The effect of non-punitive peer comparison and performance feedback on drivers' behavior using the telematics: The first randomized trial in Iran

The effect of Real-Time feedback and incentives on speeding behaviors using Telematics: A randomized controlled trial

Speeding behaviour of drivers is highly correlated to their tangible consequence. Therefore, this study aimed to evaluate the effectiveness of telematics-based feedback and financial incentives in reducing speeding behaviors through a randomized controlled field trial. This randomized controlled trial included four groups of (1) control, (2) information-only, (3) gain-of-reward, and (4) loss-of-reward. While drivers of the control group were unobtrusively monitored using telematics devices, drivers of the information-only group received real-time, weekly, and monthly feedback via text message. In both groups with financial incentives, in addition to receiving feedback, drivers could receive payments at the end of each month based on observed speeding. The primary outcome was the distance traveled at speeds more than 10% (S10 + ) above the posted speed limit as a proportion of the total traveled distance. A total of 397 male taxi drivers consented to participate in the study. After the stratified randomization, the mean age of the participant was 46.0 (95% Confidence Interval: 43.8 to 48.2), 47.0 (44.7 to 49.3), 46.1 (43.7 to 48.5), and 48.8 (46.5 to 51.1) years for the control, the information-only, the gain-of-reward, and the loss-of-reward groups, respectively. The mean S10 + rate per 100 km was 0.9 (0.5 to 1.2) for the control, 0.8 (0.4 to 1.1) for the information-only, 0.7 (0.3 to 1.1) for the gain-of-reward, and 1.3 (0.4 to 2.2) for the loss-of-reward group at the start of intervention. During the intervention phase, the loss-of-reward group with 0.6 (0.5 to 0.7) had the lowest mean of S10 + rate, followed by the gain-of-reward group with 0.8 (0.7 to 0.8). The loss-of-reward and gain-of-reward groups were the most influenced groups by the intervention, with 38.0% (13.2 to 55.7; p-value < 0.01) and 29.4% (2.0 to 49.2; p-value = 0.04) less S10 + rate than the control group, respectively. It was figured out that providing information regarding drivers' behavior without appropriating motives or penalties would have a minuscule impact.In addition, the group of drivers who were treated with instant punishment was the most influenced group by the intervention.

The effectiveness of fixed speed cameras on Iranian taxi drivers: An evaluation of the influential factors

Background

The adherence to speed limits can reduce deaths associated with road traffic injuries (RTIs) by more than a quarter. This study aimed to evaluate the effective factors on the speeding behavior of Iranian taxi drivers around fixed speed cameras.

Method

Telematics devices used in this study collected the location and speed of the vehicles. The units of analysis in this study were trips per camera, including 2.5 km before and after each camera. Linear regression analysis was used to identify kangaroo driving (KD), defined as trips with a significant V-shape in speed distribution around the camera. In the clustered camera zones, cameras were placed at regular intervals of approximately 3.5 km.

Findings

A total of 93,160 trips were recorded from 13,857,443 data points. There was an inverse association between drivers' age and KD with an odds ratio (OR) of 0.98 (95% confidence interval: 0.98-0.98). The intercity trips had a substantially higher probability of KD than urban trips (OR: 4.94 [4.73-5.16]). The tendency of drivers toward KD during the daylight hours vs. nighttime was significant for both urban (OR: 1.15 [1.06-1.25]) and intercity (OR: 1.18 [1.14-1.22]) trips. The 4 -8 a.m. period had the highest chance of KD in both urban (10.71% [7.41-14.53]) and intercity (44.13% [41.18-47.09]) trips. There was a significant decrease in the odds of KD inside the clustered camera zones (OR: 0.22 [0.20-0.25]).

Conclusion

The heterogeneous occurrence of KD in different locations and times indicates the necessity of evidence-based decision-making in urban planning to improve safe driving behaviors. The lower occurrence of KD in clustered camera zones could be a practical key to the effective control of speeding behaviors by helping in the efficient placement of cameras through sustainable development of cities and roads.