<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Efficient traffic survey analysis is a catalyst for achieving an efficient and advanced transport planning and sustainable urban development. Unfortunately, the obvious decline in the traffic survey on Nigerian urban roads has left the road transport system to be handicap of traffic data, quality service deliveries and characterized by traffic-related quagmires with devastating socio-economic consequences including congestion, crime and crash incidences. This paper examined traffic survey analysis on major highways in Ogun State, Nigeria using manual traffic count method for estimation of traffic volume and flow pattern. The traffic data gathered were presented and analyzed using descriptive and inferential (ANOVA and Student ‘t’ test) techniques to determine variations in vehicular traffic volume and flow situation (inbound and outbound). Findings revealed that Car/SUV is the most dominant traffic relative to others. Meanwhile, ANOVA results show significant variation in traffic volume on the selected highways (p. value &lt; 0.05), while, the Student ‘t’ test shows no significant difference between traffic inbound and outbound. Findings also revealed that the physical condition of the highways is relatively poor. Based on these findings, the study recommended improvement measures and strategies to curtail traffic-related issues towards achieving efficient, safe, and quality road transport planning in Nigeria.</p></abstract>

Efficient traffic survey analysis is a catalyst for achieving an efficient and advanced transport planning and sustainable urban development. Unfortunately, the obvious decline in the traffic survey on Nigerian urban roads has left the road transport system to be handicap of traffic data, quality service deliveries and characterized by traffic-related quagmires with devastating socio-economic consequences including congestion, crime and crash incidences. This paper examined traffic survey analysis on major highways in Ogun State, Nigeria using manual traffic count method for estimation of traffic volume and flow pattern. The traffic data gathered were presented and analyzed using descriptive and inferential (ANOVA and Student ‘t’ test) techniques to determine variations in vehicular traffic volume and flow situation (inbound and outbound). Findings revealed that Car/SUV is the most dominant traffic relative to others. Meanwhile, ANOVA results show significant variation in traffic volume on the selected highways (p. value < 0.05), while, the Student ‘t’ test shows no significant difference between traffic inbound and outbound. Findings also revealed that the physical condition of the highways is relatively poor. Based on these findings, the study recommended improvement measures and strategies to curtail traffic-related issues towards achieving efficient, safe, and quality road transport planning in Nigeria.

Traffic Survey Analysis: Implications for Road Transport Planning In Nigeria

Department of Urban and Regional Planning

LOGI – Scientific Journal on Transport and Logistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Traffic Survey Analysis: Implications for Road Transport Planning In Nigeria"}

Efficient traffic survey analysis is a catalyst for achieving an efficient and advanced transport planning and sustainable urban development. Unfortunately,...

Traffic Survey Analysis: Implications for Road Transport Planning In Nigeria

Online veröffentlicht: 26. Nov. 2020

Seitenbereich: 12 - 22

Eingereicht: 01. Juni 2020

Akzeptiert: 03. Aug. 2020

DOI: https://doi.org/10.2478/logi-2020-0011

Schlüsselwörter
Highway, traffic volume, traffic flow, manual count

© 2020 Umar Obafemi Salisu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Traffic Survey Analysis: Implications for Road Transport Planning In Nigeria

Online veröffentlicht: 26. Nov. 2020

Seitenbereich: 12 - 22

Eingereicht: 01. Juni 2020

Akzeptiert: 03. Aug. 2020

DOI: https://doi.org/10.2478/logi-2020-0011

SchlüsselwörterHighway, traffic volume, traffic flow, manual count

© 2020 Umar Obafemi Salisu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Highway, traffic volume, traffic flow, manual count