Make this detour and be unselfish! Influencing urban route choice by explaining traffic management

Traffic management policies aim to improve traffic flow by influencing the route choice of drivers, therefore preventing traffic jams in crowded cities. With respect to a system-optimum of the traffic network, drivers might have to make small-scale detours. The aim of this article is to encourage unselfish route choice behaviour in an urban context by informing drivers in advance about the objectives of traffic management. Two studies were conducted: (1) an online survey (N = 244) and (2) a driving simulation study (N = 48). The first study focussed on the general effect of recommendations for routes with longer travel times (system-optimal routes) when traffic management is explained. Other route choice attributes (travel time, red-light duration, time pressure) were analysed as well. Drivers were randomly confronted with 35 route choice scenarios consisting of a main route with certain red-light duration and an alternative route without. Results showed that the compliance with system-optimal routes is increased by around 10 percentage points when comparing the group with recommendation to the group without. This effect occurred independently of the variation of other route choice attributes. The second study aimed to determine if the compliance can be increased even more if drivers receive in-depth information about traffic management and experience ‘good’ as well as ‘bad’ recommendations in a driving simulator. Results showed no further effect of these manipulations on route choice. Only decision-making times and subjective evaluation were influenced by in-depth information compared to basic information. Altruism was partly correlated with decision-making. This article shows a novel approach to encouraging drivers to select routes with longer travel times for the benefit of the common good. Drivers’ knowledge gap regarding traffic management needs to be closed in order to enhance their understanding of traffic regulations. Finally, results of this research should be transferred to driver models within traffic simulations to estimate the effects on traffic networks.     

Travel behavior changes and responses to advanced traveler information in prolonged and large-scale network disruptions: A case study of west LRT line construction in the city of Calgary

The objective of this study was the investigation of travel behavioral effects of the reduction in traffic capacity resulting from the construction of the West LRT (Light Rail Transit) line in the city of Calgary, Alberta, Canada. Travelers’ responses to real-time information providing traffic updates and advisory detours due to lane/road closures were also examined. The West LRT alignment extends approximately 8.2 km from downtown into the city’s southwest. Many road closures took place in the vicinity of the LRT line construction zones, inducing significant delays to traffic. Data on travelers’ behavioral responses and responses to real-time information were obtained by conducting a survey on a sample of users of the main road affected by the construction. The survey also investigated the effects of West LRT line construction on drivers’ daily commutes, including increases in travel times, mode choices, alternate route choices, and selection of sources of information on traffic conditions. A significant change in the selection of transportation mode was caused by West LRT construction. Throughout the construction period, there was a decrease in the percentage of respondents who reported private vehicles as their first choice and an increase in the percentage of respondents who preferred public transit as their first and second choices. Radio was found to be the most preferred source for traffic updates and detour advice, followed by variable message signs (VMS). The findings of the en-route information model showed that driving experience, employment status, travel time and purpose, and desire for pre-trip information had significant effects on traveler’s rerouting decisions after getting en-route information through VMS. The results from this study are of interest for understanding behavioral changes for the purposes of traffic management, mitigation schemes and design of advanced traveler information systems in response to network disruptions.     

Delay or travel time information? The impact of advanced traveler information systems on drivers’ behavior before freeway work zones

Peak travel times contribute to congestion formation at freeway work zones. Advanced Traveler Information Systems (ATIS) can inform drivers in real-time about the delays and travel times en-route and can provide information about an alternative route to a destination. Different ATIS display strategies are available; however, road authorities lack insights into how time display methods and sign characteristics influence the driving behavior (decelerations, lateral position), the drivers’ attention allocation ability and the subsequent route choice before the freeway diversion. A driving simulator study was conducted with 80 drivers in the State of Qatar to investigate drivers' behavior and voluntary route choices when encountering total travel time (default setting) or delay time updates for two freeway routes on Variable Message Signs (VMS) and Graphical Route Information Panels (GRIP). The GRIPs are a graphical alternative to conventional VMS that can provide drivers with a visual map of the most direct route or an alternative less congested route to a destination using different color schemes. The time difference ratio between the two routes was kept constant to compare the effectiveness of the information designs and investigate the drivers’ attention towards the signs with an eye-tracker. The results showed that the display of zero delays for a detour did influence 74–83% of the drivers to take the alternative route when being displayed on a VMS and a GRIP with free flow attribute framing. When displaying equal total travel times, the GRIP did influence 25% more drivers to follow the alternative route than the VMS. Generally, displaying zero delays for the alternative route resulted in an efficient attention allocation to the first ATIS location and fewer mean decelerations before the repeated ATIS location nearing the diversion. Road authorities are advised to activate the display of delay times to support efficient route choices among freeway drivers.     

Introducing human factors in pedestrian crossing behaviour models

The objective of this research is the development of pedestrian crossing choice models on the basis of road, traffic and human factors. For that purpose, a field survey was carried out, in which a panel of 75 pedestrians were asked to take 8 short walking trips (each one corresponding to a different walking and crossing scenario) in the Athens city centre in Greece, allowing to record their crossing behaviour in different road and traffic conditions. The same individuals were asked to fill in a questionnaire on their travel motivations, their mobility characteristics, their risk perceptions and preferences with respect to walking and road crossing, their opinion on drivers, etc. The walking and crossing scenarios’ data were used to develop mixed sequential logit models of pedestrian behaviour on the basis of road and traffic characteristics. The modelling results showed that pedestrian crossing choices are significantly affected by road type, traffic flow and traffic control. The questionnaire data were used to estimate human factors (components) of pedestrian crossing behaviour by means of principal component analysis. The results showed that three components of pedestrian crossing behaviour emerge, namely a “risk-taking and optimisation” component reflecting the tendency to cross at mid-block in order to save time, etc., a “conservative” component, concerning individuals with increased perceived risk of mid-block crossing, who also appear to be frequent public transport users, and a “pedestrian for pleasure” component, bringing together frequent pedestrians, walking for health or pleasure, etc. The introduction of these components as explanatory variables into the choice models resulted in improvement of the modelling results, indicating that human factors have additional explanatory power over road and traffic factors of pedestrian behaviour. Therefore, the development of integrated choice and latent variables models appears to be an appropriate field for further research.     

Who overtakes more? Explanatory analysis of the characteristics of drivers from low/middle and high-income countries on passing frequency

The passing manoeuvre requires a driver to make decisions and take actions which are dependent on his/her behavioural characteristics and driving ability. However, previous works on passing rate models have exclusively considered geometric and traffic-related variables. This study aims at bridging this gap by investigating the influence of driver profile (i.e., age, gender, nationality - Italian or Iranian - aggressive driving scores, driving exposure) on passing frequency. A driving simulation experiment involving 54 drivers (36 Italians, 18 Iranians) was conducted along a 6.67 km segment of a two-lane rural highway with passing manoeuvres permitted along 25% of its length. Controlled factors included traffic flow and speed in the oncoming direction, and speed in the driver direction, with a total of 27 scenarios assigned to drivers based on a 3³ confounded factorial design. A Poisson regression model was used to investigate the significance of independent variables. Age and gender and their interaction term were significant, thus the effects of age and gender on the number of passing manoeuvres are mutually interdependent. Furthermore, drivers who drive less often completed fewer overtaking manoeuvres. Sensitivity analyses were carried out to understand the magnitude of change in passing frequency attributable to a variation in the explanatory variables. The findings suggest that driver characteristics have a significant effect on passing frequency and should be considered when conducting a performance and safety evaluation of two-lane roads.     

User-related assessment of a Driver Assistance System for Continuous Support – A field trial

A Driver Assistance System for Continuous Support continuously evaluates the status of the host vehicle as well as the surrounding traffic based on information from on-board sensors. When the system detects a hazard, it issues a warning to the driver, depending on the degree of the hazard. The effects of this system on driver behaviour and acceptance were evaluated in a field trial carried out in 2013. Twenty-four drivers took part in test drives with a within-subject design along a 53 km test route containing motorway and rural-road sections. Driving data was logged and the test drivers were observed by means of an in-car observation method (Wiener Fahrprobe); in this case by two observers in the car along with the driver. Questionnaires were used to assess the drivers’ comprehension of and reaction to the system. The system was successful in affecting driver behaviour in terms of lower speed when negotiating curves. Positive effects were found in the form of better speed adaptation to the situation during driving with the system activated. Also, lane choice and lane change improved with the system on. When it came to speed limit compliance, driving speed in general and longitudinal and lateral positioning, no effects could be found. No major differences were found regarding distance to the vehicle in front, overtaking manoeuvres, stopping behaviour at intersections, driving against yellow at traffic lights and interaction behaviour with other road users while driving with or without the system. On the negative side, it was noted that only during driving with the system activated did the test drivers make turns at intersections at too high speeds. In addition, more errors associated with dangerous distance to the side were observed with the system activated. In terms of the emotional state of the driver, the only difference found was that the drivers felt an increase in irritation. Regarding subjective workload, the drivers only assessed one item, i.e. whether their performance decreased statistically significantly while driving with the system. The test drivers were of the opinion that the system was useful, and that it would enhance safety especially in overtaking manoeuvres on motorways. The blind-spot warning was found especially useful in the overtaking process. The drivers appreciated the fact that the system did not give information all the time.     

Driving around bends with or without shoulders: The influence of bend direction

Paved shoulders have long been used to create “forgiving” roads where drivers can maintain control of their vehicles even when as they drift out of the lane. While the safety benefits of shoulders have been well documented, their effects on driver behavior around curves have scarcely been examined. The purpose of this paper is to fill this gap by assessing whether the addition of shoulders affects driver behavior differently as a function of bend direction. Driver behavior in a driving simulator was analyzed on left and right curves of two-lane rural roads in the presence and absence of 0.75-m and 1.25-m shoulders. The results demonstrated significant changes in drivers’ lateral control when shoulders were provided. In the absence of oncoming traffic, the shoulders caused participants to deviate more toward the inner lane edge at curve entry, at the apex and at the innermost position on right bends but not left ones. In the presence of oncoming traffic, this also occurred at the apex and the innermost position, leading participants to spend more time off the lane on right curves. Participants did not slow down in either traffic condition to compensate for steering farther inside, thereby increasing the risk of lane departure on right curves equipped with shoulders. These findings highlight the direction-specific influence of shoulders on a driver’s steering control when driving around bends. They provide arguments supporting the idea that drivers view paved shoulders as a new field of safe travel on right curves. Recommendations are made to encourage drivers to keep their vehicle within the lane on right bends and to prevent potential interference with cyclists when a shoulder is present.     

Accounting for sensation seeking in route choice behavior with travel time information

The purpose of this paper is to demonstrate that latent variables, with the focus on sensation seeking concepts, incorporated in new technique of route choice modeling, improve our analyzing of route choice behavior with pre-trip travel time information. The application of a hybrid discrete choice model framework integrates a latent variable model and a route choice model by combining their measurement and structural equations. The model is estimated based on data from a laboratory experiment and a field study of a simple network. The results show that certain sensation seeking domains (e.g., thrill and adventure seeking) alongside traditional variables (e.g., travel time information) enrich our understanding and provide more insight into route choice behavior. Furthermore, observed personal variables, such as gender and marital status, may serve as causal indicators to sensation seeking variables.     

Instruction-prompted objective behaviors as proxy for subjective measures in a driving simulator

Interactions with other road users and interpretations of traffic situations are important aspects of driving safety. Self-reports are often used to study drivers’ perceptions and attitudes but self-reports can be inaccurate and biased because of socially desirable responding. Driving simulators offer objective measures of driver behaviors but have limited ability to elicit natural behaviors. To address this issue, we tested a driving simulator-based approach that combined realistic driving scenarios including potentially frustrating forward obstacles and delays in travel time with two different types of instructions. Participants' vehicle control behaviors and subjective perception of traffic delays were compared. Results demonstrated that behaviors collected following instructions to drive safely did not have significant associations with participants’ perceptions of the traffic delays while participants following instructions to drive quickly demonstrated behaviors that were predictive of their subjective perceptions of the traffic delays. The findings suggest that vehicle control behaviors can be used as a proxy for subjective perceptions of traffic delays. We conclude that driving simulator methodology combining instructions, realistic traffic scenarios, and adaptive analytical methods is appropriate for studying drivers’ behaviors and interactions with other road users and can minimize the need to rely on subjective self-reports.     

Influence of following vehicle’s tailway and classification on subject driver’s response to the circular yellow indication

Traffic crashes at signalized intersections are frequently linked to driver behavior at the onset of the circular yellow (CY) indication. To better understand behavioral factors that influence a driver’s decision to stop or go at an intersection, this study analyzed the behavior of the driver of a subject vehicle at the onset of the CY indication. Driver performance data from 53 participants were collected in the Oregon State University Driving Simulator, simulating scenarios of driving through high-speed intersections under various conditions. Data included interactions where the driver stopped at the stop line (n = 644) or proceeded through the intersection (n = 628) in response to a CY indication. Data were analyzed as panel data while considering 12 indicator variables related to the driver’s stop/go decision. These indicator variables included time to stop line (TTSL), tailway time, following vehicle type, vehicle speed at the onset of the CY indication, and demographics (age, gender, driving experience, level of education, personal vehicle type, number of times driving per week, number of miles driving last year, participation in previous simulation studies. A random-parameter binary logit model was used to determine contributing factors for driver decision making at the onset of CY indication while accounting for unobserved heterogeneity. Four indicator variables were significantly related to the driver’s stop/go decision, but three factors varied across observations. Findings showed that a driver’s stop/go decision in response to a CY indication was associated with the time to the stop line (TTSL), tailway time to the following vehicle, subject vehicle speed at the onset of the CY indication, and driver’s age (20–36 years), but was not significantly associated with classification of the following vehicle. Also, the findings indicated that a shorter tailway increased a subject driver’s red-light running frequency. These findings provide insights into variables that affect driver decisions in a vehicle-following situation at the onset of the CY indication. This information can help make better decisions in smart traffic control systems such as to extend/decrease the green interval slightly to avoid decisions that are more difficult.     

Foot-in-the-door technique and reduction of driver’s aggressiveness: A field study

Research has reported that the foot-in-the-door technique is effective at increasing helping behavior. However, the effect of this technique on negative social behavior has never been examined. A field experiment was conducted to explore whether this technique could reduce aggressiveness. Drivers waiting at a traffic light were blocked by an experimental car. In the Foot-in-the-door condition, when the traffic light was red, a passerby confederate asked the driver for directions to a well-known store located in the area of the experiment. The confederate then thanked the driver and walked off in the direction indicated. In the control condition, no request was addressed to the car driver. When the traffic light turned green, the experimental car pretended to be blocked by an engine problem. The number of drivers who honked at the target car and the amount of time that elapsed before the drivers responded by honking their horns were the dependent variables. It was found that fewer drivers honked in the Foot-in-the-door condition and drivers who honked displayed their behavior later than those in the control condition. Self-perception theory was used to explain these results.     

Identifying the main factors contributing to driving errors and traffic violations – Results from naturalistic driving data

Researchers have identified various factors that likely affect aberrant driving behaviors and therefore crash risk. However, it remains unclear which of these factors poses the greatest risk for either errors or violations under naturalistic driving conditions. This study investigated important variables contributing to driving errors and traffic violations based on naturalistic driving data from the second Strategic Highway Research Program (SHRP 2). In addition, this study identified factors determining the drivers’ willingness to perform common secondary tasks while driving, which have been associated with different degrees of crash risk. Results showed that anger, passenger presence, and persistent individual differences in driver behavior were the main factors associated with committed violations; surprise, high-risk visually distracting secondary tasks, and the driving task demand passing through an interchange were the main factors associated with errors. The willingness to engage in risky secondary tasks while driving appeared to be related to an overall tendency to engage in risky driving behaviors. However, drivers considered the driving context particularly when engaging in visually distracting secondary tasks. This study’s comprehensive approach should be a step towards generating a complete model of the variables that contribute to, or mitigate dangers in traffic.     

Temporal fluctuations in driving demand: The effect of traffic complexity on subjective measures of workload and driving performance

Traffic density has been shown to be a factor of traffic complexity which influences driver workload. However, little research has systematically varied and examined how traffic density affects workload in dynamic traffic conditions. In this driving simulator study, the effects of two dynamically changing traffic complexity factors (Traffic Flow and Lane Change Presence) on workload were examined. These fluctuations in driving demand were then captured using a continuous subjective rating method and driving performance measures. The results indicate a linear upward trend in driver workload with increasing traffic flow, up to moderate traffic flow levels. The analysis also showed that driver workload increased when a lane change occurred in the drivers’ forward field of view, with further increases in workload when that lane change occurred in close proximity. Both of these main effects were captured via subjective assessment and with driving performance parameters such as speed variation, mean time headway and variation in lateral position. Understanding how these traffic behaviours dynamically influence driver workload is beneficial in estimating and managing driver workload. The present study suggests possible ways of defining the level of workload associated with surrounding traffic complexity, which could help contribute to the design of an adaptive workload estimator.     

Passing behavior on two-lane highways

Two-lane highways make up a substantial proportion of the road network in most of the world. Passing is among the most significant driving behaviors on two-lane highways. It substantially impacts the highway performance. Despite the importance of the problem, few studies attempted to model passing behavior. In this research, a model that attempts to capture both drivers’ desire to pass and their gap acceptance decisions to complete a desired passing maneuver is developed and estimated using data on passing maneuvers collected with a driving simulator. Sixteen different scenarios were used in the experiment in order to capture the impact of factors related to the various vehicles involved, the road geometry and the driver characteristics in the model.A passing behavior model is developed that includes choices in two levels: the desire to pass and the decision whether or not to accept an available passing gap. The probability to complete a passing maneuver is modeled as the product of the probabilities of a positive decision on both these choices. The estimation results show that modeling the drivers’ desire to pass the vehicle in front has a statistically significant contribution in explaining their passing behavior. The two sub-models incorporate variables that capture the impact of the attributes of the specific passing gap that the driver evaluates and the relevant vehicles, the geometric characteristics of the road section and the driver characteristics and account for unobserved heterogeneity in the driver population.     

Effectiveness of the compensatory strategy adopted by older drivers: Difference between professional and non-professional drivers

It has been a controversial issue for the effect of ageing population on driving safety. Apparently, drivers’ physiological and cognitive performances deteriorate with age. However, older drivers may compensate for the elevated risk by adjusting their behaviors, known as compensatory strategy. Despite the extensive research on this topic, the compensatory strategy of older professional drivers is not well understood since many studies focused on the differences in compensatory behavior between older and young drivers. Professional drivers tend to be more skillful and able to cope with the unfavorable driving environments, thus presenting a higher capability to mitigate the risk. This study attempts to examine the compensatory behavior and its safety effect amongst older professional drivers, as compared to those of older non-professional drivers, using the driving simulator approach. In the driving simulator experiment, participants were asked to follow a leading vehicle for one hour, and two sudden brake events were presented. 41 (mid-aged and older) drivers completed the driving tests. Each participant was required to complete a car-following test, either under high or low traffic flow conditions. Performance indicators include driving capability (i.e. lateral control, longitudinal control, and brake reaction time) and compensatory behavior (i.e. average speed, and time headway). Additionally, two modified traffic conflict measures: time exposed time-to-collision (TET) and time integrated time-to-collision (TIT) are applied to indicate the traffic conflict risk. The random parameter Tobit models were estimated to measure the association between conflict risk and driver attributes, and random intercept models were used to assess other driving performance indicators. Results show that despite the impaired lateral control performance and longer brake reaction time of older drivers, the likelihood of severe traffic conflict of older drivers is lower than that of mid-aged drivers. Furthermore, though both older professional and older non-professional drivers adopted longer time headway, the reduction in the risk of severe traffic conflict is more profound among the older professional drivers. Such findings suggest that older professional drivers are more capable of mitigating the possible collision risk by adopting the compensatory strategy, as compared to older non-professional drivers. This justifies the existence of compound effect by the compensatory strategy of older driver and better driving skills of professional driver. This research provides useful insights into driver training and management strategies for employers, as older drivers would become a major cohort in the transportation industry.     

Tactical steering behaviour under irrevocable visual occlusion

ObjectiveTo investigate the extent of a driver’s mental model with irrevocable visual occlusion and analysing the distance to crash.BackgroundDrivers have a mental model of the immediate surroundings which allows them to predict their own as well as others’ travel paths. To navigate safely through traffic, this mental model has to be updated frequently to remain valid. In between information sampling events, the mental model will become outdated over time, as the traffic system is dynamic.MethodA simulator study with 22 participants was conducted to investigate the information decay in the mental model. This was implemented by extending visual occlusion until the driver collided with another vehicle or ran off the road, thus providing an estimate of how long it takes until the mental model becomes obsolete.ResultsAn analysis of variance with the factors curve direction, curve radius and traffic showed that curve radius did not influence the distance to crash. Without traffic, drivers veered off the road sooner in right curves. Adding traffic eliminated this difference. Traffic ahead led to a shortened distance to crash. Compared to a tangential travel path from the current lateral position at the time of the occlusion, drivers crashed on average 2.6 times later than they would have, had they not had any mental model of the situation.ConclusionsThe drivers’ mental representation of the future situation seems to include information on how to act, to alleviate deviations in yaw angle, including and considering the presence of other road users.     

A fuzzy-based driver assistance system using human cognitive parameters and driving style information

Reducing the number of traffic accidents due to human errors is an urgent need in several countries around the world. In this scenario, the use of human-robot interaction (HRI) strategies has recently shown to be a feasible solution to compensate human limitations while driving. In this work we propose a HRI system which uses the driver’s cognitive factors and driving style information to improve safety. To achieve this, deep neural networks based approaches are used to detect human cognitive parameters such as sleepiness, driver’s age and head posture. Additionally, driving style information is also obtained through speed analysis and external traffic information. Finally, a fuzzy-based decision-making stage is proposed to manage both human cognitive information and driving style, and then limit the maximum allowed speed of a vehicle. The results showed that we were able to detect human cognitive parameters such as sleepiness –63% to 88% accuracy–, driver’s age –80% accuracy– and head posture –90.42% to 97.86% accuracy– as well as driving style –87.8% average accuracy. Based on such results, the fuzzy-based architecture was able to limit the maximum allowed speed for different scenarios, reducing it from 50 km/h to 17 km/h. Moreover, the fuzzy-based method showed to be more sensitive with respect to inputs changes than a previous published weighted-based inference method.     

Logistics of hurricane evacuation in Hurricanes Katrina and Rita

This study examines household hurricane evacuation logistics—the activities and associated resources needed to reach a safe location and remain there until it is safe to return—during Hurricanes Katrina and Rita. Evacuation logistics variables include evacuation route information sources, evacuation departure dates, vehicles taken, evacuation routes and destinations, travel distances and times, shelter accommodations, and costs of transportation, food, and lodging. This study confirmed previous findings that evacuees take multiple cars, rely on personal experience and traffic conditions to choose their evacuation routes, and are most likely to choose the homes of friends/relatives as their shelter accommodations. However, this study also produced new data on evacuation distances, durations, and costs—as well as associations with demographic and situational variables that are associated with household evacuation logistics. In addition, this study provides additional data indicating that common assumptions about evacuation route choice are incorrect. More research is needed to understand evacuees’ choices of ultimate destinations and evacuation routes.     

How drivers adapt their behaviour to changes in task complexity: The role of secondary task demands and road environment factors

The present study investigates the impact of different sources of task complexity such as driving demands and secondary task demands on driver behaviour. Although much research has been dedicated to understanding the impact of secondary task demands or specific road traffic environments on driving performance, there is little information on how drivers adapt their behaviour to their combined presence. This paper aims to describe driver behaviour while negotiating different sources of task complexity, including mobile phone use while driving (i.e., calling and texting) and different road environments (i.e., straight segments, curves, hills, tunnels, and curves on hills). A driving simulator experiment was conducted to explore the effects of different road scenarios and different types of distraction while driving. The collected data was used to estimate driving behaviour through a Generalized Linear Mixed Model (GLMM) with repeated measures. The analysis was divided into two phases. Phase one aimed to evaluate driver performance under the presence and absence of pedestrians and oncoming traffic, different lanes width and different types of distraction. The second phase analysed driver behaviour when driving through different road geometries and lane widths and under different types of distraction. The results of the experiment indicated that drivers are likely to overcorrect position in the vehicle lane in the presence of pedestrians and oncoming traffic. The effect of road geometry on driver behaviour was found to be greater than the effect of mobile phone distraction. Curved roads and hills were found to influence preferred speeds and lateral position the most. The results of this investigation also show that drivers under visual-manual distraction had a higher standard deviation of speed and lateral position compared to the cognitive distraction and the non-distraction condition.