A Bayesian Network model for contextual versus non-contextual driving behavior assessment

Driving behavior is generally considered to be one of the most important factors in crash occurrence. This paper aims to evaluate the benefits of utilizing context-relevant information in the driving behavior assessment process (i.e. contextual driving behavior assessment approach). We use a Bayesian Network (BN) model that investigates the relationships between GPS driving observations, individual driving behavior, individual driving risks, and individual crash frequency. In contrast to prior studies without context information (i.e. non-contextual approach), the data used in the BN approach is a combination of contextual features in the surrounding environment that may contribute to crash risk, such as road conditions surrounding the vehicle of interest and dynamic traffic flow information, as well as the non-contextual data such as instantaneous driving speed and the acceleration/deceleration of a vehicle. An information-aggregation mechanism is developed to aggregates massive amounts of vehicle GPS data points, kinematic events and context information into drivel-level data. With the proposed model, driving behavior risks for drivers is assessed and the relationship between contextual driving behavior and crash occurrence is established. The analysis results in the case study section show that the contextual model has significantly better performance than the non-contextual model, and that drivers who drive at a speed faster than others or much slower than the speed limit at the ramp, and with more rapid acceleration or deceleration on freeways are more likely to be involved in crash events. In addition, younger drivers, and female drivers with higher VMT are found to have higher crash risk.     

Traffic models for goods,service and business movements to manufacturing establishments

This paper is concerned with a problem area of increasing interest, namely the traffic characteristics of specific generators located on non‐residential land use. It concentrates on the problem of modelling traffic generation for goods, service and business movements at the manufacturing establishment. Firstly the contributions of earlier researchers are reviewed in the context of factors which have been considered important. Then a further study conducted by the author in Sheffield and in Manchester, England, is described. This study considers more rigorously than hitherto the questions of similarities in trip rates over different manufacturing activities and geographical areas, and of the choice of explanatory variables. Comparison of regressions is used to formalize indications of similarities in trip rates, and analysis of variance for choosing the most satisfactory explanatory variables. The study provides evidence of similarity in trip rates over seven different manufacturing activities and two geographical areas. It also shows distinctions between different non‐work traffic types in the extent of similarities in trip rates over different manufacturing activities and in explanatory variables for traffic generation relationships. Regarding the latter it is concluded that it is not possible to model accurately such traffic movements on the basis of explanatory variables which are normally available. Instead trip rates should be expressed in simple mathematical terms and should be based on large data populations. The study also makes contributions on peak flow factors for the actual design of facilities of manufacturing establishments. These findings and others are discussed in the context of the work of earlier researchers. Finally conclusions are drawn and guidance offered for future work into this problem.     

Driver response to variable message signs: a stated preference investigation

This paper uses a Stated Preference approach to undertake a detailed assessment of the effect on drivers’ route choice of information provided by variable message signs (VMS). Although drivers’ response to VMS information will vary according to the availability of alternative routes and the extent to which they are close substitutes, our findings show that route choice can be strongly influenced by the provision of information about traffic conditions ahead. This has important implications for the use of VMS systems as part of comprehensive traffic management and control systems. The principal findings are that the impact of VMS information depends on: the content of the message, such as the cause of delay and its extent; local circumstances, such as relative journey times in normal conditions; and drivers’ characteristics, such as their age, sex and previous network knowledge. The impact of qualitative indicators, visible queues and delays were examined. It was found that not only is delay time more highly valued than normal travel time, which is to be expected, but that drivers become more sensitive to delay time as delay times increased across the range presented.     

Effect of variable message signs on driver speed behavior on a section of expressway under adverse fog conditions—A driving simulator approach

Variable message signs (VMS) are used to provide dynamic information and one current application is to show different speed limits under different conditions. As speed is an important contributor to road accidents and also affects driver speed behavior, the present study focuses on how effective traffic advisory information is when helping drivers to divert from potentially dangerous conditions. Graphical representation of an Expressway section made it easy to isolate the effects of speed etc. by drivers with information provided through VMS under adverse fog conditions. Understanding and reacting to the VMS system by drivers is essential for its success. If drivers do not react by changing speed behavior then the VMS system will fail and further implementation may cease. In this paper an Analysis of Variance model, which is appropriate to the proposed experimental conditions, is used to study how subjects (drivers) will perceive provided information and also to find the effect of VMS on driver speed behavior on the simulated Expressway section.     

Intelligent transportation system and traffic safety – drivers perception and acceptance of electronic speed checkers

Intelligent Transportation System (ITS) can play an important role in reducing risks and increasing traffic safety. Discussion as to whether a technological approach or a behavioral approach is the right way to achieve a safer traffic environment forms a point of departure for this paper. On the one hand, there are the technicians who emphasize technology as the way towards safer traffic. Behaviorists, on the other hand, view the drivers’ behavior as fundamental and argue that education and incentive-oriented policies are essential in order to influence the driver and therefore increase traffic safety. Independent of the approach advocated a successful outcome of either a technological improvement, or an information campaign, has to be based on a high level of acceptance among potential users. In order to increase traffic safety, it is therefore essential to recognize driver motivation and attitudes. In this paper we focus on drivers’ attitudes towards risk, traffic safety and safety measures. A study of drivers’ attitudes and acceptance of an electronic device for speed checking (which the drivers tested for nine months) indicated a high acceptance level. The drivers perceived that they had both become more aware of traffic regulations and behaved in accordance with safety regulations.     

Public perceptions of the use of dynamic message signs

Intelligent transportation systems have been promoted as a means to improve both the efficiency and safety of the road network. The effectiveness of advanced technologies in improving road safety has been an area of research which has thus far yielded mixed results. In order to ensure that advanced technologies deliver on their intended outcomes, more research has to be devoted to understanding road users' perceptions and reactions to these systems. This study examines drivers' perceptions of the use of dynamic message signs and their self‐reported reactions to the messages displayed. In general, drivers support the use of highway electronic boards for traffic incident reports and weather information which have an impact on traffic delays and level of service. They also think that it is a good idea to display road safety messages and to remind drivers to drive safely and be courteous on the roads. Moreover, most drivers reported that they do read and think about the messages displayed and react positively to some of the road safety messages.     

Effectiveness of using variable message signs to disseminate dynamic traffic information: Evidence from field trails in European cities

Variable message signs (VMS) can provide up‐to‐date traffic information and guidance to drivers through electronic signs at the roadside. The paper draws together the results from VMS field trials conducted in nine cities as part of European Union‐sponsored research projects carried out between 1994 and 1999. The projects followed common guidelines in carrying out field trial evaluations, which has enabled generalized findings to be made on the impacts of the different VMS applications. The main emphasis in the paper is on drivers' reactions to VMS and the impacts of VMS on road network efficiency. Results are reported for four different types of traffic information. For incident messages, it is not only the severity of the problem reported that influences the level of diversions, but also other factors such as the specific location mentioned and the availability of viable alternative routes to avoid the problem location. For route guidance information, it is demonstrated that substantial diversions occur when the route advice differs from that given normally. For continuous information describing the traffic state on a major route, information increases the use of the major route and reduces use of alternative routes if there are no traffic problems reported on the major route. Travel time information was well regarded by drivers and found to be effective in inducing route changes. In general, the deployments of VMS to inform drivers of traffic conditions have proved successful in terms of improving network travel times and reducing environmental impacts. Whilst such changes have been relatively small, driver perception of the benefits is much higher. This is potentially very significant in terms of the role that VMS can play in the development of integrated transport strategies, as the provision of information may encourage greater acceptance of a range of demand management measures.     

An impact analysis of traffic image information system on driver travel choice

A driver is one of the main components in a transportation system that influences the effectiveness of any active demand management (ADM) strategies. As such, the understanding on driver behavior and their travel choice is crucial to ensure the successful implementation of ADM strategies in alleviating traffic congestion, especially in city centres. This study aims to investigate the impact of traffic information dissemination via traffic images on driver travel choice and decision. A relationship of driver travel choice with respect to their perceived congestion level is developed by an integrated framework of genetic algorithm–fuzzy logic, being a new attempt in driver behavior modeling. Results show that drivers consider changing their travel choice when the perceived congestion level is medium, in which changing departure time and diverting to alternative roads are two popular choices. If traffic congestion escalates further, drivers are likely to cancel their trip. Shifting to public transport system is the least likely choice for drivers in an auto-dependent city. These findings are important and useful to engineers as they are required to fully understand driver (user) sensitivity to traffic conditions so that relevant active travel demand management strategies could be implemented successfully. In addition, engineers could use the relationships established in this study to predict drivers’ response under various traffic conditions when carrying out modeling and impact studies.     

Developing freeway lane‐changing support systems using artificial neural networks

Lane‐changing involves many concerns about safety and efficiency which makes it one of the most difficult tasks of driving. It is indeed quite personal since drivers operate vehicles according to their integrated perception of comprehensive circumstances rather than individual rules. A lane‐changing decision support model is developed in this study using artificial neural networks (ANN). The advantages of the ANN approach lie in the learning capability. Due to its nature, an ANN model can consolidate various kinds of information surrounding the vehicle for the drivers and generate reliable results to help control vehicles. It then becomes a useful mechanism to assist drivers in judging current situations and making the right decisions. Several preliminary validations and comparisons are conducted with the field survey data. It is confirmed that the ANN model mimics traffic characteristics more accurately than conventional methods. This product would expedite the implementation of relevant applications in the intelligent transportation systems context. In particular, the ANN model can be adapted to individual driver characteristics. This reveals practical feasibility and significant market potential for customized in‐vehicle equipment.     

Optimisation of parking guidance and information systems display configurations

Operators of parking guidance and information (PGI) systems often have difficulty in determining the best car park availability information to present to drivers in periods of high demand. This paper describes a behavioural model of parking choice incorporating drivers perceptions of waiting times at car parks based on PGI signs. This model was used to predict the influence of PGI signs on the overall performance of the traffic system.Relationships were developed for estimating the arrival rates at car parks based on trip patterns, driver characteristics, car park attributes as well as the car park availability information displayed on PGI signs. Drivers' perceptions of waiting times at car parks were assumed to be influenced by the PGI signs for observers of the signs and actual car park utilisation levels for non-observers. The model assumes that the choice of car park does not change after entering the city centre, even if conditions observed are different from those initially perceived.A mathematical programme was formulated to determine the optimal display PGI sign configuration to minimise queue lengths and vehicle kilometres of travel (VKT). The model was limited to off-street parking choices and illegal parking was not incorporated. A simple genetic algorithm was used to identify solutions that significantly reduced queue lengths and VKT compared with existing practices.These procedures were applied to an existing PGI system operating in Tama New Town near Tokyo. Significant reductions in queue lengths and VKT were predicted using the optimisation model. This would reduce traffic congestion and lead to various environmental benefits.     

Profile of the accident prone older driver

Accident histories and other related records of elderly drivers were used to develop a profile of the accident prone older driver in Michigan. Elderly drivers were defined as drivers with age greater than or equal to 65 years. The variables used in the study were developed by stratifying drivers age, sex, and residency; type of accident and violation; and number of traffic infraction points received. Comparisons were made between these strata, and the statistical significance of observed patterns in cross tabulated data was tested by performing the chi-square test. The results of the study indicate that, by and large, the elderly drivers from urban areas as compared to those from rural areas, and male drivers as compared to females are more likely to be cited for traffic violations. The statistical analysis showed some recognizable traits of the “young” elderly drivers that suggest prioritized safety countermeasures oriented toward them.     

Analysis of yellow-light running at signalized intersections using high-resolution traffic data

Many accidents occurring at signalized intersections are closely related to drivers’ decisions of running through intersections during yellow light, i.e., yellow-light running (YLR). Therefore it is important to understand the relationships between YLR and the factors which contribute to drivers’ decision of YLR. This requires collecting a large amount of YLR cases. However, existing data collection method, which mainly relies on video cameras, has difficulties to collect a large amount of YLR data. In this research, we propose a method to study drivers’ YLR behaviors using high-resolution event-based data from signal control systems. We used 8 months’ high-resolution data collected by two stop-bar detectors at a signalized intersection located in Minnesota and identified over 30,000 YLR cases. To identify the possible reasons for drivers’ decision of YLR, this research further categorized the YLR cases into four types: “in should-go zone”, “in should-stop zone”, “in dilemma zone”, and “in optional zone” according to the driver’s location when signal turns to yellow. Statistical analysis indicates that the mean values of approaching speed and acceleration rate are significantly different for different types of YLR. We also show that there were about 10% of YLR drivers who cannot run through intersection before traffic light turns to red. Furthermore, based on a strong correlation between hourly traffic volume and number of YLR events, this research developed a regression model that can be used to predict the number of YLR events based on hourly flow rate. This research also showed that snowing weather conditions cause more YLR events.     

Modeling car-following behavior on urban expressways in Shanghai: A naturalistic driving study

Although car-following behavior is the core component of microscopic traffic simulation, intelligent transportation systems, and advanced driver assistance systems, the adequacy of the existing car-following models for Chinese drivers has not been investigated with real-world data yet. To address this gap, five representative car-following models were calibrated and evaluated for Shanghai drivers, using 2100 urban-expressway car-following periods extracted from the 161,055 km of driving data collected in the Shanghai Naturalistic Driving Study (SH-NDS). The models were calibrated for each of the 42 subject drivers, and their capabilities of predicting the drivers’ car-following behavior were evaluated.The results show that the intelligent driver model (IDM) has good transferability to model traffic situations not presented in calibration, and it performs best among the evaluated models. Compared to the Wiedemann 99 model used by VISSIM®, the IDM is easier to calibrate and demonstrates a better and more stable performance. These advantages justify its suitability for microscopic traffic simulation tools in Shanghai and likely in other regions of China. Additionally, considerable behavioral differences among different drivers were found, which demonstrates a need for archetypes of a variety of drivers to build a traffic mix in simulation. By comparing calibrated and observed values of the IDM parameters, this study found that (1) interpretable calibrated model parameters are linked with corresponding observable parameters in real world, but they are not necessarily numerically equivalent; and (2) parameters that can be measured in reality also need to be calibrated if better trajectory reproducing capability are to be achieved.     

Why do some motorbike riders wear a helmet and others don’t? Evidence from Delhi,India

Road traffic accident fatalities lead to important private and social costs in the metropolitan areas of most low and middle income countries. An important share of these fatalities is due to injuries to the head and the neck. Helmets can provide efficient protection, but many drivers do not use them. We focus on helmet use behavior among motorbike users in Delhi. We use a detailed data set collected for the purpose of the study. To guide our empirical analysis, we rely on a model in which drivers decide on self-protection and self-insurance. The empirical findings suggest that risk-averse drivers are more likely to wear a helmet and that this has no systematic effect on speed. Helmet use also increases with education. Drivers who show a higher awareness of road risks seem to be both more likely to wear a helmet and to speed less. Controlling for risk awareness, we observe that drivers tend to compensate between speed and helmet use. The results can provide a basis for awareness-raising policies. They also show that improvements to the road infrastructure risk leading to risk-compensating behavior.     

Sight distance analysis of highways using GIS tools

Analyzing the distance visible to a driver on the highway is important for traffic safety, especially in maneuvers such as emergency stops, when passing another vehicle or when vehicles cross at intersections. This analysis is necessary not only in the design phase of highways, but also when they are in service. For its use in this last phase, a procedure supported by a Geographic Information System (GIS) has been implemented that determines the highway distances visible to the driver. The use of a GIS allows the sight distance analysis to be integrated with other analyses related to traffic safety, such as crash and design consistency analyses. In this way, more complete analyses could be made and costs shared. Additionally, with the procedure proposed it is possible to use data regarding the trajectory of a vehicle obtained on a highway with a Global Positioning System (GPS) device. This application is very useful when highway design data are not available. The procedure developed and its application in a case study are presented in this article.     

Mobile phone use by young drivers: effects on traffic speed and headways

Abstract

This paper investigates the effects of mobile phone use while driving on traffic speed and headways, with particular focus on young drivers. For this purpose, a field survey was carried out in real road traffic conditions, in which drivers' speeds and headways were measured while using or not using a mobile phone. The survey took place within a University Campus area, allowing to distinguish between settings approximating to either free flow or interrupted flow conditions. Linear and loglinear regression methods were used to investigate the effects of mobile phone use and several other young driver characteristics, such as gender, driving experience and annual distance travelled, on vehicle speeds and headways. Separate models were developed for average free flow, interrupted flow, as well as for total average speed. Results show that mobile phone use leads to a statistically significant reduction in traffic speeds of young drivers in all types of traffic conditions. Furthermore, male and female drivers reduce their speed similarly when using a mobile phone while driving. However, male drivers using their mobile phone drive at lower speeds than female drivers not using their mobile phones. Sensitivity analysis revealed that, among all explanatory variables, the effect of mobile phone use on speed was most important. Accordingly, vehicle headways appear to increase for drivers using their mobile phone. However, this effect could not be statistically validated, due to the strong correlation between speed and headway.     

Characterization and comparison of traffic flow on reversible roadways

Reversible traffic operations have become an increasingly popular strategy for mitigating traffic congestion associated with the directionally unbalanced traffic flows that are a routine part of peak commute periods, planned special events, and emergency evacuations. It is interesting that despite its widespread and long‐term use, relatively little is known about the operational characteristics of this form of operation. For example, the capacity of a reversed lane has been estimated by some to be equal to that of a normal lane while others have theorized it to be half of this value. Without accurate estimates of reversible lane performance it is not possible to confidently gauge the benefits of reversible roadways or model them using traffic simulation. This paper presents the results of a study to measure and evaluate the speed and flow characteristics of reverse‐flow traffic streams by comparing them under various operating conditions and locations. It was found that, contrary to some opinions, the flow characteristics of reverse‐flowing lanes were generally similar to normally flowing lanes under a variety of traffic volume, time‐of‐day, location, and type‐of‐use conditions. The study also revealed that drivers will readily use reversible lanes without diminished operating speeds, particularly as volumes increase. Copyright © 2010 John Wiley & Sons, Ltd.     

临时关闭道路以疏导城市道路交通流的可行性分析

文章基于Braess悖论,以单位车辆的平均出行时间为最优目标,以网络道路系统为约束条件,从逆向思维角度建立了通过临时关闭道路引导交通流以缓解城市道路交通拥挤的Narsh均衡非线性规划模型,并以北京二环道路网络为研究对象进行了实例分析。结果表明,在城市道路网中,关闭部分路段并不能明显缓解交通拥堵现状,但可以在不影响路网整体通行时间的条件下改善路网局部拥堵状况。建议城市道路交通临时疏导方案应该根据路网交通流的分布特点和道路通过能力等因素进行制订。     

Safety in the road environment: a driver behavioural response perspective

The existing literature on road safety suggests that a driver's perception of safety is an important influence on their driving behaviour. A challenging research question is how to measure the perception of safety given the complex interactions among drivers, vehicles and the road setting. In this paper, we investigate a sample of driver evaluations of the perception of safety associated with a set of typical road environments. A roundabout was selected as the context for the empirical study. Data was obtained by a computerised survey using the video-captured road and traffic situations. A controlled experiment elicited driver responses when faced with a mixture of attributes that describe the roundabout environment. An ordered probit model identified the contribution of each attribute to the overall determination of the perception of safety. An indicator of perceived safety was developed for a number of typical road and traffic situations and for different driver segments.     

A model for assessing the effects of dynamic travel time information via variable message signs

In view of the serious traffic congestion during peak hours in most metropolitan areas around the world and recent improvement of information technology, there is a growing aspiration to alleviate road congestion by applications of electronic information and communication technology. Providing drivers with dynamic travel time information such as estimated journey times on major routes should help drivers to select better routes and guide them to utilise existing expressway network. This can be regarded as one possible strategy for effective traffic management. This paper aims to investigate the effects and benefits of providing dynamic travel time information to drivers via variable message signs at the expressway network. In order to assess the effects of the dynamic driver information system with making use of the variable message signs, a time-dependent traffic assignment model is proposed. A numerical example is used to illustrate the effects of the dynamic travel time information via variable message signs. This revised version was published online in June 2006 with corrections to the Cover Date.