Development of accident prediction models for rural highway intersections

A study was done to develop macrolevel crash prediction models that can be used to understand and identify effective countermeasures for improving signalized highway intersections and multilane stop-controlled highway intersections in rural areas. Poisson and negative binomial regression models were fit to intersection crash data from Georgia, California, and Michigan. To assess the suitability of the models, several goodness-of-fit measures were computed. The statistical models were then used to shed light on the relationships between crash occurrence and traffic and geometric features of the rural signalized intersections. The results revealed that traffic flow variables significantly affected the overall safety performance of the intersections regardless of intersection type and that the geometric features of intersections varied across intersection type and also influenced crash type.

Evaluation of the Scottsdale Loop 101 automated speed enforcement demonstration program

Speeding is recognized as a major contributing factor in traffic crashes. In order to reduce speed-related crashes, the city of Scottsdale, Arizona implemented the first fixed-camera photo speed enforcement program (SEP) on a limited access freeway in the US. The 9-month demonstration program spanning from January 2006 to October 2006 was implemented on a 6.5 mile urban freeway segment of Arizona State Route 101 running through Scottsdale. This paper presents the results of a comprehensive analysis of the impact of the SEP on speeding behavior, crashes, and the economic impact of crashes. The impact on speeding behavior was estimated using generalized least square estimation, in which the observed speeds and the speeding frequencies during the program period were compared to those during other periods. The impact of the SEP on crashes was estimated using 3 evaluation methods: a before-and-after (BA) analysis using a comparison group, a BA analysis with traffic flow correction, and an empirical Bayes BA analysis with time-variant safety. The analysis results reveal that speeding detection frequencies (speeds> or =76 mph) increased by a factor of 10.5 after the SEP was (temporarily) terminated. Average speeds in the enforcement zone were reduced by about 9 mph when the SEP was implemented, after accounting for the influence of traffic flow. All crash types were reduced except rear-end crashes, although the estimated magnitude of impact varies across estimation methods (and their corresponding assumptions). When considering Arizona-specific crash related injury costs, the SEP is estimated to yield about $17 million in annual safety benefits.

Arterial travel time estimation : revisiting the classical procedure

Travel time is an important network performance measure and it quantifies congestion in a manner easily understood by all transport users. In urban networks, travel time estimation is challenging due to number of reasons such as, fluctuations in traffic flow due to traffic signals, significant flow to/from mid link sinks/sources, etc. The classical analytical procedure utilizes cumulative plots at upstream and downstream locations for estimating travel time between the two locations. In this paper, we discuss about the issues and challenges with classical analytical procedure such as its vulnerability to non conservation of flow between the two locations. The complexity with respect to exit movement specific travel time is discussed. Recently, we have developed a methodology utilising classical procedure to estimate average travel time and its statistic on urban links (Bhaskar, Chung et al. 2010). Where, detector, signal and probe vehicle data is fused. In this paper we extend the methodology for route travel time estimation and test its performance using simulation. The originality is defining cumulative plots for each exit turning movement utilising historical database which is self updated after each estimation. The performance is also compared with a method solely based on probe (Probe-only). The performance of the proposed methodology has been found insensitive to different route flow, with average accuracy of more than 94% given a probe per estimation interval which is more than 5% increment in accuracy with respect to Probe-only method.

Benefits and issues of urban network travel time prediction

This paper presents the benefits and issues related to travel time prediction on urban network. Travel time information quantifies congestion and is perhaps the most important network performance measure. Travel time prediction has been an active area of research for the last five decades. The activities related to ITS have increased the attention of researchers for better and accurate real-time prediction of travel time. Majority of the literature on travel time prediction is applicable to freeways where, under non-incident conditions, traffic flow is not affected by external factors such as traffic control signals and opposing traffic flows. On urban environment the problem is more complicated due to conflicting areas (intersections), mid-link sources and sinks etc. and needs to be addressed.

Sustainable urban transport : smart technology initiatives in Singapore

Achieving sustainability is one of the major goals of many urban transportation systems. Over the years, many innovative policies have been attempted to achieve an efficient, safe, and sustainable transport system. Those policies often require smart technologies to assist implementation process and enhance effectiveness. This paper discusses how sustainability can be promoted by embedding smart technologies in a modern transportation system. In particular, this paper studies the transport system of Singapore to address how this system is addressing sustainability through the use of smart technologies. Various technological initiatives in managing traffic flow, monitoring and enforcement, sharing real-time information, and managing revenues are discussed in light of their potentiality in addressing sustainability issues. The Singapore experience provides a useful reference for the cities intending to develop and promote a sustainable transport system.

Large area noise evaluation

A software tool (DRONE) has been developed to evaluate road traffic noise in a large area with the consideration of network dynamic traffic flow and the buildings. For more precise estimation of noise in urban network where vehicles are mainly in stop and go running conditions, vehicle sound power level (for acceleration/deceleration cruising and ideal vehicle) is incorporated in DRONE. The calculation performance of DRONE is increased by evaluating the noise in two steps of first estimating the unit noise database and then integrating it with traffic simulation. Details of the process from traffic simulation to contour maps are discussed in the paper and the implementation of DRONE on Tsukuba city is presented.

Comparison and modification of car following models toward a more accurate microscopic simulation parameters reproduction

Traffic safety studies demand more than what current micro-simulation models can provide as they presume that all drivers of motor vehicles exhibit safe behaviours. Several car-following models are used in various micro-simulation models. This research compares the mainstream car following models’ capabilities of emulating precise driver behaviour parameters such as headways and Time to Collisions. The comparison firstly illustrates which model is more robust in the metric reproduction. Secondly, the study conducted a series of sensitivity tests to further explore the behaviour of each model. Based on the outcome of these two steps exploration of the models, a modified structure and parameters adjustment for each car-following model is proposed to simulate more realistic vehicle movements, particularly headways and Time to Collision, below a certain critical threshold. NGSIM vehicle trajectory data is used to evaluate the modified models performance to assess critical safety events within traffic flow. The simulation tests outcomes indicate that the proposed modified models produce better frequency of critical Time to Collision than the generic models, while the improvement on the headway is not significant. The outcome of this paper facilitates traffic safety assessment using microscopic simulation.

Effects of average speed enforcement on speed compliance and crashes : a review of the literature

Average speed enforcement is a relatively new approach gaining popularity throughout Europe and Australia. This paper reviews the evidence regarding the impact of this approach on vehicle speeds, crashes rates and a number of additional road safety and public health outcomes. The economic and practical viability of the approach as a road safety countermeasure is also explored. A literature review, with an international scope, of both published and grey literature was conducted. There is a growing body of evidence to suggest a number of road safety benefits associated with average speed enforcement, including high rates of compliance with speed limits, reductions in average and 85th percentile speeds and reduced speed variability between vehicles. Moreover, the approach has been demonstrated to be particularly effective in reducing excessive speeding behaviour. Reductions in crash rates have also been reported in association with average speed enforcement, particularly in relation to fatal and serious injury crashes. In addition, the approach has been shown to improve traffic flow, reduce vehicle emissions and has also been associated with high levels of public acceptance. Average speed enforcement offers a greater network-wide approach to managing speeds that reduces the impact of time and distance halo effects associated with other automated speed enforcement approaches. Although comparatively expensive it represents a highly reliable approach to speed enforcement that produces considerable returns on investment through reduced social and economic costs associated with crashes.

Data requirements and graph data structures for a multi-modal, multi-objective trip planner

Traffic congestion has a significant impact on the economy and environment. Encouraging the use of multimodal transport (public transport, bicycle, park’n’ride, etc.) has been identified by traffic operators as a good strategy to tackle congestion issues and its detrimental environmental impacts. A multi-modal and multi-objective trip planner provides users with various multi-modal options optimised on objectives that they prefer (cheapest, fastest, safest, etc) and has a potential to reduce congestion on both a temporal and spatial scale. The computation of multi-modal and multi-objective trips is a complicated mathematical problem, as it must integrate and utilize a diverse range of large data sets, including both road network information and public transport schedules, as well as optimising for a number of competing objectives, where fully optimising for one objective, such as travel time, can adversely affect other objectives, such as cost. The relationship between these objectives can also be quite subjective, as their priorities will vary from user to user. This paper will first outline the various data requirements and formats that are needed for the multi-modal multi-objective trip planner to operate, including static information about the physical infrastructure within Brisbane as well as real-time and historical data to predict traffic flow on the road network and the status of public transport. It will then present information on the graph data structures representing the road and public transport networks within Brisbane that are used in the trip planner to calculate optimal routes. This will allow for an investigation into the various shortest path algorithms that have been researched over the last few decades, and provide a foundation for the construction of the Multi-modal Multi-objective Trip Planner by the development of innovative new algorithms that can operate the large diverse data sets and competing objectives.

Enlarged stopping distance to improve vehicle discharge at urban signalised intersections

Normally, vehicles queued at an intersection reach maximum flow rate after the fourth vehicle and results in a start-up lost time. This research demonstrated that the Enlarged Stopping Distance (ESD) concept could assist in reducing the start-up time and therefore increase traffic flow capacity at signalised intersections. In essence ESD gives sufficient space for a queuing vehicle to accelerate simultaneously without having to wait for the front vehicle to depart, hence reducing start-up lost time. In practice, the ESD concept would be most effective when enlarged stopping distance between the first and second vehicle allowing faster clearance of the intersection.

Crisis response planning in tunnel and road networks

Critical road infrastructure (such as tunnels and overpasses) is of major significance to society and constitutes major components of interdependent, ‘systems and networks’. Failure in critical components of these wide area infrastructure systems can often result in cascading disturbances with secondary and tertiary impacts - some of which may become initiating sources of failure in their own right, triggering further systems failures across wider networks. Perrow1) considered the impact of our increasing use of technology in high-risk fields, analysing the implications on everyday life and argued that designers of these types of infrastructure systems cannot predict every possible failure scenario nor create perfect contingency plans for operators. Challenges exist for transport system operators in the conceptualisation and implementation of response and subsequent recovery planning for significant events. Disturbances can vary from reduced traffic flow causing traffic congestion throughout the local road network(s) and subsequent possible loss of income to businesses and industry to a major incident causing loss of life or complete loss of an asset. Many organisations and institutions, despite increasing recognition of the effects of crisis events, are not adequately prepared to manage crises2). It is argued that operators of land transport infrastructure are in a similar category of readiness given the recent instances of failures in road tunnels. These unexpected infrastructure failures, and their ultimately identified causes, suggest there is significant room for improvement. As a result, risk profiles for road transport systems are often complex due to the human behaviours and the inter-mix of technical and organisational components and the managerial coverage needed for the socio-technical components and the physical infrastructure. In this sense, the span of managerial oversight may require new approaches to asset management that combines the notion of risk and continuity management. This paper examines challenges in the planning of response and recovery practices of owner/operators of transport systems (above and below ground) in Australia covering: • Ageing or established infrastructure; and • New-build infrastructure. With reference to relevant international contexts this paper seeks to suggest options for enhancing the planning and practice for crisis response in these transport networks and as a result support the resilience of Critical Infrastructure.

Towards the retrieval of accurate OD matrices from Bluetooth data : lessons learned from 2 years of data

The Bluetooth technology is being increasingly used to track vehicles throughout their trips, within urban networks and across freeway stretches. One important opportunity offered by this type of data is the measurement of Origin-Destination patterns, emerging from the aggregation and clustering of individual trips. In order to obtain accurate estimations, however, a number of issues need to be addressed, through data filtering and correction techniques. These issues mainly stem from the use of the Bluetooth technology amongst drivers, and the physical properties of the Bluetooth sensors themselves. First, not all cars are equipped with discoverable Bluetooth devices and the Bluetooth-enabled vehicles may belong to some small socio-economic groups of users. Second, the Bluetooth datasets include data from various transport modes; such as pedestrian, bicycles, cars, taxi driver, buses and trains. Third, the Bluetooth sensors may fail to detect all of the nearby Bluetooth-enabled vehicles. As a consequence, the exact journey for some vehicles may become a latent pattern that will need to be extracted from the data. Finally, sensors that are in close proximity to each other may have overlapping detection areas, thus making the task of retrieving the correct travelled path even more challenging. The aim of this paper is twofold. We first give a comprehensive overview of the aforementioned issues. Further, we propose a methodology that can be followed, in order to cleanse, correct and aggregate Bluetooth data. We postulate that the methods introduced by this paper are the first crucial steps that need to be followed in order to compute accurate Origin-Destination matrices in urban road networks.

Safety at railway level crossings : driver acceptance of potential ITS interventions

There is a continuing need to improve safety at Railway Level Crossings (RLX) particularly those that do not have gates and lights regulating traffic flow. A number of Intelligent Transport System (ITS) interventions have been proposed to improve drivers’ awareness and reduce errors in detecting and responding appropriately at level crossings. However, as with other technologies, successful implementation and ultimately effectiveness rests with the acceptance of the technology by the end user. In the current research, four focus groups were held (n=38) with drivers in metropolitan and regional locations in Queensland to examine their perceptions of potential in-vehicle and road-based ITS interventions to improve safety at RLX. The findings imply that further development of the ITS interventions, in particular the design and related promotion of the final product, must consider ease of use, usefulness and relative cost.

Effectiveness of eco-driving during queue discharge at urban signalised intersections

This research investigated the effectiveness of using an eco-driving strategy at urban signalised intersections from both the individual driver and the traffic flow perspective. The project included a field driving experiment and a series of traffic simulation investigations. The study found that the prevailing eco-driving strategy has negative impacts on traffic mobility and environmental performance when the traffic is highly congested. An improved eco-driving strategy has been developed to mitigate these negative impacts.

Point-to-point speed enforcement : recommendations for better practice

Point-to-point speed cameras are a relatively new and innovative technological approach to speed enforcement that is increasingly been used in a number of highly motorised countries. Previous research has provided evidence of the positive impact of this approach on vehicle speeds and crash rates, as well as additional traffic related outcomes such as vehicle emissions and traffic flow. This paper reports on the conclusions and recommendations of a large-scale project involving extensive consultation with international and domestic (Australian) stakeholders to explore the technological, operational, and legislative characteristics associated with the technology. More specifically, this paper provides a number of recommendations for better practice regarding the implementation of point-to-point speed enforcement in the Australian and New Zealand context. The broader implications of the research, as well as directions for future research, are also discussed.