Spatial econometrics models for congestion prediction with in-vehicle route guidance

This study explores the congestion dependence relationship among links using microsimulation, based on data from a real road network. The work is motivated by recent innovations to improve the reliability of Dynamic Route Guidance (DRG) systems. The reliability of DRG systems can be significantly enhanced by adding a function to predict the congestion in the road network. This paper also talks about the application of spatial econometrics modelling to congestion prediction, by using historical Traffic Message Channel (TMC) data stored in the vehicle navigation unit. The nature of TMC data is in the form of a time series of geo-referenced congestion warning messages which is generally collected from various traffic sources. The prediction of future congestion could be based on the previous year of TMC data. Synthetic TMC data generated by microscopic traffic simulation for the network of Coventry are used in this study. The feasibility of using spatial econometrics modelling techniques to predict congestion is explored. Results are presented at the end

Measuring cycle riding comfort in Southampton using an instrumented bicycle

The increased environmental awareness and the rising fuel costs make bicycles a more and more attractive mode of travel for short journeys. Considering the future prospect of this mode of transportation and the great advantages that it offers in terms of space consumption, health and environmental sustainability, several city authorities worldwide are presently undertaking schemes aiming at improving cycling infrastructure. The aim of the present study is to monitor the impact of such schemes on the riding comfort of cyclists, as expressed by the, usually lower, quantity and magnitude of vibrations occurring as a result of cycling over pavement defects. Millbrook Road East in the western edge of the city center of Southampton is used as a case study, where vibration measurements are taken by means of an instrumented bicycle during periods before and after a redevelopment scheme involving the resurfacing of the road pavement. The results show a clear overall improvement in cycling comfort post-redevelopment, with statistically significant reductions in both the number of high severity vibrations and of their magnitude in "typical" cycling trips taken on the road. However, instances of finishing "snags" in some parts of the surface appear to introduce new minor defects (e.g. around manholes) that are not visible to the naked eye, and these still have some negative effect on the riding experience. Moreover, the study highlights the detrimental impact that widespread pavement defects can have on riding comfort, which affect cyclists of all ages, abilities and styles

London Congestion Charging: Successes, Gaps and Future Opportunities Offered by Cooperative ITS

The London Congestion Charging (LCC) scheme was initially introduced on 17 February 2003. Being the largest of its kind and employing advanced technology, it marked a major innovation in the field of urban road user charging and provided inspiration to several other cities worldwide. Nine years on, and following a number of operational changes that have taken place, this study analyzes successes and pitfalls, and identifies potential future opportunities in the light of latest technological developments in the field of cooperative Intelligent Transport Systems (ITS). The analysis concentrates primarily on the LCC scheme itself, but draws broader conclusions about the future of urban road charging in general

Analysing passenger arrivals rates and waiting time at bus stops

The present study investigates the rather under-explored topic of passenger waiting times at public transport facilities. Using data collected from part of London’s bus network by means of physical counts, measurements and observations, and complemented by on-site passenger interviews, the waiting behaviour is analysed for a number of bus stops served by different numbers of lines. The analysis employs a wide range of statistical methods and tools, and concentrates on three aspects: passenger interarrival time, passenger actual waiting time, and passenger perceived waiting time. The results suggest that there is a clear difference in terms of the passenger arrivals rate between stops served by up to two lines and stops served by three lines or more, as it appears that passengers in the former time their arrival at the stop to coincide with bus arrivals as much as possible. Also, it is found that waiting time at such stops is best approximated by the exponential distribution, with the gamma distribution also offering an adequate fit. Finally, as concerns the passengers’ perception of waiting time, it is found that this follows a lognormal or a gamma distribution, and generally overestimates the actual waiting time; however, this effect fades as the actual waiting time increases

A descriptive study on public transport user behaviour from Live Bus Arrivals

In order to offer public transport that meet citizens’ needs for transport and further increase the use of bus services, Public Authorities need to analyse and understand travellers behaviour. Automatic Vehicle Location (AVL) data provide information on the observed time of arrival and departure of a bus at each stop. These data are fed into an algorithm to provide information to users on the expected time of arrival at the bus stop by an on-line service. In the city of London this service is called Live Bus Arrivals. This work describes the general behaviour of Live Bus Arrivals users by analysing the type of requests, localising them and compare them in different days of the week and time ranges. The objective is to identify some of the main passengers’ origin, destination and interchanges behaviour that could be of value to decision-makers and planners

Development and testing of a prototype instrumented bicycle model for the prevention of cyclist accidents

Cycling is an increasingly popular mode of travel in cities owing to the great advantages that it offers in terms of space consumption, health and environmental sustainability, and is therefore favoured and promoted by many city authorities worldwide. However, cycling is also perceived as relatively unsafe, and therefore it has yet to be adopted as a viable alternative to the private car. Rising accident numbers, unfortunately, confirm this perception as reality, with a particular source of hazard (and a significant proportion of collisions) appearing to originate from the interaction of cyclists with Heavy Vehicles (HVs). This paper introduces Cyclist 360° Alert, a novel technological solution aimed at tackling this problem and ultimately improving the safety of cyclists and promoting it to non-riders. Following a thorough review of the trends of cyclist collisions, which sets the motivation of the research, the paper goes on to present the Cyclist 360° Alert system architecture design, and examines possible technologies and techniques that can be employed in the accurate positioning of cyclists and vehicles. It then focuses in particular on the aspect of bicycle tracking, and proposes a localisation approach based on micro-electromechanical systems (MEMS) sensor configurations. Initial experimental results from a set of controlled experiments using a purpose-developed prototype bicycle simulator model, are reported, and conclusions on the applicability of specific sensor configurations are drawn, both in terms of sensor accuracy and reliability in taking sample measurements of motion

Reliable dynamic in-vehicle navigation

Having started off from luxury makes and models, in-vehicle navigation systems are now gradually spreading through the entire vehicle fleet, as drivers appreciate their usefulness. Increasingly sophisticated systems are being developed, having much more advanced functions than simple driving directions. This thesis presents a new approach for in-vehicle navigation, in which travel time reliability is incorporated in the route finding component of the navigation system. Based on historical traffic data and in the absence of current traffic information, positions in the road network at which it is likely to encounter delays, are predicted and avoided as much as possible by the route finding algorithm. The thesis starts by reviewing shortest path algorithms and conjectures that the most appropriate algorithm to use is A*, which forms a vital part of the approach developed. Performing multiple runs of A* forwards and backwards on the road network, efficiency of the route finding procedure is achieved. The time-dependent version of the algorithm is also derived. Then, the thesis goes on to define reliability on a single link of the road network as the maximum delay that can be encountered with 90% confidence and extends this definition to derive the reliability of entire routes. Having introduced the route finding procedure and the concept of reliability, the thesis presents the in-vehicle navigation approach, which involves computing a more reliable route from the driver's origin to his/her destination than the fastest, if this is unreliable. Additionally, the approach aims at computing multiple alternative partially disjoint but equivalently reliable routes to the driver, such that the congestion feedback effect can be avoided as much as possible, without the need of carrying out a dynamic traffic assignment, which would be impracticable in an in-vehicle system. A number of constraints are introduced so as to ensure that the resulting routes are acceptable to the driver (are not too long, etc). Hence, the main concept lies in initially computing the fastest time-dependent route, then applying penalties to the links characterised as unreliable (increasing the link weights in inverse proportion to their reliability) and re-running the route finding algorithm so as to find a more reliable route. After each run, the route obtained is checked against the constraints and if it does not satisfy them, it is discarded, the penalties are reduced and a new route is sought. In order to obtain alternative partially disjoint routes, penalties are also applied to links that are already included in a previously computed and accepted route. The new algorithm, RDIN, is thus presented and mathematically formulated. An extension to RDIN for re-routing, RDIN-R, is also developed. The software tool developed for the application of RDIN and RDIN-R, the Adaptive Reliable Imperial Advanced Navigation Engine (ARIAdNE) is described. A simulation example is given for demonstration and preliminary validation; then a number of field experiments are carried out in Central London to test the method in a real road network environment and to compare its performance with an existing conventional car navigation system. The results suggest that the method is workable and precise, while at the same time it is a promising step forward in the field of in-vehicle navigation

An Innovative Multi-Sensor Fusion Algorithm to Enhance Positioning Accuracy of an Instrumented Bicycle

Cycling is an increasingly popular mode of travel in cities, but its poor safety record currently acts as a hurdle to its wider adoption as a real alternative to the private car. A particular source of hazard appears to originate from the interaction of cyclists with motorized traffic at low speeds in urban areas. But while technological advances in recent years have resulted in numerous attempts at systems for preventing cyclist-vehicle collisions, these have generally encountered the challenge of accurate cyclist localization. This paper addresses this challenge by introducing an innovative bicycle localization algorithm, which is derived from the geometrical relationships and kinematics of bicycles. The algorithm relies on the measurement of a set of kinematic variables (such as yaw, roll, and steering angles) through low-cost on-board sensors. It then employs a set of Kalman filters to predict-correct the direction and position of the bicycle and fuse the measurements in order to improve positioning accuracy. The capabilities of the algorithm are then demonstrated through a real-world field experiment using an instrumented bicycle, called ``iBike'', in an urban environment. The results show that the proposed fusion achieves considerably lower positioning errors than that would be achieved based on dead-reckoning alone, which makes the algorithm a credible basis for the development of future collision warning and avoidance systems

A framework for user- and system-oriented optimisation of fuel efficiency and traffic flow in Adaptive Cruise Control

Fully automated vehicles could have a significant share of the road network traffic in the near future. Several commercial vehicles with full-range Adaptive Cruise Control (ACC) systems or semi-autonomous functionalities are already available on the market. Many research studies aim at leveraging the potential of automated driving in order to improve the fuel efficiency of vehicles. However, in the vast majority of those, fuel efficiency is isolated to the driving dynamics between a single follower-leader pair, hence overlooking the complex nature of traffic. Consequently fuel efficiency and the efficient use of the roadway capacity are framed as conflicting objectives, leading to fuel-economy control models that adopt highly conservative driving styles. This formulation of the problem could be seen as a user-optimal approach, where in spite of delivering savings for individual vehicles, there is the side-effect of the deterioration of traffic flow. An important point that is overlooked is that the inefficient use of roadway capacity gives rise to congested traffic and traffic breakdowns, which in return increases energy costs within the system. The optimisation methods used in these studies entail high computational costs and, therefore, impose a strict constraint on the scope of problem. In this study, the use of car-following models and the limitation of the search space of optimal strategies to the parameter space of these is proposed. The proposed framework enables performing much more comprehensive optimisations and conducting more extensive tests on the collective impacts of fuel-economy driving strategies. The results show that, as conjectured, a “short-sighted” user-optimal approach is unable to deliver overall fuel efficiency. Conversely, a system-optimal formulation for fuel efficient driving is presented, and it is shown that the objectives of fuel efficiency and traffic flow are in fact not only non-conflicting, but also that they could be viewed as one when the global benefits to the network are considered

Testing a reliable in-vehicle navigation algorithm in the field

The results of a field experiment carried out to assess the accuracy and efficiency of a new in-vehicle navigation algorithm, whose aim is to incorporate and consider travel time reliability and route the guided vehicle along uncongested roads, in the absence of real-time traffic information are presented. Using historical travel time profiles deduced from floating vehicle data, the algorithm is implemented in a purpose-developed software tool and tested in the London Congestion Charging Zone. The experiment consists of driving a vehicle along routes computed by the algorithm and comparing the outcome with that of a conventional navigation system installed in a second vehicle. The results indicate that the new algorithm outperforms the conventional system in most cases, thus suggesting that it is a step forward towards a more intelligent navigation system