Using satellite images to asses the effect of road lighting on the number of road accidents

Traffic safety represents an important research topic in transportation. The correlation between the risk of accident and road lighting is well known in literature. For example, Per Ole Wanvik estimated that on average the reduction of injury accident during darkness is around 30% in areas with road lighting. Some other studies analyzed the influence of road lighting on traffic safety on highways or in intersections. A common approach in such evaluations is to compare the number of accidents occurring in the daytime with the ones occurring in the nighttime. The presented work is not limited to a particular road type and consider most of the roads in Denmark. The analysis is based on a comparison of the number of nighttime accidents occurring in roads with different light intensity levels, accounting also for road type and flow. Moreover, this study introduces a new method to evaluate the intensity of road lighting throughout the use of satellite images. In literature, the use of satellite image in traffic safety is limited on analyzing road design or traffic volume

Vehicle Delay-Driven Passenger Delay Modelling: An Agent-Based Copenhagen Case Study

Travel time of passengers is often uncertain due to lack of punctuality of public transport services. Whereas Automatic Vehicle Location (AVL) data makes it easy to measure the punctuality of public transport vehicles themselves, calculating door-to-door passenger punctuality is challenging, as both the intended and realised routes of passengers have to be considered. This study introduces a MATSim mesoscopic simulation framework for evaluating passenger punctuality caused by vehicle delays in the railway system in the metropolitan area of Copenhagen. Based upon empirical train delay data for 65 weekdays in the autumn of 2014, the model shows that passenger punctuality is considerably smaller than train punctuality, with 17.8% of the passengers using the railway system being delayed more than a minute compared to their intended plan

Using wearable GPS devices in travel surveys: A case study in the Greater Copenhagen Area

GPS data collection has become an important means of investigating travel behaviour, as it ideally provides far more detailed information than traditional travel survey methods. While setting fewer requirements to the respondents, it however sets high requirements to the post processing of the data collected. This study proposes a combined fuzzy logic‐ and GIS‐based algorithm to process raw GPS data. The algorithm is applied to GPS data collected in the highly complex Greater Copenhagen Area network and detects trip legs and distinguishes between five modes of transport. The algorithm shows promising results by (i) identifying trip legs for 82% of the reported trip legs, (ii) not classifying non‐trips such as scatter around activities as trip legs and (iii) identifying the correct mode of transport in more than 90% of trip legs for which corresponding observed modes are available

Motivators to participate in the Danish bike-to-work campaign

The current study investigates the success of the Danish bike-to-work campaign (Vi cycler til arbejde), a best practice example of the Danish planning approach promoting modal shift with a shared vision, and innovative self-sustaining institutional programs and business solutions. Rather than relying on tax exemptions or subsidiaries, the campaign largely depends on its ability to cater for people’s functional and emotional needs. Therefore the present study focuses on the role of existence, relatedness and growth in encouraging participation in the campaign. A behavioural framework was formulated, and data collected from an online survey developed during the study was used to validate the framework and estimate corresponding mathematical models. Results indicate that (i) growth needs are positively influenced by existence and relatedness needs (ii) participation is positively related to self-actualization and negatively related to perceived cycling difficulties, (iii) social norms and bonding are a stronger contributor to competitiveness than fitness or health needs, (iv) firm’s consistent participation in the campaign over several years is an important factor in the participation of its employees, (v) cycling experience is positively associated with less perceived difficulties, and (vi) needs are positively associated with cycling habits on weekdays/weekends, the availability of a mountain bike/BMX and recreational and utilitarian cycling purposes

Joint modeling of schedule- and frequency-based services in public transport assignment models

Public transport networks today are getting increasingly complex with many lines and possibilities to go from origin to destination. When passengers make their route choice in a public transport network they cannot depart at the minute they want, but must wait until the first departure on the considered line. But how do passengers plan their route if they have a combination of high frequent and low frequent services under the assumption that passengers do not consult the timetable for high frequent services? This paper describes a framework to include both schedule- and frequency-based services in a joint model. Such networks are found in most major cities and especially in the greater Copenhagen area where there is a mix of frequency-based services such as A-busses and the metro and schedule-based services as the S-train and local bus lines. Four different transfer types are identified when transferring between schedule- and frequency-based services. These include a type where the passenger transfers from a frequency-based to a schedule-based line. In this case the passenger has a probability to reach the first departure on the schedule- based line, but can in some cases also miss the first departure and must wait for the next departure. A choice set generation method is developed using the event dominance principle to exclude alternatives which are above a certain threshold. This gives a choice set which is used in a discrete choice model (MNL). On this basis, it is possible to distribute the flow across the different alternatives. Two example cases are used to show the methodology: DTU to Copenhagen Airport and DTU to Brønshøj. The results indicate that there the framework can handle the two types off lines. It is found that the desired departure time, parameters in the utility function and the choice of threshold is crucial to find the correct choice set and distribution of flow across the alternatives. But there is also found improvement points in the choice set generation technique, but especially the discrete choice modelling should be investigated further to include that passengers can take decisions en route