Forecasting road traffic and its significance for transport policy

2019 ◽  
pp. 153-176
Author(s):  
Phil Goodwin

Traffic forecasting developed initially to decide how much road capacity to provide, but early methods tended to underestimate the growth. The methods were changed but then from the late 1980s systematically overestimated traffic growth, distorting the appraisal of benefits, and transforming the policy implications: it became evident that no feasible road capacity expansion would be enough to cope with the forecast traffic, and it would be necessary to manage demand instead. Since 2015 the official forecasts have sensibly avoided specifying a ‘most probable’ future, replacing it with a variety of different possibilities from almost no growth to exceedingly high. This creates a framework for a much more useful type of policy appraisal, though practical road proposals mostly still confidently assert high traffic growth at levels which have not been seen for over 25 years.

2012 ◽  
Vol 33 ◽  
pp. 1105-1110 ◽  
Author(s):  
Dancheng Li ◽  
Zhiliang Liu ◽  
Cheng Liu ◽  
Binsheng Liu ◽  
Wei Zhang

2021 ◽  
Vol 03 (01) ◽  
pp. 17-24
Author(s):  
Nadia Slimani ◽  
Ilham Slimani ◽  
Nawal Sbiti ◽  
Mustapha Amghar

Traffic forecasting is a research topic debated by several researchers affiliated to a range of disciplines. It is becoming increasingly important given the growth of motorized vehicles on the one hand, and the scarcity of lands for new transportation infrastructure on the other. Indeed, in the context of smart cities and with the uninterrupted increase of the number of vehicles, road congestion is taking up an important place in research. In this context, the ability to provide highly accurate traffic forecasts is of fundamental importance to manage traffic, especially in the context of smart cities. This work is in line with this perspective and aims to solve this problem. The proposed methodology plans to forecast day-by-day traffic stream using three different models: the Multilayer Perceptron of Artificial Neural Networks (ANN), the Seasonal Autoregressive Integrated Moving Average (SARIMA) and the Support Machine Regression (SMOreg). Using those three models, the forecast is realized based on a history of real traffic data recorded on a road section over 42 months. Besides, a recognized traffic manager in Morocco provides this dataset; the performance is then tested based on predefined criteria. From the experiment results, it is clear that the proposed ANN model achieves highest prediction accuracy with the lowest absolute relative error of 0.57%.


2021 ◽  
Author(s):  
Corinna Peters

This study assesses changes in mobility behaviour in the City of Barcelona due the COVID‐19pandemic and its impact on air pollution and GHG emissions. Urban transport is an important sourceof global greenhouse gas (GHG) emissions. Improving urban mobility patterns is therefore crucial formitigating climate change. This study combines quantitative survey data and official governmentdata with in‐depth interviews with public administration officials of the City. Data illustrates thatBarcelona has experienced an unprecedented reduction in mobility during the lockdown (a 90%drop) and mobility remained at comparatively low levels throughout the year 2020. Most remarkableis the decrease in the use of public transport in 2020 compared to pre‐pandemic levels, whereas roadtraffic has decreased to a lesser extent and cycling surged at times to levels up to 60% higher thanpre‐pandemic levels. These changes in mobility have led to a radical and historic reduction in airpollution, with NO2 and PM10 concentration complying with WHO guidelines in 2020. Reductions inGHG emissions for Barcelona’s transport sector are estimated at almost 250.000 t CO2eq in 2020 (7%of the City’s overall annual emissions). The study derives policy implications aimed at achieving along‐term shift towards climate‐friendlier, low‐emission transport in Barcelona, namely how torecover lost demand in public transport and seize the opportunity that the crisis brings for reform byfurther reducing road traffic and establishing a 'cycling culture' in Barcelona, as already achieved inother European cities.


Energy Policy ◽  
2018 ◽  
Vol 115 ◽  
pp. 109-118 ◽  
Author(s):  
Hoda Talebian ◽  
Omar E. Herrera ◽  
Martino Tran ◽  
Walter Mérida

2018 ◽  
Vol 10 (2) ◽  
pp. 93-109 ◽  
Author(s):  
Ibai Lana ◽  
Javier Del Ser ◽  
Manuel Velez ◽  
Eleni I. Vlahogianni

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