the 5% level. The trials were not blind and it seems that the lack of blinding has influenced the level of the groups accident reporting. To address this bias we used a correction factor formed by the difference in the number of single accidents of the two groups. The experiences with self-reporting of accidents via a web based questionnaire sent by e-mail with one respective two month intervals were very good; in both trials more than 80% answered all questionnaires whereas less than 2% did not answer, and the quality of the self-reported accident was considered high.

Use of Low-Level Sensor Data to Improve the Accuracy of Bluetooth-Based Travel Time Estimation

Bluetooth sensors have a large detection zone compared with other static vehicle reidentification systems. A larger detection zone increases the probability of detecting a Bluetooth-enabled device in a fast-moving vehicle, yet increases the probability of multiple detection events being triggered by a single device. The latter situation could lead to location ambiguity and could reduce the accuracy of travel time estimation. Therefore, the accuracy of travel time estimation by Bluetooth technology depends on how location ambiguity is handled by the estimation method. The issue of multiple detection events in the context of travel time estimation by Bluetooth technology has been considered by various researchers. However, treatment of this issue has been simplistic. Most previous studies have used the first detection event (enter–enter) as the best estimate. No systematic analysis has been conducted to explore the most accurate method of travel time estimation with multiple detection events. In this study, different aspects of the Bluetooth detection zone, including size and impact on the accuracy of travel time estimation, were discussed. Four methods were applied to estimate travel time: enter–enter, leave–leave, peak–peak, and combined. These methods were developed on the basis of various technical considerations related to multiple detection events. A controlled field experiment was conducted to evaluate the accuracy of the methods through comparison with the ground truth travel time data measured by Global Positioning System technology. The results showed that the accuracy of the combined and peak–peak methods was higher than that of the other methods and that the employment of the first detection event did not necessarily yield the best travel time estimation.

Does a tow-bar increase the risk of neck injury in rear-end collisions?

INTRODUCTION Does a tow-bar increase the risk of neck injury in the struck car in a rear-end collision? The rear part of a modern car has collision zones that are rendered nonoperational when the car is equipped with a tow-bar. Past crash tests have shown that a cars acceleration was higher in a car equipped with a tow-bar and also that a dummy placed in a car with a tow-bar had higher peak acceleration in the lower neck area. METHOD This study aimed to investigate the association between the risk of neck injury in drivers and passengers, and the presence of a registered tow-bar on the struck car in a rear-end collision. We performed a merger of police reports, the National Hospital Discharge Registry, and the National Registry of Motor Vehicles in Denmark. We identified 9,370 drivers and passengers of whom 1,519 were diagnosed with neck injury within the first year after the collision. We found a statistically insignificant 5% decrease in the risk of neck injury in the occupants of the struck car when a tow-bar was fitted compared to when it was not fitted (hazard ratio=0.95; 95% confidence level=0.85-1.05; p=0.32). The result was controlled for gender, age, and the seat of the occupant. Several other collision and car characteristics and demographic information on the drivers and passengers were evaluated as confounders but were not statistically significant. CONCLUSIONS The present study may serve as valuable input for a meta-analysis on the effect of a tow-bar because negative results are necessary in order to avoid publication bias.