Learned Programme

For many of us  the experience of crossing at busy junctions makes us feel second class to those passing in front of us in motor vehicles. Although the Highway Code now places pedestrians at the top of the road user hierarchy, many junctions are yet to be upgraded to provide adequate pedestrian priority and still largely focus on the movement of vehicles. But how can pedestrians be given greater priority without making congestion, and air quality, significantly worse? How can the needs of bus users be balanced with those of pedestrians? In this presentation we will draw upon examples from a range of authorities to illustrate how computer vision detection is enabling authorities to make more nuanced decisions about when to prioritise pedestrians whilst also minimising the impact on the network.

Awaiting Final Synopsis

In Rotherham, we were successful in securing nearly £600k in funding through the TSOG awarded by DfT. Using our existing Imtrac data, it was quickly realised that all of the asset along the A631 in Rotherham was life expired. The basis of our bid was to upgrade the obsolescent equipment along this route and try to future proof the route and make it ready to test equipment crucial to bringing Connected and Autonomous Vehicles (CAVS) to the region. Early contractor involvement meant the project was started in April 2024 and completed in November 2024!! Not only did we upgrade what we set out to do, we even found some hidden bounces! What were these? You’ll have to wait for the presentation! 

A look into how the largest roundabout in Plymouth overcame detection issues with smartmicro above ground sensors.

The Swansea Bay & West Wales Metro is a regional initiative aimed at providing reliable bus services across the South West Wales Authorities. By implementing traffic signal intelligence, the project seeks to enhance the speed and reliability of bus journeys, thereby reducing travel times across the region.

In line with the Department for Transport’s LTN 1/24: Bus User Priority guidance document, this paper outlines the approach taken by Swansea Council, in collaboration with AECOM, during the design and implementation stages of the Swansea Metro project. It details the research carried out for various technologies and innovative design processes enabling a comparison of Local & AVL bus priority systems.

In 2021, York became the first UK city to deploy real-time traffic modelling within its traffic management operations. The main benefit of this deployment was to fuse together live data from the city's assets such as: timings from signals connected to UTC; and traffic flow detection from loops and cameras, with city-wide floating vehicle data and a transport model to provide an accurate prediction of current and near-future traffic conditions. This information allows the city to be proactive in its approach to traffic management.

In 2024, the city has implemented a real-world pilot to automatically simulate alternative signal plans within the real-time model, and to send recommendations to the network management officers to implement via the UTC. The combination of automated simulations - triggered by user-defined thresholds and results from the near-future traffic predictions - and implementation of the plans recommended using a customisable scoring system, resulted in traffic delay reductions of up to 8% in the peaks. 

In our paper and presentation, we will explain the architecture of the system, present the results of the switch-on / switch-off test, and summarise the benefits and lessons learned from the pilot. We will also consider the options and potential benefits for city-wide rollout of such an approach.

Designers of traffic signal junctions spend plenty of time examining the theoretical capacity, but as the importance of active modes of travel increase do we fully understand how many people a new facility might serve?  This paper examines the theoretical capacity of a crossing phase to see how many pedestrians could cross in a single cycle, because there might be times when that is important.

The FLEX detector is a self-contained, stand-alone detector designed for traffic data collection, that requires no power and no side road cabinets. Based on advanced AI algorithms and models, provides exceptional performance and 99% accuracy. Data is sent to cloud based servers through a built-in LTE modem, and can be retrieved through a user friendly web interface or API. We'll present a case study from the Swedish Road Administration where the FLEX is used for capillary data acquisition in secondary and rural roads. 

A practitioner’s guide for incorporating passive safety into traffic signal designs, including dispelling myths and misconceptions, and the problems still to be faced.

This paper outlines a groundbreaking project led by Kirklees Council to control the flow of pedestrians and vehicles through a busy, multi-lane crossing in Huddersfield. Working with Starling Technologies, the Council are using predictive AI techniques to overcome pedestrian crowding and jaywalking at a central, high footfall location. This paper will present the baseline data and the understanding of crowd dynamics at the roadside. It will go on to detail the interventions put in place to adjust traffic and pedestrian flow during peak times, highlighting the impact on safety.