Manuel Silvestri

Effects of safety measures on driver's speed behavior at pedestrian crossings

This paper reports the results of a multi-factorial experiment that was aimed at the following: (a) analyzing drivers speed behavior while approaching zebra crossings under different conditions of vehicle-pedestrian interaction and with respect to several safety measures and (b) comparing safety measures and identifying the most effective treatment for zebra crossings. Three safety countermeasures at pedestrian crossings (curb extensions, parking restrictions and advanced yield markings) and the condition of no treatment (baseline condition) were designed on a two-lane urban road and implemented in an advanced driving simulator. Several conditions of vehicle-pedestrian interaction (in terms of the time left for the vehicle to get to the zebra crossing at the moment the pedestrian starts the crossing) were also simulated. Forty-two drivers completed the driving in the simulator. Based on the recorded speed data, two analyses were performed. The first analysis, which focused on the mean speed profiles, revealed that the drivers speed behavior was affected by conditions of vehicle-pedestrian interaction and was fully consistent with previous findings in the literature and with the Threat Avoidance Model developed by Fuller. Further analysis was based on variables that were obtained from the speed profiles of drivers (the speed at the beginning of the deceleration phase, the distance from the zebra crossing where the deceleration began, the minimum speed value reached during the deceleration, the distance from the pedestrian crossing where the braking phase ended and the average deceleration rate). Multivariate variance analysis (MANOVA) revealed that there was a significant main effect for safety measures and for pedestrian conditions (the presence and absence of a pedestrian). The results identified that the curb extension was the countermeasure that induces the most appropriate drivers speed behavior while approaching the zebra crossing. This conclusion was also confirmed by outcomes of the questionnaire on the countermeasures effectiveness. More than 80% of the drivers perceived that the curb extensions were effective, which indicates that when this countermeasure was present, the drivers were more willing to yield and that the visibility of the pedestrian crossing was better. For this countermeasure, the lowest number of interactions in which the drivers did not yield to a pedestrian was also recorded.

Interaction driver–bicyclist on rural roads: Effects of cross-sections and road geometric elements

The interaction of motorists and bicyclists, particularly during passing maneuvers, is cited as one of the primary causes of bicyclist fatalities. This paper reports the results of a driving simulator study, which sought to analyze the effects that three cross-section configurations of a two-lane rural road and four geometric elements of the road have on driver behavior, during the interaction with a cyclist. A two-lane rural road, about 11km long, was designed and implemented in an advanced-interactive driving simulator. Three different cross-sections (all with same width, but with and without a bicycle lane and for different widths of bicycle lane) were tested. Forty participants carried out three driving sessions (one for each road alignment with different cross-section) and were exposed to the condition of bicycle traffic along four geometric elements of the alignment (2 tangents with different lengths, right curve and left curve). The driving simulator experiments were designed in such a way that, along the sections where the driver-cyclist interactions occurred, the oncoming traffic was absent. Overall, 468 speed profiles and 468 lateral position profiles were plotted to obtain the descriptive variables of the driver behavior during the interaction with the cyclist. The influences of cross-sections, geometric elements and bicycle traffic conditions on driver behavior were evaluated by a multivariate variance analysis. The presence of the cyclist determined different levels of influence on drivers trajectory for the three cross-sections. A wider bicycle lane ensured a higher later clearance distance between driver and cyclist, allowing safer overtaking maneuver. The interferences of the cyclist on drivers behavior depended on the geometric elements. On tangents, the lowest lateral clearances were recorded and no speed reduction was observed, compared to the cyclist absence condition. On the left curve, the higher lateral clearance was recorded, due to the concordant tendencies of the driver to move away from the cyclist and to cut the curve. This determined an excessive and risky displacement of the vehicle to the opposing lane, whose criticality was also emphasized by the high speed adopted by the driver. On the right curve, the lateral clearance was higher than that recorded on the tangents, probably due to the necessity of the driver to perform the demanding maneuver of entering in the right curve, which also determined a speed reduction compared to the cyclist absence condition. The obtained results provide suggestions for the most efficient cross-section reorganization of existing two-lane rural roads in order to improve the road safety.

Drivers’ Behavior at Bicycle Crossroads

The main objective of this study was to examine the effect on drivers’ behavior of several countermeasures at bicycle crossroads during the driver–cyclist interaction (a cyclist that crosses the road) by the use of a driving simulator. Three conditions of cyclist crossroads were investigated: baseline condition (no treatment), raised island and the colored paved markings. Forty-two participants drove a suburban scenario with several bicycle crossroads having different configurations and presence/absence of cyclist. 378 speed profiles were plotted from 150 m before each crossroads. The analysis revealed that the driver’s speed behavior was fully consistent with the behavioral models in literature. A further analysis was performed on driver’s speed by ANOVA. Results showed that there was a main effect of the countermeasures, which determined lower speeds compared with that of the baseline condition. In addition, driver behavior was actually characterized by the specific peculiarities of the two countermeasures and both determined a better yielding behavior. However, the outcome of the questionnaire to participants showed that colored paved markings was considered as the most effective in terms of driving aid.

Driver–Cyclist Interaction Under Different Bicycle Crossroad Configurations

Objective of the present study was to analyze the effectiveness of countermeasures at bicycle crossroads during the driver–cyclist interaction by the use of a driving simulator. Three countermeasures were examined: baseline condition (absence of treatment), colored paved markings and raised island. Forty-two participants drove a suburban scenario with several bicycle crossroads having difference configurations and presence/absence of cyclist. 378 speed profiles were plotted from 150 m before each crossroads to obtain the explanatory variables of the driver behavior. A set of ANOVAs was used to analyze the driver behavior. Results showed that countermeasures affected in statistically significant way the distance at which the driver ends the braking maneuver, highlighting the better effectiveness of the colored pavement. A general improvement of the driver speed behavior was also observed for this countermeasure. The outcome of the questionnaire confirmed that it was considered as the most effective in terms of driving aid.

Drivers’ Behavior in Pedestrian Detection: Effects of Road Types

The current study was aimed to study the driver’s behavior while approaching zebra crossings under different types of roads. A driving simulator experiment was carried out to collect drivers’ behavior in response to a pedestrian crossing in different road environments (urban, suburban and rural road). The speed profile of each driver was plotted 150 m in advance of each one of the crossroads and the variables of the driving behavior were analyzed by a set of ANOVAs. Results showed that the driver had similar behavior in the urban and suburban road, while in the rural environment the driver compensates the higher risks due to the higher speeds by advancing the yielding maneuver. Such findings should be considered for the development of driving assistance systems for pedestrian detection in the different types of road environments.

Effects on Driver’s Behavior of Illegal Pedestrian Crossings

The aim of this study was to analyze the driver behavior during the interaction with a pedestrian crossing into and outside the zebra crossing. 42 participants experienced different conditions of driver-pedestrian interactions (no pedestrian, legal and illegal crossings). The drivers’ behavior variables were collected from the drivers’ speed profiles, which were plotted in the last 150 m in advance of the collision point. Based on the vehicle dynamics, more critical driver’s speed behaviors were revealed for illegal pedestrian crossings, for which the driver adopted abrupt yielding maneuver compared to the legal crossing condition. Moreover, higher accident rates were recorded when drivers interacted with jaywalkers. The results confirm that adequate pedestrian paths should be planned in order to avoid jaywalker conditions and pedestrian detection systems could significantly help the driver in the condition of illegal pedestrian crossing behavior.

Survival Model of Drivers’ Speed Reduction Time at Bicycle Crossroads: A Driving Simulator Study

The main objective of this study was to assess the effectiveness of several countermeasures at bicycle crossroads on drivers’ behavior during the driver–cyclist interaction (a cyclist that crosses the road) by the use of a driving simulator. Three treatments of the cyclist crossroads were investigated: baseline condition (no treatment), raised island, and the colored paved markings. Forty-two participants drove a suburban scenario with several bicycle crossroads having difference configurations and presence/absence of cyclist. Overall, 252 speed profiles were plotted from 150 m before each crossroad of which 23 showed non-yield events: 12 for the baseline condition, 6 for the colored paved markings, and 5 for the raised island. The method of the survival analysis was applied to model the driver speed reduction time (the elapsed time to pass from the initial speed to the minimum speed during the yielding maneuver) with the use of the Weibull distribution. The model identified the average deceleration, the drivers’ age, and the countermeasure condition as significant explanatory variables. The survival curves highlighted that for the colored paved markings the driver adopted longer values of the speed reduction times and then a less aggressive driver’s braking behavior. Moreover, the outcomes of the questionnaire confirmed that the colored paved markings were considered to be the most effective in terms of driving aid.

Effects of Intersection Collision Warning Systems and Traffic Calming Measures on Driver’s Behavior at Intersections

The objective of this study was to examine the effect of intersection collision warning systems (ICWSs) and traffic calming measure on drivers’ behavior, in response to a potential conflict event at the intersections, which constitute a crucial point with respect of the road safety. The drivers’ behavior was analyzed by means of a multivariate variance analysis (MANOVA) procedure. ICWSs were the auditory speech message and the visual warning. Both ICWSs provided to the driver the direction of the violator vehicle. The traffic calming measure was the dragon teeth. Results show that ICWSs help the drivers’ to detect earlier the violator vehicle and act a safer braking maneuver to avoid the conflict at the intersections. For the traffic calming measure no statistically significant effects were found. However, for this condition, a decrease of about 1.3 km/h of the minimum speed value reached by the driver to avoid the collision was recorded.