{"id":{"repo_id":"de-montfort","oai_identifier":"oai:dora.dmu.ac.uk:2086/25689"},"canonical_url":"https://search.dev.ndltd.org/etd/de-montfort/oai:dora.dmu.ac.uk:2086/25689","repository":{"repo_id":"de-montfort","name":"De Montfort University","base_url":"https://dora.dmu.ac.uk/server/oai/request"},"display":{"title":"Characterisation of vehicle drive cycles for peak hour traffic: implications for emissions modelling","abstract":"Local authorities arc responsible for maintaining air quality in urban areas and are assisted in this task by applying methods to estimate emissions from road transport. These methods are often reliant on the ‘average speed’ parameter. Evidence suggests that for large urban road networks this parameter is unrepresentative, particularly for peak hour periods. The aim of the research described was to investigate the characterisation of links with respect to measured driving cycles and physical link attributes, in order to assess whether link characterisation can assist in the prediction of emissions to the wider road net. Also, to examine vehicle emissions at the scale of individual roads for peak hour travel periods using two contrasting modelling approaches. A detailed investigation of the drive cycle data found that speed distributions, to be extremely complex, questioning the use of a single average speed to be representative of the reported variations. It was found that more appropriate speeds may be obtained, depending on link type, using speed distributions. Also, that speed distributions on the whole did not conform to standard probability functions and thus required the application of non-parametric analysis. The association between speed distributions and link type was assessed with respect to external characteristics. The findings showed that speed is particularly sensitive to link type (e.g., high streets) and link endings (e.g., traffic signals). A statistical technique to compare speed distributions across the field study network was developed to assess the variations of speed between link types. Emissions were predicted for a single passenger car using two contrasting modelling methodologies. It was found that MODEM (MOdelling of EMissions in urban areas) predicts emissions carbon monoxide, total hydrocarbons and nitrogen oxides to be significantly greater than that of the Screening Method developed for the Design Manual for Roads and Bridges (DMRB). The divergence between the models was due in part to emission functions on which each model is based. The results confirmed that the DMRB is not particularly sensitive to changes in speed, and questioned whether detailed speed measurements are advantageous when applying this approach. In terms of external characteristics, a significant relationship was identified between mean link emissions carbon monoxide and total hydrocarbons, founded on measured speed and links having 3-lanes, are high streets or those ending with a right signalled turn.","abstract_html":"Local authorities arc responsible for maintaining air quality in urban areas and are assisted in this task by applying methods to estimate emissions from road transport. These methods are often reliant on the ‘average speed’ parameter. Evidence suggests that for large urban road networks this parameter is unrepresentative, particularly for peak hour periods. The aim of the research described was to investigate the characterisation of links with respect to measured driving cycles and physical link attributes, in order to assess whether link characterisation can assist in the prediction of emissions to the wider road net. Also, to examine vehicle emissions at the scale of individual roads for peak hour travel periods using two contrasting modelling approaches. A detailed investigation of the drive cycle data found that speed distributions, to be extremely complex, questioning the use of a single average speed to be representative of the reported variations. It was found that more appropriate speeds may be obtained, depending on link type, using speed distributions. Also, that speed distributions on the whole did not conform to standard probability functions and thus required the application of non-parametric analysis. The association between speed distributions and link type was assessed with respect to external characteristics. The findings showed that speed is particularly sensitive to link type (e.g., high streets) and link endings (e.g., traffic signals). A statistical technique to compare speed distributions across the field study network was developed to assess the variations of speed between link types. Emissions were predicted for a single passenger car using two contrasting modelling methodologies. It was found that MODEM (MOdelling of EMissions in urban areas) predicts emissions carbon monoxide, total hydrocarbons and nitrogen oxides to be significantly greater than that of the Screening Method developed for the Design Manual for Roads and Bridges (DMRB). The divergence between the models was due in part to emission functions on which each model is based. The results confirmed that the DMRB is not particularly sensitive to changes in speed, and questioned whether detailed speed measurements are advantageous when applying this approach. In terms of external characteristics, a significant relationship was identified between mean link emissions carbon monoxide and total hydrocarbons, founded on measured speed and links having 3-lanes, are high streets or those ending with a right signalled turn.","abstract_has_math":false,"creators":["Turpin, Kevin"],"institution":"De Montfort University","degree_name":"PhD","degree_level":"Doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2004,"date_issued":"2004-06","date_published":"2004-06","updated_at":"2026-07-24T06:18:54Z","subjects":[],"languages":[],"rights":[],"rights_urls":["https://dora.dmu.ac.uk/bitstreams/18bbf814-1614-475c-a84e-fb66f9452c07/download"],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Turpin, Kevin"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2004-06"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Faculty of Technology, Arts and Culture"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["De Montfort University"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://hdl.handle.net/2086/25689"]},{"key":"dc:type","label":"Dc Type","values":["Thesis or dissertation"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["PhD"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["https://dora.dmu.ac.uk/bitstreams/18bbf814-1614-475c-a84e-fb66f9452c07/download"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://dora.dmu.ac.uk/bitstreams/4c8c6482-165c-48fe-b05d-ce7198c6e23d/download"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Local authorities arc responsible for maintaining air quality in urban areas and are assisted in this task by applying methods to estimate emissions from road transport. 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Also, that speed distributions on the whole did not conform to standard probability functions and thus required the application of non-parametric analysis. The association between speed distributions and link type was assessed with respect to external characteristics. The findings showed that speed is particularly sensitive to link type (e.g., high streets) and link endings (e.g., traffic signals). A statistical technique to compare speed distributions across the field study network was developed to assess the variations of speed between link types. Emissions were predicted for a single passenger car using two contrasting modelling methodologies. It was found that MODEM (MOdelling of EMissions in urban areas) predicts emissions carbon monoxide, total hydrocarbons and nitrogen oxides to be significantly greater than that of the Screening Method developed for the Design Manual for Roads and Bridges (DMRB). The divergence between the models was due in part to emission functions on which each model is based. The results confirmed that the DMRB is not particularly sensitive to changes in speed, and questioned whether detailed speed measurements are advantageous when applying this approach. In terms of external characteristics, a significant relationship was identified between mean link emissions carbon monoxide and total hydrocarbons, founded on measured speed and links having 3-lanes, are high streets or those ending with a right signalled turn."]},{"key":"dc:format.checksum.md5","label":"Dc Format Checksum Md5","values":["75e2fd9a6d2dbbb0ee0697ffdc341aeb","bd41181d9a4c38b5ebacc69a027024d9","df96b8b1c831100f8352a62f162f523c"]},{"key":"dc:title","label":"Title","values":["Characterisation of vehicle drive cycles for peak hour traffic: implications for emissions modelling"]}]}],"canonical_facts":{"dc:creator":["Turpin, Kevin"],"dc:date.issued":["2004-06"],"dc:description.abstract":["Local authorities arc responsible for maintaining air quality in urban areas and are assisted in this task by applying methods to estimate emissions from road transport. These methods are often reliant on the ‘average speed’ parameter. 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The association between speed distributions and link type was assessed with respect to external characteristics. The findings showed that speed is particularly sensitive to link type (e.g., high streets) and link endings (e.g., traffic signals). A statistical technique to compare speed distributions across the field study network was developed to assess the variations of speed between link types. Emissions were predicted for a single passenger car using two contrasting modelling methodologies. It was found that MODEM (MOdelling of EMissions in urban areas) predicts emissions carbon monoxide, total hydrocarbons and nitrogen oxides to be significantly greater than that of the Screening Method developed for the Design Manual for Roads and Bridges (DMRB). The divergence between the models was due in part to emission functions on which each model is based. The results confirmed that the DMRB is not particularly sensitive to changes in speed, and questioned whether detailed speed measurements are advantageous when applying this approach. 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